Spaces:
Runtime error
Runtime error
Commit
β’
d152ffd
1
Parent(s):
71496cd
Add application file
Browse filesThis view is limited to 50 files because it contains too many changes. Β
See raw diff
- Gradio.ipynb +1 -0
- datasets/bus.jpg +0 -0
- datasets/s1000/s1000 (1).jpg +0 -0
- datasets/s1000/s1000 (2).jpg +0 -0
- datasets/s1000/s1000 (3).jpg +0 -0
- datasets/s1000/s1000 (4).jpg +0 -0
- datasets/s1000/s1000 (5).jpg +0 -0
- datasets/zidane.jpg +0 -0
- saved_model/s1000_best.pt +3 -0
- saved_model/yolov5s.pt +3 -0
- yolov5/.gitattributes +2 -0
- yolov5/.github/CODE_OF_CONDUCT.md +128 -0
- yolov5/.github/ISSUE_TEMPLATE/bug-report.yml +85 -0
- yolov5/.github/ISSUE_TEMPLATE/config.yml +8 -0
- yolov5/.github/ISSUE_TEMPLATE/feature-request.yml +50 -0
- yolov5/.github/ISSUE_TEMPLATE/question.yml +33 -0
- yolov5/.github/PULL_REQUEST_TEMPLATE.md +9 -0
- yolov5/.github/SECURITY.md +7 -0
- yolov5/.github/dependabot.yml +23 -0
- yolov5/.github/workflows/ci-testing.yml +121 -0
- yolov5/.github/workflows/codeql-analysis.yml +54 -0
- yolov5/.github/workflows/docker.yml +54 -0
- yolov5/.github/workflows/greetings.yml +63 -0
- yolov5/.github/workflows/rebase.yml +21 -0
- yolov5/.github/workflows/stale.yml +38 -0
- yolov5/.gitignore +256 -0
- yolov5/.pre-commit-config.yaml +67 -0
- yolov5/7.1.2 +1 -0
- yolov5/CONTRIBUTING.md +98 -0
- yolov5/LICENSE +674 -0
- yolov5/README.md +300 -0
- yolov5/data/Argoverse.yaml +67 -0
- yolov5/data/GlobalWheat2020.yaml +54 -0
- yolov5/data/Objects365.yaml +114 -0
- yolov5/data/SKU-110K.yaml +53 -0
- yolov5/data/VOC.yaml +81 -0
- yolov5/data/VisDrone.yaml +61 -0
- yolov5/data/coco.yaml +45 -0
- yolov5/data/coco128.yaml +30 -0
- yolov5/data/hyps/hyp.Objects365.yaml +34 -0
- yolov5/data/hyps/hyp.VOC.yaml +40 -0
- yolov5/data/hyps/hyp.scratch-high.yaml +34 -0
- yolov5/data/hyps/hyp.scratch-low.yaml +34 -0
- yolov5/data/hyps/hyp.scratch-med.yaml +34 -0
- yolov5/data/images/bus.jpg +0 -0
- yolov5/data/images/zidane.jpg +0 -0
- yolov5/data/scripts/download_weights.sh +20 -0
- yolov5/data/scripts/get_coco.sh +27 -0
- yolov5/data/scripts/get_coco128.sh +17 -0
- yolov5/data/xView.yaml +102 -0
Gradio.ipynb
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"name":"Gradio.ipynb","provenance":[],"collapsed_sections":[],"authorship_tag":"ABX9TyMP5m/oK5+rqNLpzprjWgfY"},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"}},"cells":[{"cell_type":"code","execution_count":1,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"68CgGISA0OQu","executionInfo":{"status":"ok","timestamp":1657789122929,"user_tz":-180,"elapsed":20255,"user":{"displayName":"orhan ekinci","userId":"08596083551140132378"}},"outputId":"de975cdf-9dd8-4454-f587-bf831c035834"},"outputs":[{"output_type":"stream","name":"stdout","text":["Mounted at /content/drive\n"]}],"source":["from google.colab import drive\n","drive.mount('/content/drive')"]},{"cell_type":"code","source":["!ls \"/content/drive/My Drive/Colab Notebooks/Model Representation/\"\n","%cd drive/My Drive/Colab Notebooks/Model Representation/"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"NN8c3dXt0hfN","executionInfo":{"status":"ok","timestamp":1657789124086,"user_tz":-180,"elapsed":1161,"user":{"displayName":"orhan ekinci","userId":"08596083551140132378"}},"outputId":"0626aab3-f0ea-439e-f487-2c704b22a575"},"execution_count":2,"outputs":[{"output_type":"stream","name":"stdout","text":["datasets flagged Gradio.ipynb saved_model yolov5\n","/content/drive/My Drive/Colab Notebooks/Model Representation\n"]}]},{"cell_type":"code","source":["import os\n","cwd = os.getcwd()\n","cwd"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":35},"id":"vN36F7c50mF4","executionInfo":{"status":"ok","timestamp":1657789124087,"user_tz":-180,"elapsed":11,"user":{"displayName":"orhan ekinci","userId":"08596083551140132378"}},"outputId":"85d491ab-1f37-40bd-f344-0ca02e38065c"},"execution_count":3,"outputs":[{"output_type":"execute_result","data":{"text/plain":["'/content/drive/My Drive/Colab Notebooks/Model Representation'"],"application/vnd.google.colaboratory.intrinsic+json":{"type":"string"}},"metadata":{},"execution_count":3}]},{"cell_type":"code","source":["!pip install -qr https://raw.githubusercontent.com/ultralytics/yolov5/master/requirements.txt gradio # install dependencies"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"8xT1CQBM1Afx","executionInfo":{"status":"ok","timestamp":1657789272147,"user_tz":-180,"elapsed":148069,"user":{"displayName":"orhan ekinci","userId":"08596083551140132378"}},"outputId":"f45c871a-7627-45c3-c529-aca081b2253d"},"execution_count":4,"outputs":[{"output_type":"stream","name":"stdout","text":["\u001b[K |ββββββββββββββββββββββββββββββββ| 5.1 MB 4.3 MB/s \n","\u001b[K |ββββββββββββββββββββββββββββββββ| 596 kB 45.0 MB/s \n","\u001b[K |ββββββββββββββββββββββββββββββββ| 750.6 MB 11 kB/s \n","\u001b[K |ββββββββββββββββββββββββββββββββ| 21.0 MB 1.3 MB/s \n","\u001b[K |ββββββββββββββββββββββββββββββββ| 57 kB 4.5 MB/s \n","\u001b[K |ββββββββββββββββββββββββββββββββ| 54 kB 3.0 MB/s \n","\u001b[K |ββββββββββββββββββββββββββββββββ| 212 kB 59.8 MB/s \n","\u001b[K |ββββββββββββββββββββββββββββββββ| 2.3 MB 44.1 MB/s \n","\u001b[K |ββββββββββββββββββββββββββββββββ| 1.1 MB 50.8 MB/s \n","\u001b[K |ββββββββββββββββββββββββββββββββ| 84 kB 2.7 MB/s \n","\u001b[K |ββββββββββββββββββββββββββββββββ| 140 kB 58.8 MB/s \n","\u001b[K |ββββββββββββββββββββββββββββββββ| 272 kB 43.8 MB/s \n","\u001b[K |ββββββββββββββββββββββββββββββββ| 84 kB 2.9 MB/s \n","\u001b[K |ββββββββββββββββββββββββββββββββ| 94 kB 2.9 MB/s \n","\u001b[K |ββββββββββββββββββββββββββββββββ| 144 kB 47.4 MB/s \n","\u001b[K |ββββββββββββββββββββββββββββββββ| 271 kB 41.4 MB/s \n","\u001b[K |ββββββββββββββββββββββββββββββββ| 63 kB 1.8 MB/s \n","\u001b[K |ββββββββββββββββββββββββββββββββ| 80 kB 8.1 MB/s \n","\u001b[K |ββββββββββββββββββββββββββββββββ| 68 kB 6.1 MB/s \n","\u001b[K |ββββββββββββββββββββββββββββββββ| 54 kB 2.9 MB/s \n","\u001b[K |ββββββββββββββββββββββββββββββββ| 43 kB 2.1 MB/s \n","\u001b[K |ββββββββββββββββββββββββββββββββ| 62 kB 804 kB/s \n","\u001b[K |ββββββββββββββββββββββββββββββββ| 856 kB 59.3 MB/s \n","\u001b[K |ββββββββββββββββββββββββββββββββ| 4.1 MB 42.2 MB/s \n","\u001b[?25h Building wheel for ffmpy (setup.py) ... \u001b[?25l\u001b[?25hdone\n"," Building wheel for python-multipart (setup.py) ... \u001b[?25l\u001b[?25hdone\n","\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n","torchtext 0.13.0 requires torch==1.12.0, but you have torch 1.11.0 which is incompatible.\n","torchaudio 0.12.0+cu113 requires torch==1.12.0, but you have torch 1.11.0 which is incompatible.\u001b[0m\n"]}]},{"cell_type":"code","source":["import gradio as gr\n","import torch\n","from PIL import Image\n","\n","# Images\n","#torch.hub.download_url_to_file('https://github.com/ultralytics/yolov5/raw/master/data/images/zidane.jpg', 'zidane.jpg')\n","#torch.hub.download_url_to_file('https://github.com/ultralytics/yolov5/raw/master/data/images/bus.jpg', 'bus.jpg')\n","\n","# Model\n","#model = torch.hub.load('ultralytics/yolov5', 'yolov5s') # force_reload=True to update\n","\n","model = torch.hub.load(cwd+'/yolov5', 'custom', path=cwd+'/saved_model/yolov5s.pt', source='local') # local model\n","\n","\n","\n","def yolo(im, size=640):\n"," g = (size / max(im.size)) # gain\n"," im = im.resize((int(x * g) for x in im.size), Image.ANTIALIAS) # resize\n","\n"," results = model(im) # inference\n"," results.render() # updates results.imgs with boxes and labels\n"," return Image.fromarray(results.imgs[0])\n","\n","\n","inputs = gr.inputs.Image(type='pil', label=\"Original Image\")\n","outputs = gr.outputs.Image(type=\"pil\", label=\"Output Image\")\n","\n","title = \"YOLOv5\"\n","description = \"YOLOv5 Gradio demo for object detection. Upload an image or click an example image to use.\"\n","article = \"<p style='text-align: center'>YOLOv5 is a family of compound-scaled object detection models trained on the COCO dataset, and includes \" \\\n"," \"simple functionality for Test Time Augmentation (TTA), model ensembling, hyperparameter evolution, \" \\\n"," \"and export to ONNX, CoreML and TFLite. <a href='https://github.com/ultralytics/yolov5'>Source code</a> |\" \\\n"," \"<a href='https://apps.apple.com/app/id1452689527'>iOS App</a> | <a href='https://pytorch.org/hub/ultralytics_yolov5'>PyTorch Hub</a></p>\"\n","\n","examples = [[cwd+'/datasets/zidane.jpg'], [cwd+'/datasets/bus.jpg']]\n","gr.Interface(yolo, inputs, outputs, title=title, description=description, article=article, examples=examples, analytics_enabled=False).launch(\n"," debug=True)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"id":"FwCb9Nmk1n6n","executionInfo":{"status":"ok","timestamp":1657788661371,"user_tz":-180,"elapsed":223749,"user":{"displayName":"orhan ekinci","userId":"08596083551140132378"}},"outputId":"219fa614-9dda-4870-fe54-dfce5b4e4b05"},"execution_count":10,"outputs":[{"output_type":"stream","name":"stderr","text":["\u001b[31m\u001b[1mrequirements:\u001b[0m PyYAML>=5.3.1 not found and is required by YOLOv5, attempting auto-update...\n","Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n","Requirement already satisfied: PyYAML>=5.3.1 in /usr/local/lib/python3.7/dist-packages (6.0)\n","\n","\u001b[31m\u001b[1mrequirements:\u001b[0m torch!=1.12.0,>=1.7.0 not found and is required by YOLOv5, attempting auto-update...\n","Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n","Requirement already satisfied: torch!=1.12.0,>=1.7.0 in /usr/local/lib/python3.7/dist-packages (1.11.0)\n","Requirement already satisfied: typing-extensions in /usr/local/lib/python3.7/dist-packages (from torch!=1.12.0,>=1.7.0) (4.1.1)\n","\n","\u001b[31m\u001b[1mrequirements:\u001b[0m torchvision!=0.13.0,>=0.8.1 not found and is required by YOLOv5, attempting auto-update...\n","Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n","Requirement already satisfied: torchvision!=0.13.0,>=0.8.1 in /usr/local/lib/python3.7/dist-packages (0.12.0)\n","Requirement already satisfied: torch==1.11.0 in /usr/local/lib/python3.7/dist-packages (from torchvision!=0.13.0,>=0.8.1) (1.11.0)\n","Requirement already satisfied: pillow!=8.3.*,>=5.3.0 in /usr/local/lib/python3.7/dist-packages (from torchvision!=0.13.0,>=0.8.1) (7.1.2)\n","Requirement already satisfied: requests in /usr/local/lib/python3.7/dist-packages (from torchvision!=0.13.0,>=0.8.1) (2.23.0)\n","Requirement already satisfied: numpy in /usr/local/lib/python3.7/dist-packages (from torchvision!=0.13.0,>=0.8.1) (1.21.6)\n","Requirement already satisfied: typing-extensions in /usr/local/lib/python3.7/dist-packages (from torchvision!=0.13.0,>=0.8.1) (4.1.1)\n","Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests->torchvision!=0.13.0,>=0.8.1) (3.0.4)\n","Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests->torchvision!=0.13.0,>=0.8.1) (1.24.3)\n","Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests->torchvision!=0.13.0,>=0.8.1) (2022.6.15)\n","Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests->torchvision!=0.13.0,>=0.8.1) (2.10)\n","\n","\u001b[31m\u001b[1mrequirements:\u001b[0m 3 packages updated per /root/.cache/torch/hub/ultralytics_yolov5_master/requirements.txt\n","\u001b[31m\u001b[1mrequirements:\u001b[0m β οΈ \u001b[1mRestart runtime or rerun command for updates to take effect\u001b[0m\n","\n","YOLOv5 π 2022-7-14 Python-3.7.13 torch-1.11.0+cu102 CPU\n","\n","Fusing layers... \n","YOLOv5s summary: 213 layers, 7225885 parameters, 0 gradients\n","Adding AutoShape... \n","/usr/local/lib/python3.7/dist-packages/gradio/deprecation.py:40: UserWarning: `optional` parameter is deprecated, and it has no effect\n"," warnings.warn(value)\n"]},{"output_type":"stream","name":"stdout","text":["Colab notebook detected. This cell will run indefinitely so that you can see errors and logs. To turn off, set debug=False in launch().\n"]},{"output_type":"stream","name":"stderr","text":["Connected (version 2.0, client OpenSSH_7.6p1)\n","Authentication (publickey) successful!\n"]},{"output_type":"stream","name":"stdout","text":["Running on public URL: https://21879.gradio.app\n","\n","This share link expires in 72 hours. For free permanent hosting, check out Spaces (https://huggingface.co/spaces)\n"]},{"output_type":"display_data","data":{"text/plain":["<IPython.core.display.HTML object>"],"text/html":["<div><iframe src=\"https://21879.gradio.app\" width=\"900\" height=\"500\" allow=\"autoplay; camera; microphone;\" frameborder=\"0\" allowfullscreen></iframe></div>"]},"metadata":{}},{"output_type":"stream","name":"stdout","text":["Keyboard interruption in main thread... closing server.\n"]},{"output_type":"execute_result","data":{"text/plain":["(<gradio.routes.App at 0x7f39e2421b50>,\n"," 'http://127.0.0.1:7860/',\n"," 'https://21879.gradio.app')"]},"metadata":{},"execution_count":10}]},{"cell_type":"code","source":["import gradio as gr\n","import torch\n","from PIL import Image\n","\n","# Images\n","#torch.hub.download_url_to_file('https://github.com/ultralytics/yolov5/raw/master/data/images/zidane.jpg', 'zidane.jpg')\n","#torch.hub.download_url_to_file('https://github.com/ultralytics/yolov5/raw/master/data/images/bus.jpg', 'bus.jpg')\n","\n","# Model\n","#model = torch.hub.load('ultralytics/yolov5', 'yolov5s') # force_reload=True to update\n","model = torch.hub.load(cwd+'/yolov5', 'custom', path=cwd+'/saved_model/s1000_best.pt', source='local') # local model\n","\n","\n","def yolo(im, size=640):\n"," g = (size / max(im.size)) # gain\n"," im = im.resize((int(x * g) for x in im.size), Image.ANTIALIAS) # resize\n","\n"," results = model(im) # inference\n"," results.render() # updates results.imgs with boxes and labels\n"," return Image.fromarray(results.imgs[0])\n","\n","\n","inputs = gr.inputs.Image(type='pil', label=\"Original Image\")\n","outputs = gr.outputs.Image(type=\"pil\", label=\"Output Image\")\n","\n","title = \"YOLOv5\"\n","description = \"YOLOv5 Gradio demo for object detection. Upload an image or click an example image to use.\"\n","article = \"<p style='text-align: center'>YOLOv5 is a family of compound-scaled object detection models trained on the COCO dataset, and includes \" \\\n"," \"simple functionality for Test Time Augmentation (TTA), model ensembling, hyperparameter evolution, \" \\\n"," \"and export to ONNX, CoreML and TFLite. <a href='https://github.com/ultralytics/yolov5'>Source code</a> |\" \\\n"," \"<a href='https://apps.apple.com/app/id1452689527'>iOS App</a> | <a href='https://pytorch.org/hub/ultralytics_yolov5'>PyTorch Hub</a></p>\"\n","\n","path_folder = cwd+'/datasets/s1000/'\n","examples = [[path_folder+'s1000 (1).png'], [path_folder+'s1000 (2).png'],[path_folder+'s1000 (3).png'],[path_folder+'s1000 (4).png'],[path_folder+'s1000 (5).png']]\n","gr.Interface(yolo, inputs, outputs, title=title, description=description, article=article, examples=examples, analytics_enabled=False).launch(\n"," debug=True)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"id":"8kaOPNyz2cEr","executionInfo":{"status":"ok","timestamp":1657789820492,"user_tz":-180,"elapsed":541032,"user":{"displayName":"orhan ekinci","userId":"08596083551140132378"}},"outputId":"dd0ad238-a602-4bd0-e610-2f523a37d378"},"execution_count":5,"outputs":[{"output_type":"stream","name":"stderr","text":["\u001b[31m\u001b[1mrequirements:\u001b[0m PyYAML>=5.3.1 not found and is required by YOLOv5, attempting auto-update...\n","Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n","Requirement already satisfied: PyYAML>=5.3.1 in /usr/local/lib/python3.7/dist-packages (6.0)\n","\n","\u001b[31m\u001b[1mrequirements:\u001b[0m torch>=1.7.0 not found and is required by YOLOv5, attempting auto-update...\n","Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n","Requirement already satisfied: torch>=1.7.0 in /usr/local/lib/python3.7/dist-packages (1.11.0)\n","Requirement already satisfied: typing-extensions in /usr/local/lib/python3.7/dist-packages (from torch>=1.7.0) (4.1.1)\n","\n","\u001b[31m\u001b[1mrequirements:\u001b[0m torchvision>=0.8.1 not found and is required by YOLOv5, attempting auto-update...\n","Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n","Requirement already satisfied: torchvision>=0.8.1 in /usr/local/lib/python3.7/dist-packages (0.12.0)\n","Requirement already satisfied: numpy in /usr/local/lib/python3.7/dist-packages (from torchvision>=0.8.1) (1.21.6)\n","Requirement already satisfied: pillow!=8.3.*,>=5.3.0 in /usr/local/lib/python3.7/dist-packages (from torchvision>=0.8.1) (7.1.2)\n","Requirement already satisfied: torch==1.11.0 in /usr/local/lib/python3.7/dist-packages (from torchvision>=0.8.1) (1.11.0)\n","Requirement already satisfied: requests in /usr/local/lib/python3.7/dist-packages (from torchvision>=0.8.1) (2.23.0)\n","Requirement already satisfied: typing-extensions in /usr/local/lib/python3.7/dist-packages (from torchvision>=0.8.1) (4.1.1)\n","Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests->torchvision>=0.8.1) (2.10)\n","Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests->torchvision>=0.8.1) (1.24.3)\n","Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests->torchvision>=0.8.1) (3.0.4)\n","Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests->torchvision>=0.8.1) (2022.6.15)\n","\n","\u001b[31m\u001b[1mrequirements:\u001b[0m 3 packages updated per /content/drive/My Drive/Colab Notebooks/Model Representation/yolov5/requirements.txt\n","\u001b[31m\u001b[1mrequirements:\u001b[0m β οΈ \u001b[1mRestart runtime or rerun command for updates to take effect\u001b[0m\n","\n","YOLOv5 π 2022-6-24 Python-3.7.13 torch-1.11.0+cu102 CPU\n","\n","Fusing layers... \n","Model summary: 213 layers, 7012822 parameters, 0 gradients\n","Adding AutoShape... \n","/usr/local/lib/python3.7/dist-packages/gradio/deprecation.py:40: UserWarning: `optional` parameter is deprecated, and it has no effect\n"," warnings.warn(value)\n"]},{"output_type":"stream","name":"stdout","text":["Colab notebook detected. This cell will run indefinitely so that you can see errors and logs. To turn off, set debug=False in launch().\n"]},{"output_type":"stream","name":"stderr","text":["Connected (version 2.0, client OpenSSH_7.6p1)\n","Authentication (publickey) successful!\n"]},{"output_type":"stream","name":"stdout","text":["Running on public URL: https://32048.gradio.app\n","\n","This share link expires in 72 hours. For free permanent hosting, check out Spaces (https://huggingface.co/spaces)\n"]},{"output_type":"display_data","data":{"text/plain":["<IPython.core.display.HTML object>"],"text/html":["<div><iframe src=\"https://32048.gradio.app\" width=\"900\" height=\"500\" allow=\"autoplay; camera; microphone;\" frameborder=\"0\" allowfullscreen></iframe></div>"]},"metadata":{}},{"output_type":"stream","name":"stderr","text":["Traceback (most recent call last):\n"," File \"/usr/local/lib/python3.7/dist-packages/gradio/routes.py\", line 256, in run_predict\n"," fn_index, raw_input, username, session_state\n"," File \"/usr/local/lib/python3.7/dist-packages/gradio/blocks.py\", line 548, in process_api\n"," predictions, duration = await self.call_function(fn_index, processed_input)\n"," File \"/usr/local/lib/python3.7/dist-packages/gradio/blocks.py\", line 464, in call_function\n"," block_fn.fn, *processed_input, limiter=self.limiter\n"," File \"/usr/local/lib/python3.7/dist-packages/anyio/to_thread.py\", line 32, in run_sync\n"," func, *args, cancellable=cancellable, limiter=limiter\n"," File \"/usr/local/lib/python3.7/dist-packages/anyio/_backends/_asyncio.py\", line 937, in run_sync_in_worker_thread\n"," return await future\n"," File \"/usr/local/lib/python3.7/dist-packages/anyio/_backends/_asyncio.py\", line 867, in run\n"," result = context.run(func, *args)\n"," File \"/usr/local/lib/python3.7/dist-packages/gradio/interface.py\", line 515, in <lambda>\n"," if len(self.output_components) == 1\n"," File \"/usr/local/lib/python3.7/dist-packages/gradio/interface.py\", line 718, in run_prediction\n"," prediction = predict_fn(*processed_input)\n"," File \"<ipython-input-5-7438d39302b1>\", line 15, in yolo\n"," g = (size / max(im.size)) # gain\n","AttributeError: 'NoneType' object has no attribute 'size'\n"]},{"output_type":"stream","name":"stdout","text":["Keyboard interruption in main thread... closing server.\n"]},{"output_type":"execute_result","data":{"text/plain":["(<gradio.routes.App at 0x7f9be15b0ed0>,\n"," 'http://127.0.0.1:7860/',\n"," 'https://32048.gradio.app')"]},"metadata":{},"execution_count":5}]}]}
|
datasets/bus.jpg
ADDED
![]() |
datasets/s1000/s1000 (1).jpg
ADDED
![]() |
datasets/s1000/s1000 (2).jpg
ADDED
![]() |
datasets/s1000/s1000 (3).jpg
ADDED
![]() |
datasets/s1000/s1000 (4).jpg
ADDED
![]() |
datasets/s1000/s1000 (5).jpg
ADDED
![]() |
datasets/zidane.jpg
ADDED
![]() |
saved_model/s1000_best.pt
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:19c8454fdec99b2a9c7bf2894d3df671f04795ea3b09cd0f02ef09a5110de561
|
3 |
+
size 14359221
|
saved_model/yolov5s.pt
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:8b3b748c1e592ddd8868022e8732fde20025197328490623cc16c6f24d0782ee
|
3 |
+
size 14808437
|
yolov5/.gitattributes
ADDED
@@ -0,0 +1,2 @@
|
|
|
|
|
|
|
1 |
+
# this drop notebooks from GitHub language stats
|
2 |
+
*.ipynb linguist-vendored
|
yolov5/.github/CODE_OF_CONDUCT.md
ADDED
@@ -0,0 +1,128 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
# YOLOv5 π Contributor Covenant Code of Conduct
|
2 |
+
|
3 |
+
## Our Pledge
|
4 |
+
|
5 |
+
We as members, contributors, and leaders pledge to make participation in our
|
6 |
+
community a harassment-free experience for everyone, regardless of age, body
|
7 |
+
size, visible or invisible disability, ethnicity, sex characteristics, gender
|
8 |
+
identity and expression, level of experience, education, socio-economic status,
|
9 |
+
nationality, personal appearance, race, religion, or sexual identity
|
10 |
+
and orientation.
|
11 |
+
|
12 |
+
We pledge to act and interact in ways that contribute to an open, welcoming,
|
13 |
+
diverse, inclusive, and healthy community.
|
14 |
+
|
15 |
+
## Our Standards
|
16 |
+
|
17 |
+
Examples of behavior that contributes to a positive environment for our
|
18 |
+
community include:
|
19 |
+
|
20 |
+
- Demonstrating empathy and kindness toward other people
|
21 |
+
- Being respectful of differing opinions, viewpoints, and experiences
|
22 |
+
- Giving and gracefully accepting constructive feedback
|
23 |
+
- Accepting responsibility and apologizing to those affected by our mistakes,
|
24 |
+
and learning from the experience
|
25 |
+
- Focusing on what is best not just for us as individuals, but for the
|
26 |
+
overall community
|
27 |
+
|
28 |
+
Examples of unacceptable behavior include:
|
29 |
+
|
30 |
+
- The use of sexualized language or imagery, and sexual attention or
|
31 |
+
advances of any kind
|
32 |
+
- Trolling, insulting or derogatory comments, and personal or political attacks
|
33 |
+
- Public or private harassment
|
34 |
+
- Publishing others' private information, such as a physical or email
|
35 |
+
address, without their explicit permission
|
36 |
+
- Other conduct which could reasonably be considered inappropriate in a
|
37 |
+
professional setting
|
38 |
+
|
39 |
+
## Enforcement Responsibilities
|
40 |
+
|
41 |
+
Community leaders are responsible for clarifying and enforcing our standards of
|
42 |
+
acceptable behavior and will take appropriate and fair corrective action in
|
43 |
+
response to any behavior that they deem inappropriate, threatening, offensive,
|
44 |
+
or harmful.
|
45 |
+
|
46 |
+
Community leaders have the right and responsibility to remove, edit, or reject
|
47 |
+
comments, commits, code, wiki edits, issues, and other contributions that are
|
48 |
+
not aligned to this Code of Conduct, and will communicate reasons for moderation
|
49 |
+
decisions when appropriate.
|
50 |
+
|
51 |
+
## Scope
|
52 |
+
|
53 |
+
This Code of Conduct applies within all community spaces, and also applies when
|
54 |
+
an individual is officially representing the community in public spaces.
|
55 |
+
Examples of representing our community include using an official e-mail address,
|
56 |
+
posting via an official social media account, or acting as an appointed
|
57 |
+
representative at an online or offline event.
|
58 |
+
|
59 |
+
## Enforcement
|
60 |
+
|
61 |
+
Instances of abusive, harassing, or otherwise unacceptable behavior may be
|
62 |
+
reported to the community leaders responsible for enforcement at
|
63 |
+
hello@ultralytics.com.
|
64 |
+
All complaints will be reviewed and investigated promptly and fairly.
|
65 |
+
|
66 |
+
All community leaders are obligated to respect the privacy and security of the
|
67 |
+
reporter of any incident.
|
68 |
+
|
69 |
+
## Enforcement Guidelines
|
70 |
+
|
71 |
+
Community leaders will follow these Community Impact Guidelines in determining
|
72 |
+
the consequences for any action they deem in violation of this Code of Conduct:
|
73 |
+
|
74 |
+
### 1. Correction
|
75 |
+
|
76 |
+
**Community Impact**: Use of inappropriate language or other behavior deemed
|
77 |
+
unprofessional or unwelcome in the community.
|
78 |
+
|
79 |
+
**Consequence**: A private, written warning from community leaders, providing
|
80 |
+
clarity around the nature of the violation and an explanation of why the
|
81 |
+
behavior was inappropriate. A public apology may be requested.
|
82 |
+
|
83 |
+
### 2. Warning
|
84 |
+
|
85 |
+
**Community Impact**: A violation through a single incident or series
|
86 |
+
of actions.
|
87 |
+
|
88 |
+
**Consequence**: A warning with consequences for continued behavior. No
|
89 |
+
interaction with the people involved, including unsolicited interaction with
|
90 |
+
those enforcing the Code of Conduct, for a specified period of time. This
|
91 |
+
includes avoiding interactions in community spaces as well as external channels
|
92 |
+
like social media. Violating these terms may lead to a temporary or
|
93 |
+
permanent ban.
|
94 |
+
|
95 |
+
### 3. Temporary Ban
|
96 |
+
|
97 |
+
**Community Impact**: A serious violation of community standards, including
|
98 |
+
sustained inappropriate behavior.
|
99 |
+
|
100 |
+
**Consequence**: A temporary ban from any sort of interaction or public
|
101 |
+
communication with the community for a specified period of time. No public or
|
102 |
+
private interaction with the people involved, including unsolicited interaction
|
103 |
+
with those enforcing the Code of Conduct, is allowed during this period.
|
104 |
+
Violating these terms may lead to a permanent ban.
|
105 |
+
|
106 |
+
### 4. Permanent Ban
|
107 |
+
|
108 |
+
**Community Impact**: Demonstrating a pattern of violation of community
|
109 |
+
standards, including sustained inappropriate behavior, harassment of an
|
110 |
+
individual, or aggression toward or disparagement of classes of individuals.
|
111 |
+
|
112 |
+
**Consequence**: A permanent ban from any sort of public interaction within
|
113 |
+
the community.
|
114 |
+
|
115 |
+
## Attribution
|
116 |
+
|
117 |
+
This Code of Conduct is adapted from the [Contributor Covenant][homepage],
|
118 |
+
version 2.0, available at
|
119 |
+
https://www.contributor-covenant.org/version/2/0/code_of_conduct.html.
|
120 |
+
|
121 |
+
Community Impact Guidelines were inspired by [Mozilla's code of conduct
|
122 |
+
enforcement ladder](https://github.com/mozilla/diversity).
|
123 |
+
|
124 |
+
For answers to common questions about this code of conduct, see the FAQ at
|
125 |
+
https://www.contributor-covenant.org/faq. Translations are available at
|
126 |
+
https://www.contributor-covenant.org/translations.
|
127 |
+
|
128 |
+
[homepage]: https://www.contributor-covenant.org
|
yolov5/.github/ISSUE_TEMPLATE/bug-report.yml
ADDED
@@ -0,0 +1,85 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
name: π Bug Report
|
2 |
+
# title: " "
|
3 |
+
description: Problems with YOLOv5
|
4 |
+
labels: [bug, triage]
|
5 |
+
body:
|
6 |
+
- type: markdown
|
7 |
+
attributes:
|
8 |
+
value: |
|
9 |
+
Thank you for submitting a YOLOv5 π Bug Report!
|
10 |
+
|
11 |
+
- type: checkboxes
|
12 |
+
attributes:
|
13 |
+
label: Search before asking
|
14 |
+
description: >
|
15 |
+
Please search the [issues](https://github.com/ultralytics/yolov5/issues) to see if a similar bug report already exists.
|
16 |
+
options:
|
17 |
+
- label: >
|
18 |
+
I have searched the YOLOv5 [issues](https://github.com/ultralytics/yolov5/issues) and found no similar bug report.
|
19 |
+
required: true
|
20 |
+
|
21 |
+
- type: dropdown
|
22 |
+
attributes:
|
23 |
+
label: YOLOv5 Component
|
24 |
+
description: |
|
25 |
+
Please select the part of YOLOv5 where you found the bug.
|
26 |
+
multiple: true
|
27 |
+
options:
|
28 |
+
- "Training"
|
29 |
+
- "Validation"
|
30 |
+
- "Detection"
|
31 |
+
- "Export"
|
32 |
+
- "PyTorch Hub"
|
33 |
+
- "Multi-GPU"
|
34 |
+
- "Evolution"
|
35 |
+
- "Integrations"
|
36 |
+
- "Other"
|
37 |
+
validations:
|
38 |
+
required: false
|
39 |
+
|
40 |
+
- type: textarea
|
41 |
+
attributes:
|
42 |
+
label: Bug
|
43 |
+
description: Provide console output with error messages and/or screenshots of the bug.
|
44 |
+
placeholder: |
|
45 |
+
π‘ ProTip! Include as much information as possible (screenshots, logs, tracebacks etc.) to receive the most helpful response.
|
46 |
+
validations:
|
47 |
+
required: true
|
48 |
+
|
49 |
+
- type: textarea
|
50 |
+
attributes:
|
51 |
+
label: Environment
|
52 |
+
description: Please specify the software and hardware you used to produce the bug.
|
53 |
+
placeholder: |
|
54 |
+
- YOLO: YOLOv5 π v6.0-67-g60e42e1 torch 1.9.0+cu111 CUDA:0 (A100-SXM4-40GB, 40536MiB)
|
55 |
+
- OS: Ubuntu 20.04
|
56 |
+
- Python: 3.9.0
|
57 |
+
validations:
|
58 |
+
required: false
|
59 |
+
|
60 |
+
- type: textarea
|
61 |
+
attributes:
|
62 |
+
label: Minimal Reproducible Example
|
63 |
+
description: >
|
64 |
+
When asking a question, people will be better able to provide help if you provide code that they can easily understand and use to **reproduce** the problem.
|
65 |
+
This is referred to by community members as creating a [minimal reproducible example](https://stackoverflow.com/help/minimal-reproducible-example).
|
66 |
+
placeholder: |
|
67 |
+
```
|
68 |
+
# Code to reproduce your issue here
|
69 |
+
```
|
70 |
+
validations:
|
71 |
+
required: false
|
72 |
+
|
73 |
+
- type: textarea
|
74 |
+
attributes:
|
75 |
+
label: Additional
|
76 |
+
description: Anything else you would like to share?
|
77 |
+
|
78 |
+
- type: checkboxes
|
79 |
+
attributes:
|
80 |
+
label: Are you willing to submit a PR?
|
81 |
+
description: >
|
82 |
+
(Optional) We encourage you to submit a [Pull Request](https://github.com/ultralytics/yolov5/pulls) (PR) to help improve YOLOv5 for everyone, especially if you have a good understanding of how to implement a fix or feature.
|
83 |
+
See the YOLOv5 [Contributing Guide](https://github.com/ultralytics/yolov5/blob/master/CONTRIBUTING.md) to get started.
|
84 |
+
options:
|
85 |
+
- label: Yes I'd like to help by submitting a PR!
|
yolov5/.github/ISSUE_TEMPLATE/config.yml
ADDED
@@ -0,0 +1,8 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
blank_issues_enabled: true
|
2 |
+
contact_links:
|
3 |
+
- name: π¬ Forum
|
4 |
+
url: https://community.ultralytics.com/
|
5 |
+
about: Ask on Ultralytics Community Forum
|
6 |
+
- name: Stack Overflow
|
7 |
+
url: https://stackoverflow.com/search?q=YOLOv5
|
8 |
+
about: Ask on Stack Overflow with 'YOLOv5' tag
|
yolov5/.github/ISSUE_TEMPLATE/feature-request.yml
ADDED
@@ -0,0 +1,50 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
name: π Feature Request
|
2 |
+
description: Suggest a YOLOv5 idea
|
3 |
+
# title: " "
|
4 |
+
labels: [enhancement]
|
5 |
+
body:
|
6 |
+
- type: markdown
|
7 |
+
attributes:
|
8 |
+
value: |
|
9 |
+
Thank you for submitting a YOLOv5 π Feature Request!
|
10 |
+
|
11 |
+
- type: checkboxes
|
12 |
+
attributes:
|
13 |
+
label: Search before asking
|
14 |
+
description: >
|
15 |
+
Please search the [issues](https://github.com/ultralytics/yolov5/issues) to see if a similar feature request already exists.
|
16 |
+
options:
|
17 |
+
- label: >
|
18 |
+
I have searched the YOLOv5 [issues](https://github.com/ultralytics/yolov5/issues) and found no similar feature requests.
|
19 |
+
required: true
|
20 |
+
|
21 |
+
- type: textarea
|
22 |
+
attributes:
|
23 |
+
label: Description
|
24 |
+
description: A short description of your feature.
|
25 |
+
placeholder: |
|
26 |
+
What new feature would you like to see in YOLOv5?
|
27 |
+
validations:
|
28 |
+
required: true
|
29 |
+
|
30 |
+
- type: textarea
|
31 |
+
attributes:
|
32 |
+
label: Use case
|
33 |
+
description: |
|
34 |
+
Describe the use case of your feature request. It will help us understand and prioritize the feature request.
|
35 |
+
placeholder: |
|
36 |
+
How would this feature be used, and who would use it?
|
37 |
+
|
38 |
+
- type: textarea
|
39 |
+
attributes:
|
40 |
+
label: Additional
|
41 |
+
description: Anything else you would like to share?
|
42 |
+
|
43 |
+
- type: checkboxes
|
44 |
+
attributes:
|
45 |
+
label: Are you willing to submit a PR?
|
46 |
+
description: >
|
47 |
+
(Optional) We encourage you to submit a [Pull Request](https://github.com/ultralytics/yolov5/pulls) (PR) to help improve YOLOv5 for everyone, especially if you have a good understanding of how to implement a fix or feature.
|
48 |
+
See the YOLOv5 [Contributing Guide](https://github.com/ultralytics/yolov5/blob/master/CONTRIBUTING.md) to get started.
|
49 |
+
options:
|
50 |
+
- label: Yes I'd like to help by submitting a PR!
|
yolov5/.github/ISSUE_TEMPLATE/question.yml
ADDED
@@ -0,0 +1,33 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
name: β Question
|
2 |
+
description: Ask a YOLOv5 question
|
3 |
+
# title: " "
|
4 |
+
labels: [question]
|
5 |
+
body:
|
6 |
+
- type: markdown
|
7 |
+
attributes:
|
8 |
+
value: |
|
9 |
+
Thank you for asking a YOLOv5 β Question!
|
10 |
+
|
11 |
+
- type: checkboxes
|
12 |
+
attributes:
|
13 |
+
label: Search before asking
|
14 |
+
description: >
|
15 |
+
Please search the [issues](https://github.com/ultralytics/yolov5/issues) and [discussions](https://github.com/ultralytics/yolov5/discussions) to see if a similar question already exists.
|
16 |
+
options:
|
17 |
+
- label: >
|
18 |
+
I have searched the YOLOv5 [issues](https://github.com/ultralytics/yolov5/issues) and [discussions](https://github.com/ultralytics/yolov5/discussions) and found no similar questions.
|
19 |
+
required: true
|
20 |
+
|
21 |
+
- type: textarea
|
22 |
+
attributes:
|
23 |
+
label: Question
|
24 |
+
description: What is your question?
|
25 |
+
placeholder: |
|
26 |
+
π‘ ProTip! Include as much information as possible (screenshots, logs, tracebacks etc.) to receive the most helpful response.
|
27 |
+
validations:
|
28 |
+
required: true
|
29 |
+
|
30 |
+
- type: textarea
|
31 |
+
attributes:
|
32 |
+
label: Additional
|
33 |
+
description: Anything else you would like to share?
|
yolov5/.github/PULL_REQUEST_TEMPLATE.md
ADDED
@@ -0,0 +1,9 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
<!--
|
2 |
+
Thank you for submitting a YOLOv5 π Pull Request! We want to make contributing to YOLOv5 as easy and transparent as possible. A few tips to get you started:
|
3 |
+
|
4 |
+
- Search existing YOLOv5 [PRs](https://github.com/ultralytics/yolov5/pull) to see if a similar PR already exists.
|
5 |
+
- Link this PR to a YOLOv5 [issue](https://github.com/ultralytics/yolov5/issues) to help us understand what bug fix or feature is being implemented.
|
6 |
+
- Provide before and after profiling/inference/training results to help us quantify the improvement your PR provides (if applicable).
|
7 |
+
|
8 |
+
Please see our β
[Contributing Guide](https://github.com/ultralytics/yolov5/blob/master/CONTRIBUTING.md) for more details.
|
9 |
+
-->
|
yolov5/.github/SECURITY.md
ADDED
@@ -0,0 +1,7 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
# Security Policy
|
2 |
+
|
3 |
+
We aim to make YOLOv5 π as secure as possible! If you find potential vulnerabilities or have any concerns please let us know so we can investigate and take corrective action if needed.
|
4 |
+
|
5 |
+
### Reporting a Vulnerability
|
6 |
+
|
7 |
+
To report vulnerabilities please email us at hello@ultralytics.com or visit https://ultralytics.com/contact. Thank you!
|
yolov5/.github/dependabot.yml
ADDED
@@ -0,0 +1,23 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
version: 2
|
2 |
+
updates:
|
3 |
+
- package-ecosystem: pip
|
4 |
+
directory: "/"
|
5 |
+
schedule:
|
6 |
+
interval: weekly
|
7 |
+
time: "04:00"
|
8 |
+
open-pull-requests-limit: 10
|
9 |
+
reviewers:
|
10 |
+
- glenn-jocher
|
11 |
+
labels:
|
12 |
+
- dependencies
|
13 |
+
|
14 |
+
- package-ecosystem: github-actions
|
15 |
+
directory: "/"
|
16 |
+
schedule:
|
17 |
+
interval: weekly
|
18 |
+
time: "04:00"
|
19 |
+
open-pull-requests-limit: 5
|
20 |
+
reviewers:
|
21 |
+
- glenn-jocher
|
22 |
+
labels:
|
23 |
+
- dependencies
|
yolov5/.github/workflows/ci-testing.yml
ADDED
@@ -0,0 +1,121 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
# YOLOv5 π by Ultralytics, GPL-3.0 license
|
2 |
+
# YOLOv5 Continuous Integration (CI) GitHub Actions tests
|
3 |
+
|
4 |
+
name: YOLOv5 CI
|
5 |
+
|
6 |
+
on:
|
7 |
+
push:
|
8 |
+
branches: [master]
|
9 |
+
pull_request:
|
10 |
+
branches: [master]
|
11 |
+
schedule:
|
12 |
+
- cron: '0 0 * * *' # runs at 00:00 UTC every day
|
13 |
+
|
14 |
+
jobs:
|
15 |
+
Benchmarks:
|
16 |
+
runs-on: ${{ matrix.os }}
|
17 |
+
strategy:
|
18 |
+
matrix:
|
19 |
+
os: [ubuntu-latest]
|
20 |
+
python-version: [3.9]
|
21 |
+
model: [yolov5n]
|
22 |
+
steps:
|
23 |
+
- uses: actions/checkout@v3
|
24 |
+
- uses: actions/setup-python@v4
|
25 |
+
with:
|
26 |
+
python-version: ${{ matrix.python-version }}
|
27 |
+
#- name: Cache pip
|
28 |
+
# uses: actions/cache@v3
|
29 |
+
# with:
|
30 |
+
# path: ~/.cache/pip
|
31 |
+
# key: ${{ runner.os }}-Benchmarks-${{ hashFiles('requirements.txt') }}
|
32 |
+
# restore-keys: ${{ runner.os }}-Benchmarks-
|
33 |
+
- name: Install requirements
|
34 |
+
run: |
|
35 |
+
python -m pip install --upgrade pip
|
36 |
+
pip install -r requirements.txt coremltools openvino-dev tensorflow-cpu --extra-index-url https://download.pytorch.org/whl/cpu
|
37 |
+
python --version
|
38 |
+
pip --version
|
39 |
+
pip list
|
40 |
+
- name: Run benchmarks
|
41 |
+
run: |
|
42 |
+
python utils/benchmarks.py --weights ${{ matrix.model }}.pt --img 320
|
43 |
+
|
44 |
+
Tests:
|
45 |
+
timeout-minutes: 60
|
46 |
+
runs-on: ${{ matrix.os }}
|
47 |
+
strategy:
|
48 |
+
fail-fast: false
|
49 |
+
matrix:
|
50 |
+
os: [ubuntu-latest, macos-latest, windows-latest]
|
51 |
+
python-version: [3.9]
|
52 |
+
model: [yolov5n]
|
53 |
+
include:
|
54 |
+
- os: ubuntu-latest
|
55 |
+
python-version: '3.7' # '3.6.8' min
|
56 |
+
model: yolov5n
|
57 |
+
- os: ubuntu-latest
|
58 |
+
python-version: '3.8'
|
59 |
+
model: yolov5n
|
60 |
+
- os: ubuntu-latest
|
61 |
+
python-version: '3.10'
|
62 |
+
model: yolov5n
|
63 |
+
steps:
|
64 |
+
- uses: actions/checkout@v3
|
65 |
+
- uses: actions/setup-python@v4
|
66 |
+
with:
|
67 |
+
python-version: ${{ matrix.python-version }}
|
68 |
+
- name: Get cache dir
|
69 |
+
# https://github.com/actions/cache/blob/master/examples.md#multiple-oss-in-a-workflow
|
70 |
+
id: pip-cache
|
71 |
+
run: echo "::set-output name=dir::$(pip cache dir)"
|
72 |
+
- name: Cache pip
|
73 |
+
uses: actions/cache@v3
|
74 |
+
with:
|
75 |
+
path: ${{ steps.pip-cache.outputs.dir }}
|
76 |
+
key: ${{ runner.os }}-${{ matrix.python-version }}-pip-${{ hashFiles('requirements.txt') }}
|
77 |
+
restore-keys: ${{ runner.os }}-${{ matrix.python-version }}-pip-
|
78 |
+
- name: Install requirements
|
79 |
+
run: |
|
80 |
+
python -m pip install --upgrade pip
|
81 |
+
pip install -r requirements.txt --extra-index-url https://download.pytorch.org/whl/cpu
|
82 |
+
python --version
|
83 |
+
pip --version
|
84 |
+
pip list
|
85 |
+
- name: Check environment
|
86 |
+
run: |
|
87 |
+
python -c "import utils; utils.notebook_init()"
|
88 |
+
echo "RUNNER_OS is $RUNNER_OS"
|
89 |
+
echo "GITHUB_EVENT_NAME is $GITHUB_EVENT_NAME"
|
90 |
+
echo "GITHUB_WORKFLOW is $GITHUB_WORKFLOW"
|
91 |
+
echo "GITHUB_ACTOR is $GITHUB_ACTOR"
|
92 |
+
echo "GITHUB_REPOSITORY is $GITHUB_REPOSITORY"
|
93 |
+
echo "GITHUB_REPOSITORY_OWNER is $GITHUB_REPOSITORY_OWNER"
|
94 |
+
- name: Run tests
|
95 |
+
shell: bash
|
96 |
+
run: |
|
97 |
+
# export PYTHONPATH="$PWD" # to run '$ python *.py' files in subdirectories
|
98 |
+
d=cpu # device
|
99 |
+
model=${{ matrix.model }}
|
100 |
+
best=runs/train/exp/weights/best.pt
|
101 |
+
# Train
|
102 |
+
python train.py --img 64 --batch 32 --weights $model.pt --cfg $model.yaml --epochs 1 --device $d
|
103 |
+
# Val
|
104 |
+
python val.py --img 64 --batch 32 --weights $model.pt --device $d
|
105 |
+
python val.py --img 64 --batch 32 --weights $best --device $d
|
106 |
+
# Detect
|
107 |
+
python detect.py --weights $model.pt --device $d
|
108 |
+
python detect.py --weights $best --device $d
|
109 |
+
python hubconf.py # hub
|
110 |
+
# Export
|
111 |
+
# python models/tf.py --weights $model.pt # build TF model
|
112 |
+
python models/yolo.py --cfg $model.yaml # build PyTorch model
|
113 |
+
python export.py --weights $model.pt --img 64 --include torchscript # export
|
114 |
+
# Python
|
115 |
+
python - <<EOF
|
116 |
+
import torch
|
117 |
+
model = torch.hub.load('.', 'custom', path='$model', source='local')
|
118 |
+
print(model('data/images/bus.jpg'))
|
119 |
+
model = torch.hub.load('.', 'custom', path='$best', source='local')
|
120 |
+
print(model('data/images/bus.jpg'))
|
121 |
+
EOF
|
yolov5/.github/workflows/codeql-analysis.yml
ADDED
@@ -0,0 +1,54 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
# This action runs GitHub's industry-leading static analysis engine, CodeQL, against a repository's source code to find security vulnerabilities.
|
2 |
+
# https://github.com/github/codeql-action
|
3 |
+
|
4 |
+
name: "CodeQL"
|
5 |
+
|
6 |
+
on:
|
7 |
+
schedule:
|
8 |
+
- cron: '0 0 1 * *' # Runs at 00:00 UTC on the 1st of every month
|
9 |
+
|
10 |
+
jobs:
|
11 |
+
analyze:
|
12 |
+
name: Analyze
|
13 |
+
runs-on: ubuntu-latest
|
14 |
+
|
15 |
+
strategy:
|
16 |
+
fail-fast: false
|
17 |
+
matrix:
|
18 |
+
language: ['python']
|
19 |
+
# CodeQL supports [ 'cpp', 'csharp', 'go', 'java', 'javascript', 'python' ]
|
20 |
+
# Learn more:
|
21 |
+
# https://docs.github.com/en/free-pro-team@latest/github/finding-security-vulnerabilities-and-errors-in-your-code/configuring-code-scanning#changing-the-languages-that-are-analyzed
|
22 |
+
|
23 |
+
steps:
|
24 |
+
- name: Checkout repository
|
25 |
+
uses: actions/checkout@v3
|
26 |
+
|
27 |
+
# Initializes the CodeQL tools for scanning.
|
28 |
+
- name: Initialize CodeQL
|
29 |
+
uses: github/codeql-action/init@v2
|
30 |
+
with:
|
31 |
+
languages: ${{ matrix.language }}
|
32 |
+
# If you wish to specify custom queries, you can do so here or in a config file.
|
33 |
+
# By default, queries listed here will override any specified in a config file.
|
34 |
+
# Prefix the list here with "+" to use these queries and those in the config file.
|
35 |
+
# queries: ./path/to/local/query, your-org/your-repo/queries@main
|
36 |
+
|
37 |
+
# Autobuild attempts to build any compiled languages (C/C++, C#, or Java).
|
38 |
+
# If this step fails, then you should remove it and run the build manually (see below)
|
39 |
+
- name: Autobuild
|
40 |
+
uses: github/codeql-action/autobuild@v2
|
41 |
+
|
42 |
+
# βΉοΈ Command-line programs to run using the OS shell.
|
43 |
+
# π https://git.io/JvXDl
|
44 |
+
|
45 |
+
# βοΈ If the Autobuild fails above, remove it and uncomment the following three lines
|
46 |
+
# and modify them (or add more) to build your code if your project
|
47 |
+
# uses a compiled language
|
48 |
+
|
49 |
+
#- run: |
|
50 |
+
# make bootstrap
|
51 |
+
# make release
|
52 |
+
|
53 |
+
- name: Perform CodeQL Analysis
|
54 |
+
uses: github/codeql-action/analyze@v2
|
yolov5/.github/workflows/docker.yml
ADDED
@@ -0,0 +1,54 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
# YOLOv5 π by Ultralytics, GPL-3.0 license
|
2 |
+
# Builds ultralytics/yolov5:latest images on DockerHub https://hub.docker.com/r/ultralytics/yolov5
|
3 |
+
|
4 |
+
name: Publish Docker Images
|
5 |
+
|
6 |
+
on:
|
7 |
+
push:
|
8 |
+
branches: [ master ]
|
9 |
+
|
10 |
+
jobs:
|
11 |
+
docker:
|
12 |
+
if: github.repository == 'ultralytics/yolov5'
|
13 |
+
name: Push Docker image to Docker Hub
|
14 |
+
runs-on: ubuntu-latest
|
15 |
+
steps:
|
16 |
+
- name: Checkout repo
|
17 |
+
uses: actions/checkout@v3
|
18 |
+
|
19 |
+
- name: Set up QEMU
|
20 |
+
uses: docker/setup-qemu-action@v2
|
21 |
+
|
22 |
+
- name: Set up Docker Buildx
|
23 |
+
uses: docker/setup-buildx-action@v2
|
24 |
+
|
25 |
+
- name: Login to Docker Hub
|
26 |
+
uses: docker/login-action@v2
|
27 |
+
with:
|
28 |
+
username: ${{ secrets.DOCKERHUB_USERNAME }}
|
29 |
+
password: ${{ secrets.DOCKERHUB_TOKEN }}
|
30 |
+
|
31 |
+
- name: Build and push arm64 image
|
32 |
+
uses: docker/build-push-action@v3
|
33 |
+
with:
|
34 |
+
context: .
|
35 |
+
platforms: linux/arm64
|
36 |
+
file: utils/docker/Dockerfile-arm64
|
37 |
+
push: true
|
38 |
+
tags: ultralytics/yolov5:latest-arm64
|
39 |
+
|
40 |
+
- name: Build and push CPU image
|
41 |
+
uses: docker/build-push-action@v3
|
42 |
+
with:
|
43 |
+
context: .
|
44 |
+
file: utils/docker/Dockerfile-cpu
|
45 |
+
push: true
|
46 |
+
tags: ultralytics/yolov5:latest-cpu
|
47 |
+
|
48 |
+
- name: Build and push GPU image
|
49 |
+
uses: docker/build-push-action@v3
|
50 |
+
with:
|
51 |
+
context: .
|
52 |
+
file: utils/docker/Dockerfile
|
53 |
+
push: true
|
54 |
+
tags: ultralytics/yolov5:latest
|
yolov5/.github/workflows/greetings.yml
ADDED
@@ -0,0 +1,63 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
# YOLOv5 π by Ultralytics, GPL-3.0 license
|
2 |
+
|
3 |
+
name: Greetings
|
4 |
+
|
5 |
+
on:
|
6 |
+
pull_request_target:
|
7 |
+
types: [opened]
|
8 |
+
issues:
|
9 |
+
types: [opened]
|
10 |
+
|
11 |
+
jobs:
|
12 |
+
greeting:
|
13 |
+
runs-on: ubuntu-latest
|
14 |
+
steps:
|
15 |
+
- uses: actions/first-interaction@v1
|
16 |
+
with:
|
17 |
+
repo-token: ${{ secrets.GITHUB_TOKEN }}
|
18 |
+
pr-message: |
|
19 |
+
π Hello @${{ github.actor }}, thank you for submitting a YOLOv5 π PR! To allow your work to be integrated as seamlessly as possible, we advise you to:
|
20 |
+
- β
Verify your PR is **up-to-date with upstream/master.** If your PR is behind upstream/master an automatic [GitHub Actions](https://github.com/ultralytics/yolov5/blob/master/.github/workflows/rebase.yml) merge may be attempted by writing /rebase in a new comment, or by running the following code, replacing 'feature' with the name of your local branch:
|
21 |
+
```bash
|
22 |
+
git remote add upstream https://github.com/ultralytics/yolov5.git
|
23 |
+
git fetch upstream
|
24 |
+
# git checkout feature # <--- replace 'feature' with local branch name
|
25 |
+
git merge upstream/master
|
26 |
+
git push -u origin -f
|
27 |
+
```
|
28 |
+
- β
Verify all Continuous Integration (CI) **checks are passing**.
|
29 |
+
- β
Reduce changes to the absolute **minimum** required for your bug fix or feature addition. _"It is not daily increase but daily decrease, hack away the unessential. The closer to the source, the less wastage there is."_ -Bruce Lee
|
30 |
+
|
31 |
+
issue-message: |
|
32 |
+
π Hello @${{ github.actor }}, thank you for your interest in YOLOv5 π! Please visit our βοΈ [Tutorials](https://github.com/ultralytics/yolov5/wiki#tutorials) to get started, where you can find quickstart guides for simple tasks like [Custom Data Training](https://github.com/ultralytics/yolov5/wiki/Train-Custom-Data) all the way to advanced concepts like [Hyperparameter Evolution](https://github.com/ultralytics/yolov5/issues/607).
|
33 |
+
|
34 |
+
If this is a π Bug Report, please provide screenshots and **minimum viable code to reproduce your issue**, otherwise we can not help you.
|
35 |
+
|
36 |
+
If this is a custom training β Question, please provide as much information as possible, including dataset images, training logs, screenshots, and a public link to online [W&B logging](https://github.com/ultralytics/yolov5/wiki/Train-Custom-Data#visualize) if available.
|
37 |
+
|
38 |
+
For business inquiries or professional support requests please visit https://ultralytics.com or email support@ultralytics.com.
|
39 |
+
|
40 |
+
## Requirements
|
41 |
+
|
42 |
+
[**Python>=3.7.0**](https://www.python.org/) with all [requirements.txt](https://github.com/ultralytics/yolov5/blob/master/requirements.txt) installed including [**PyTorch>=1.7**](https://pytorch.org/get-started/locally/). To get started:
|
43 |
+
```bash
|
44 |
+
git clone https://github.com/ultralytics/yolov5 # clone
|
45 |
+
cd yolov5
|
46 |
+
pip install -r requirements.txt # install
|
47 |
+
```
|
48 |
+
|
49 |
+
## Environments
|
50 |
+
|
51 |
+
YOLOv5 may be run in any of the following up-to-date verified environments (with all dependencies including [CUDA](https://developer.nvidia.com/cuda)/[CUDNN](https://developer.nvidia.com/cudnn), [Python](https://www.python.org/) and [PyTorch](https://pytorch.org/) preinstalled):
|
52 |
+
|
53 |
+
- **Google Colab and Kaggle** notebooks with free GPU: <a href="https://colab.research.google.com/github/ultralytics/yolov5/blob/master/tutorial.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a> <a href="https://www.kaggle.com/ultralytics/yolov5"><img src="https://kaggle.com/static/images/open-in-kaggle.svg" alt="Open In Kaggle"></a>
|
54 |
+
- **Google Cloud** Deep Learning VM. See [GCP Quickstart Guide](https://github.com/ultralytics/yolov5/wiki/GCP-Quickstart)
|
55 |
+
- **Amazon** Deep Learning AMI. See [AWS Quickstart Guide](https://github.com/ultralytics/yolov5/wiki/AWS-Quickstart)
|
56 |
+
- **Docker Image**. See [Docker Quickstart Guide](https://github.com/ultralytics/yolov5/wiki/Docker-Quickstart) <a href="https://hub.docker.com/r/ultralytics/yolov5"><img src="https://img.shields.io/docker/pulls/ultralytics/yolov5?logo=docker" alt="Docker Pulls"></a>
|
57 |
+
|
58 |
+
|
59 |
+
## Status
|
60 |
+
|
61 |
+
<a href="https://github.com/ultralytics/yolov5/actions/workflows/ci-testing.yml"><img src="https://github.com/ultralytics/yolov5/actions/workflows/ci-testing.yml/badge.svg" alt="CI CPU testing"></a>
|
62 |
+
|
63 |
+
If this badge is green, all [YOLOv5 GitHub Actions](https://github.com/ultralytics/yolov5/actions) Continuous Integration (CI) tests are currently passing. CI tests verify correct operation of YOLOv5 training ([train.py](https://github.com/ultralytics/yolov5/blob/master/train.py)), validation ([val.py](https://github.com/ultralytics/yolov5/blob/master/val.py)), inference ([detect.py](https://github.com/ultralytics/yolov5/blob/master/detect.py)) and export ([export.py](https://github.com/ultralytics/yolov5/blob/master/export.py)) on macOS, Windows, and Ubuntu every 24 hours and on every commit.
|
yolov5/.github/workflows/rebase.yml
ADDED
@@ -0,0 +1,21 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
# https://github.com/marketplace/actions/automatic-rebase
|
2 |
+
|
3 |
+
name: Automatic Rebase
|
4 |
+
on:
|
5 |
+
issue_comment:
|
6 |
+
types: [created]
|
7 |
+
jobs:
|
8 |
+
rebase:
|
9 |
+
name: Rebase
|
10 |
+
if: github.event.issue.pull_request != '' && contains(github.event.comment.body, '/rebase')
|
11 |
+
runs-on: ubuntu-latest
|
12 |
+
steps:
|
13 |
+
- name: Checkout the latest code
|
14 |
+
uses: actions/checkout@v3
|
15 |
+
with:
|
16 |
+
token: ${{ secrets.ACTIONS_TOKEN }}
|
17 |
+
fetch-depth: 0 # otherwise, you will fail to push refs to dest repo
|
18 |
+
- name: Automatic Rebase
|
19 |
+
uses: cirrus-actions/rebase@1.7
|
20 |
+
env:
|
21 |
+
GITHUB_TOKEN: ${{ secrets.ACTIONS_TOKEN }}
|
yolov5/.github/workflows/stale.yml
ADDED
@@ -0,0 +1,38 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
# YOLOv5 π by Ultralytics, GPL-3.0 license
|
2 |
+
|
3 |
+
name: Close stale issues
|
4 |
+
on:
|
5 |
+
schedule:
|
6 |
+
- cron: '0 0 * * *' # Runs at 00:00 UTC every day
|
7 |
+
|
8 |
+
jobs:
|
9 |
+
stale:
|
10 |
+
runs-on: ubuntu-latest
|
11 |
+
steps:
|
12 |
+
- uses: actions/stale@v5
|
13 |
+
with:
|
14 |
+
repo-token: ${{ secrets.GITHUB_TOKEN }}
|
15 |
+
stale-issue-message: |
|
16 |
+
π Hello, this issue has been automatically marked as stale because it has not had recent activity. Please note it will be closed if no further activity occurs.
|
17 |
+
|
18 |
+
Access additional [YOLOv5](https://ultralytics.com/yolov5) π resources:
|
19 |
+
- **Wiki** β https://github.com/ultralytics/yolov5/wiki
|
20 |
+
- **Tutorials** β https://github.com/ultralytics/yolov5#tutorials
|
21 |
+
- **Docs** β https://docs.ultralytics.com
|
22 |
+
|
23 |
+
Access additional [Ultralytics](https://ultralytics.com) β‘ resources:
|
24 |
+
- **Ultralytics HUB** β https://ultralytics.com/hub
|
25 |
+
- **Vision API** β https://ultralytics.com/yolov5
|
26 |
+
- **About Us** β https://ultralytics.com/about
|
27 |
+
- **Join Our Team** β https://ultralytics.com/work
|
28 |
+
- **Contact Us** β https://ultralytics.com/contact
|
29 |
+
|
30 |
+
Feel free to inform us of any other **issues** you discover or **feature requests** that come to mind in the future. Pull Requests (PRs) are also always welcomed!
|
31 |
+
|
32 |
+
Thank you for your contributions to YOLOv5 π and Vision AI β!
|
33 |
+
|
34 |
+
stale-pr-message: 'This pull request has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions YOLOv5 π and Vision AI β.'
|
35 |
+
days-before-stale: 30
|
36 |
+
days-before-close: 5
|
37 |
+
exempt-issue-labels: 'documentation,tutorial,TODO'
|
38 |
+
operations-per-run: 300 # The maximum number of operations per run, used to control rate limiting.
|
yolov5/.gitignore
ADDED
@@ -0,0 +1,256 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
# Repo-specific GitIgnore ----------------------------------------------------------------------------------------------
|
2 |
+
*.jpg
|
3 |
+
*.jpeg
|
4 |
+
*.png
|
5 |
+
*.bmp
|
6 |
+
*.tif
|
7 |
+
*.tiff
|
8 |
+
*.heic
|
9 |
+
*.JPG
|
10 |
+
*.JPEG
|
11 |
+
*.PNG
|
12 |
+
*.BMP
|
13 |
+
*.TIF
|
14 |
+
*.TIFF
|
15 |
+
*.HEIC
|
16 |
+
*.mp4
|
17 |
+
*.mov
|
18 |
+
*.MOV
|
19 |
+
*.avi
|
20 |
+
*.data
|
21 |
+
*.json
|
22 |
+
*.cfg
|
23 |
+
!setup.cfg
|
24 |
+
!cfg/yolov3*.cfg
|
25 |
+
|
26 |
+
storage.googleapis.com
|
27 |
+
runs/*
|
28 |
+
data/*
|
29 |
+
data/images/*
|
30 |
+
!data/*.yaml
|
31 |
+
!data/hyps
|
32 |
+
!data/scripts
|
33 |
+
!data/images
|
34 |
+
!data/images/zidane.jpg
|
35 |
+
!data/images/bus.jpg
|
36 |
+
!data/*.sh
|
37 |
+
|
38 |
+
results*.csv
|
39 |
+
|
40 |
+
# Datasets -------------------------------------------------------------------------------------------------------------
|
41 |
+
coco/
|
42 |
+
coco128/
|
43 |
+
VOC/
|
44 |
+
|
45 |
+
# MATLAB GitIgnore -----------------------------------------------------------------------------------------------------
|
46 |
+
*.m~
|
47 |
+
*.mat
|
48 |
+
!targets*.mat
|
49 |
+
|
50 |
+
# Neural Network weights -----------------------------------------------------------------------------------------------
|
51 |
+
*.weights
|
52 |
+
*.pt
|
53 |
+
*.pb
|
54 |
+
*.onnx
|
55 |
+
*.engine
|
56 |
+
*.mlmodel
|
57 |
+
*.torchscript
|
58 |
+
*.tflite
|
59 |
+
*.h5
|
60 |
+
*_saved_model/
|
61 |
+
*_web_model/
|
62 |
+
*_openvino_model/
|
63 |
+
darknet53.conv.74
|
64 |
+
yolov3-tiny.conv.15
|
65 |
+
|
66 |
+
# GitHub Python GitIgnore ----------------------------------------------------------------------------------------------
|
67 |
+
# Byte-compiled / optimized / DLL files
|
68 |
+
__pycache__/
|
69 |
+
*.py[cod]
|
70 |
+
*$py.class
|
71 |
+
|
72 |
+
# C extensions
|
73 |
+
*.so
|
74 |
+
|
75 |
+
# Distribution / packaging
|
76 |
+
.Python
|
77 |
+
env/
|
78 |
+
build/
|
79 |
+
develop-eggs/
|
80 |
+
dist/
|
81 |
+
downloads/
|
82 |
+
eggs/
|
83 |
+
.eggs/
|
84 |
+
lib/
|
85 |
+
lib64/
|
86 |
+
parts/
|
87 |
+
sdist/
|
88 |
+
var/
|
89 |
+
wheels/
|
90 |
+
*.egg-info/
|
91 |
+
/wandb/
|
92 |
+
.installed.cfg
|
93 |
+
*.egg
|
94 |
+
|
95 |
+
|
96 |
+
# PyInstaller
|
97 |
+
# Usually these files are written by a python script from a template
|
98 |
+
# before PyInstaller builds the exe, so as to inject date/other infos into it.
|
99 |
+
*.manifest
|
100 |
+
*.spec
|
101 |
+
|
102 |
+
# Installer logs
|
103 |
+
pip-log.txt
|
104 |
+
pip-delete-this-directory.txt
|
105 |
+
|
106 |
+
# Unit test / coverage reports
|
107 |
+
htmlcov/
|
108 |
+
.tox/
|
109 |
+
.coverage
|
110 |
+
.coverage.*
|
111 |
+
.cache
|
112 |
+
nosetests.xml
|
113 |
+
coverage.xml
|
114 |
+
*.cover
|
115 |
+
.hypothesis/
|
116 |
+
|
117 |
+
# Translations
|
118 |
+
*.mo
|
119 |
+
*.pot
|
120 |
+
|
121 |
+
# Django stuff:
|
122 |
+
*.log
|
123 |
+
local_settings.py
|
124 |
+
|
125 |
+
# Flask stuff:
|
126 |
+
instance/
|
127 |
+
.webassets-cache
|
128 |
+
|
129 |
+
# Scrapy stuff:
|
130 |
+
.scrapy
|
131 |
+
|
132 |
+
# Sphinx documentation
|
133 |
+
docs/_build/
|
134 |
+
|
135 |
+
# PyBuilder
|
136 |
+
target/
|
137 |
+
|
138 |
+
# Jupyter Notebook
|
139 |
+
.ipynb_checkpoints
|
140 |
+
|
141 |
+
# pyenv
|
142 |
+
.python-version
|
143 |
+
|
144 |
+
# celery beat schedule file
|
145 |
+
celerybeat-schedule
|
146 |
+
|
147 |
+
# SageMath parsed files
|
148 |
+
*.sage.py
|
149 |
+
|
150 |
+
# dotenv
|
151 |
+
.env
|
152 |
+
|
153 |
+
# virtualenv
|
154 |
+
.venv*
|
155 |
+
venv*/
|
156 |
+
ENV*/
|
157 |
+
|
158 |
+
# Spyder project settings
|
159 |
+
.spyderproject
|
160 |
+
.spyproject
|
161 |
+
|
162 |
+
# Rope project settings
|
163 |
+
.ropeproject
|
164 |
+
|
165 |
+
# mkdocs documentation
|
166 |
+
/site
|
167 |
+
|
168 |
+
# mypy
|
169 |
+
.mypy_cache/
|
170 |
+
|
171 |
+
|
172 |
+
# https://github.com/github/gitignore/blob/master/Global/macOS.gitignore -----------------------------------------------
|
173 |
+
|
174 |
+
# General
|
175 |
+
.DS_Store
|
176 |
+
.AppleDouble
|
177 |
+
.LSOverride
|
178 |
+
|
179 |
+
# Icon must end with two \r
|
180 |
+
Icon
|
181 |
+
Icon?
|
182 |
+
|
183 |
+
# Thumbnails
|
184 |
+
._*
|
185 |
+
|
186 |
+
# Files that might appear in the root of a volume
|
187 |
+
.DocumentRevisions-V100
|
188 |
+
.fseventsd
|
189 |
+
.Spotlight-V100
|
190 |
+
.TemporaryItems
|
191 |
+
.Trashes
|
192 |
+
.VolumeIcon.icns
|
193 |
+
.com.apple.timemachine.donotpresent
|
194 |
+
|
195 |
+
# Directories potentially created on remote AFP share
|
196 |
+
.AppleDB
|
197 |
+
.AppleDesktop
|
198 |
+
Network Trash Folder
|
199 |
+
Temporary Items
|
200 |
+
.apdisk
|
201 |
+
|
202 |
+
|
203 |
+
# https://github.com/github/gitignore/blob/master/Global/JetBrains.gitignore
|
204 |
+
# Covers JetBrains IDEs: IntelliJ, RubyMine, PhpStorm, AppCode, PyCharm, CLion, Android Studio and WebStorm
|
205 |
+
# Reference: https://intellij-support.jetbrains.com/hc/en-us/articles/206544839
|
206 |
+
|
207 |
+
# User-specific stuff:
|
208 |
+
.idea/*
|
209 |
+
.idea/**/workspace.xml
|
210 |
+
.idea/**/tasks.xml
|
211 |
+
.idea/dictionaries
|
212 |
+
.html # Bokeh Plots
|
213 |
+
.pg # TensorFlow Frozen Graphs
|
214 |
+
.avi # videos
|
215 |
+
|
216 |
+
# Sensitive or high-churn files:
|
217 |
+
.idea/**/dataSources/
|
218 |
+
.idea/**/dataSources.ids
|
219 |
+
.idea/**/dataSources.local.xml
|
220 |
+
.idea/**/sqlDataSources.xml
|
221 |
+
.idea/**/dynamic.xml
|
222 |
+
.idea/**/uiDesigner.xml
|
223 |
+
|
224 |
+
# Gradle:
|
225 |
+
.idea/**/gradle.xml
|
226 |
+
.idea/**/libraries
|
227 |
+
|
228 |
+
# CMake
|
229 |
+
cmake-build-debug/
|
230 |
+
cmake-build-release/
|
231 |
+
|
232 |
+
# Mongo Explorer plugin:
|
233 |
+
.idea/**/mongoSettings.xml
|
234 |
+
|
235 |
+
## File-based project format:
|
236 |
+
*.iws
|
237 |
+
|
238 |
+
## Plugin-specific files:
|
239 |
+
|
240 |
+
# IntelliJ
|
241 |
+
out/
|
242 |
+
|
243 |
+
# mpeltonen/sbt-idea plugin
|
244 |
+
.idea_modules/
|
245 |
+
|
246 |
+
# JIRA plugin
|
247 |
+
atlassian-ide-plugin.xml
|
248 |
+
|
249 |
+
# Cursive Clojure plugin
|
250 |
+
.idea/replstate.xml
|
251 |
+
|
252 |
+
# Crashlytics plugin (for Android Studio and IntelliJ)
|
253 |
+
com_crashlytics_export_strings.xml
|
254 |
+
crashlytics.properties
|
255 |
+
crashlytics-build.properties
|
256 |
+
fabric.properties
|
yolov5/.pre-commit-config.yaml
ADDED
@@ -0,0 +1,67 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
# Define hooks for code formations
|
2 |
+
# Will be applied on any updated commit files if a user has installed and linked commit hook
|
3 |
+
|
4 |
+
default_language_version:
|
5 |
+
python: python3.8
|
6 |
+
|
7 |
+
# Define bot property if installed via https://github.com/marketplace/pre-commit-ci
|
8 |
+
ci:
|
9 |
+
autofix_prs: true
|
10 |
+
autoupdate_commit_msg: '[pre-commit.ci] pre-commit suggestions'
|
11 |
+
autoupdate_schedule: monthly
|
12 |
+
# submodules: true
|
13 |
+
|
14 |
+
repos:
|
15 |
+
- repo: https://github.com/pre-commit/pre-commit-hooks
|
16 |
+
rev: v4.2.0
|
17 |
+
hooks:
|
18 |
+
- id: end-of-file-fixer
|
19 |
+
- id: trailing-whitespace
|
20 |
+
- id: check-case-conflict
|
21 |
+
- id: check-yaml
|
22 |
+
- id: check-toml
|
23 |
+
- id: pretty-format-json
|
24 |
+
- id: check-docstring-first
|
25 |
+
|
26 |
+
- repo: https://github.com/asottile/pyupgrade
|
27 |
+
rev: v2.32.1
|
28 |
+
hooks:
|
29 |
+
- id: pyupgrade
|
30 |
+
name: Upgrade code
|
31 |
+
args: [ --py37-plus ]
|
32 |
+
|
33 |
+
- repo: https://github.com/PyCQA/isort
|
34 |
+
rev: 5.10.1
|
35 |
+
hooks:
|
36 |
+
- id: isort
|
37 |
+
name: Sort imports
|
38 |
+
|
39 |
+
- repo: https://github.com/pre-commit/mirrors-yapf
|
40 |
+
rev: v0.32.0
|
41 |
+
hooks:
|
42 |
+
- id: yapf
|
43 |
+
name: YAPF formatting
|
44 |
+
|
45 |
+
- repo: https://github.com/executablebooks/mdformat
|
46 |
+
rev: 0.7.14
|
47 |
+
hooks:
|
48 |
+
- id: mdformat
|
49 |
+
name: MD formatting
|
50 |
+
additional_dependencies:
|
51 |
+
- mdformat-gfm
|
52 |
+
- mdformat-black
|
53 |
+
exclude: |
|
54 |
+
(?x)^(
|
55 |
+
README.md
|
56 |
+
)$
|
57 |
+
|
58 |
+
- repo: https://github.com/asottile/yesqa
|
59 |
+
rev: v1.3.0
|
60 |
+
hooks:
|
61 |
+
- id: yesqa
|
62 |
+
|
63 |
+
- repo: https://github.com/PyCQA/flake8
|
64 |
+
rev: 4.0.1
|
65 |
+
hooks:
|
66 |
+
- id: flake8
|
67 |
+
name: PEP8
|
yolov5/7.1.2
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
Requirement already satisfied: Pillow in c:\users\aircar\appdata\local\programs\python\python37-32\lib\site-packages (8.1.2)
|
yolov5/CONTRIBUTING.md
ADDED
@@ -0,0 +1,98 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
## Contributing to YOLOv5 π
|
2 |
+
|
3 |
+
We love your input! We want to make contributing to YOLOv5 as easy and transparent as possible, whether it's:
|
4 |
+
|
5 |
+
- Reporting a bug
|
6 |
+
- Discussing the current state of the code
|
7 |
+
- Submitting a fix
|
8 |
+
- Proposing a new feature
|
9 |
+
- Becoming a maintainer
|
10 |
+
|
11 |
+
YOLOv5 works so well due to our combined community effort, and for every small improvement you contribute you will be
|
12 |
+
helping push the frontiers of what's possible in AI π!
|
13 |
+
|
14 |
+
## Submitting a Pull Request (PR) π οΈ
|
15 |
+
|
16 |
+
Submitting a PR is easy! This example shows how to submit a PR for updating `requirements.txt` in 4 steps:
|
17 |
+
|
18 |
+
### 1. Select File to Update
|
19 |
+
|
20 |
+
Select `requirements.txt` to update by clicking on it in GitHub.
|
21 |
+
|
22 |
+
<p align="center"><img width="800" alt="PR_step1" src="https://user-images.githubusercontent.com/26833433/122260847-08be2600-ced4-11eb-828b-8287ace4136c.png"></p>
|
23 |
+
|
24 |
+
### 2. Click 'Edit this file'
|
25 |
+
|
26 |
+
Button is in top-right corner.
|
27 |
+
|
28 |
+
<p align="center"><img width="800" alt="PR_step2" src="https://user-images.githubusercontent.com/26833433/122260844-06f46280-ced4-11eb-9eec-b8a24be519ca.png"></p>
|
29 |
+
|
30 |
+
### 3. Make Changes
|
31 |
+
|
32 |
+
Change `matplotlib` version from `3.2.2` to `3.3`.
|
33 |
+
|
34 |
+
<p align="center"><img width="800" alt="PR_step3" src="https://user-images.githubusercontent.com/26833433/122260853-0a87e980-ced4-11eb-9fd2-3650fb6e0842.png"></p>
|
35 |
+
|
36 |
+
### 4. Preview Changes and Submit PR
|
37 |
+
|
38 |
+
Click on the **Preview changes** tab to verify your updates. At the bottom of the screen select 'Create a **new branch**
|
39 |
+
for this commit', assign your branch a descriptive name such as `fix/matplotlib_version` and click the green **Propose
|
40 |
+
changes** button. All done, your PR is now submitted to YOLOv5 for review and approval π!
|
41 |
+
|
42 |
+
<p align="center"><img width="800" alt="PR_step4" src="https://user-images.githubusercontent.com/26833433/122260856-0b208000-ced4-11eb-8e8e-77b6151cbcc3.png"></p>
|
43 |
+
|
44 |
+
### PR recommendations
|
45 |
+
|
46 |
+
To allow your work to be integrated as seamlessly as possible, we advise you to:
|
47 |
+
|
48 |
+
- β
Verify your PR is **up-to-date with upstream/master.** If your PR is behind upstream/master an
|
49 |
+
automatic [GitHub Actions](https://github.com/ultralytics/yolov5/blob/master/.github/workflows/rebase.yml) merge may
|
50 |
+
be attempted by writing /rebase in a new comment, or by running the following code, replacing 'feature' with the name
|
51 |
+
of your local branch:
|
52 |
+
|
53 |
+
```bash
|
54 |
+
git remote add upstream https://github.com/ultralytics/yolov5.git
|
55 |
+
git fetch upstream
|
56 |
+
# git checkout feature # <--- replace 'feature' with local branch name
|
57 |
+
git merge upstream/master
|
58 |
+
git push -u origin -f
|
59 |
+
```
|
60 |
+
|
61 |
+
- β
Verify all Continuous Integration (CI) **checks are passing**.
|
62 |
+
- β
Reduce changes to the absolute **minimum** required for your bug fix or feature addition. _"It is not daily increase
|
63 |
+
but daily decrease, hack away the unessential. The closer to the source, the less wastage there is."_ β Bruce Lee
|
64 |
+
|
65 |
+
## Submitting a Bug Report π
|
66 |
+
|
67 |
+
If you spot a problem with YOLOv5 please submit a Bug Report!
|
68 |
+
|
69 |
+
For us to start investigating a possible problem we need to be able to reproduce it ourselves first. We've created a few
|
70 |
+
short guidelines below to help users provide what we need in order to get started.
|
71 |
+
|
72 |
+
When asking a question, people will be better able to provide help if you provide **code** that they can easily
|
73 |
+
understand and use to **reproduce** the problem. This is referred to by community members as creating
|
74 |
+
a [minimum reproducible example](https://stackoverflow.com/help/minimal-reproducible-example). Your code that reproduces
|
75 |
+
the problem should be:
|
76 |
+
|
77 |
+
- β
**Minimal** β Use as little code as possible that still produces the same problem
|
78 |
+
- β
**Complete** β Provide **all** parts someone else needs to reproduce your problem in the question itself
|
79 |
+
- β
**Reproducible** β Test the code you're about to provide to make sure it reproduces the problem
|
80 |
+
|
81 |
+
In addition to the above requirements, for [Ultralytics](https://ultralytics.com/) to provide assistance your code
|
82 |
+
should be:
|
83 |
+
|
84 |
+
- β
**Current** β Verify that your code is up-to-date with current
|
85 |
+
GitHub [master](https://github.com/ultralytics/yolov5/tree/master), and if necessary `git pull` or `git clone` a new
|
86 |
+
copy to ensure your problem has not already been resolved by previous commits.
|
87 |
+
- β
**Unmodified** β Your problem must be reproducible without any modifications to the codebase in this
|
88 |
+
repository. [Ultralytics](https://ultralytics.com/) does not provide support for custom code β οΈ.
|
89 |
+
|
90 |
+
If you believe your problem meets all of the above criteria, please close this issue and raise a new one using the π
|
91 |
+
**Bug Report** [template](https://github.com/ultralytics/yolov5/issues/new/choose) and providing
|
92 |
+
a [minimum reproducible example](https://stackoverflow.com/help/minimal-reproducible-example) to help us better
|
93 |
+
understand and diagnose your problem.
|
94 |
+
|
95 |
+
## License
|
96 |
+
|
97 |
+
By contributing, you agree that your contributions will be licensed under
|
98 |
+
the [GPL-3.0 license](https://choosealicense.com/licenses/gpl-3.0/)
|
yolov5/LICENSE
ADDED
@@ -0,0 +1,674 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
GNU GENERAL PUBLIC LICENSE
|
2 |
+
Version 3, 29 June 2007
|
3 |
+
|
4 |
+
Copyright (C) 2007 Free Software Foundation, Inc. <http://fsf.org/>
|
5 |
+
Everyone is permitted to copy and distribute verbatim copies
|
6 |
+
of this license document, but changing it is not allowed.
|
7 |
+
|
8 |
+
Preamble
|
9 |
+
|
10 |
+
The GNU General Public License is a free, copyleft license for
|
11 |
+
software and other kinds of works.
|
12 |
+
|
13 |
+
The licenses for most software and other practical works are designed
|
14 |
+
to take away your freedom to share and change the works. By contrast,
|
15 |
+
the GNU General Public License is intended to guarantee your freedom to
|
16 |
+
share and change all versions of a program--to make sure it remains free
|
17 |
+
software for all its users. We, the Free Software Foundation, use the
|
18 |
+
GNU General Public License for most of our software; it applies also to
|
19 |
+
any other work released this way by its authors. You can apply it to
|
20 |
+
your programs, too.
|
21 |
+
|
22 |
+
When we speak of free software, we are referring to freedom, not
|
23 |
+
price. Our General Public Licenses are designed to make sure that you
|
24 |
+
have the freedom to distribute copies of free software (and charge for
|
25 |
+
them if you wish), that you receive source code or can get it if you
|
26 |
+
want it, that you can change the software or use pieces of it in new
|
27 |
+
free programs, and that you know you can do these things.
|
28 |
+
|
29 |
+
To protect your rights, we need to prevent others from denying you
|
30 |
+
these rights or asking you to surrender the rights. Therefore, you have
|
31 |
+
certain responsibilities if you distribute copies of the software, or if
|
32 |
+
you modify it: responsibilities to respect the freedom of others.
|
33 |
+
|
34 |
+
For example, if you distribute copies of such a program, whether
|
35 |
+
gratis or for a fee, you must pass on to the recipients the same
|
36 |
+
freedoms that you received. You must make sure that they, too, receive
|
37 |
+
or can get the source code. And you must show them these terms so they
|
38 |
+
know their rights.
|
39 |
+
|
40 |
+
Developers that use the GNU GPL protect your rights with two steps:
|
41 |
+
(1) assert copyright on the software, and (2) offer you this License
|
42 |
+
giving you legal permission to copy, distribute and/or modify it.
|
43 |
+
|
44 |
+
For the developers' and authors' protection, the GPL clearly explains
|
45 |
+
that there is no warranty for this free software. For both users' and
|
46 |
+
authors' sake, the GPL requires that modified versions be marked as
|
47 |
+
changed, so that their problems will not be attributed erroneously to
|
48 |
+
authors of previous versions.
|
49 |
+
|
50 |
+
Some devices are designed to deny users access to install or run
|
51 |
+
modified versions of the software inside them, although the manufacturer
|
52 |
+
can do so. This is fundamentally incompatible with the aim of
|
53 |
+
protecting users' freedom to change the software. The systematic
|
54 |
+
pattern of such abuse occurs in the area of products for individuals to
|
55 |
+
use, which is precisely where it is most unacceptable. Therefore, we
|
56 |
+
have designed this version of the GPL to prohibit the practice for those
|
57 |
+
products. If such problems arise substantially in other domains, we
|
58 |
+
stand ready to extend this provision to those domains in future versions
|
59 |
+
of the GPL, as needed to protect the freedom of users.
|
60 |
+
|
61 |
+
Finally, every program is threatened constantly by software patents.
|
62 |
+
States should not allow patents to restrict development and use of
|
63 |
+
software on general-purpose computers, but in those that do, we wish to
|
64 |
+
avoid the special danger that patents applied to a free program could
|
65 |
+
make it effectively proprietary. To prevent this, the GPL assures that
|
66 |
+
patents cannot be used to render the program non-free.
|
67 |
+
|
68 |
+
The precise terms and conditions for copying, distribution and
|
69 |
+
modification follow.
|
70 |
+
|
71 |
+
TERMS AND CONDITIONS
|
72 |
+
|
73 |
+
0. Definitions.
|
74 |
+
|
75 |
+
"This License" refers to version 3 of the GNU General Public License.
|
76 |
+
|
77 |
+
"Copyright" also means copyright-like laws that apply to other kinds of
|
78 |
+
works, such as semiconductor masks.
|
79 |
+
|
80 |
+
"The Program" refers to any copyrightable work licensed under this
|
81 |
+
License. Each licensee is addressed as "you". "Licensees" and
|
82 |
+
"recipients" may be individuals or organizations.
|
83 |
+
|
84 |
+
To "modify" a work means to copy from or adapt all or part of the work
|
85 |
+
in a fashion requiring copyright permission, other than the making of an
|
86 |
+
exact copy. The resulting work is called a "modified version" of the
|
87 |
+
earlier work or a work "based on" the earlier work.
|
88 |
+
|
89 |
+
A "covered work" means either the unmodified Program or a work based
|
90 |
+
on the Program.
|
91 |
+
|
92 |
+
To "propagate" a work means to do anything with it that, without
|
93 |
+
permission, would make you directly or secondarily liable for
|
94 |
+
infringement under applicable copyright law, except executing it on a
|
95 |
+
computer or modifying a private copy. Propagation includes copying,
|
96 |
+
distribution (with or without modification), making available to the
|
97 |
+
public, and in some countries other activities as well.
|
98 |
+
|
99 |
+
To "convey" a work means any kind of propagation that enables other
|
100 |
+
parties to make or receive copies. Mere interaction with a user through
|
101 |
+
a computer network, with no transfer of a copy, is not conveying.
|
102 |
+
|
103 |
+
An interactive user interface displays "Appropriate Legal Notices"
|
104 |
+
to the extent that it includes a convenient and prominently visible
|
105 |
+
feature that (1) displays an appropriate copyright notice, and (2)
|
106 |
+
tells the user that there is no warranty for the work (except to the
|
107 |
+
extent that warranties are provided), that licensees may convey the
|
108 |
+
work under this License, and how to view a copy of this License. If
|
109 |
+
the interface presents a list of user commands or options, such as a
|
110 |
+
menu, a prominent item in the list meets this criterion.
|
111 |
+
|
112 |
+
1. Source Code.
|
113 |
+
|
114 |
+
The "source code" for a work means the preferred form of the work
|
115 |
+
for making modifications to it. "Object code" means any non-source
|
116 |
+
form of a work.
|
117 |
+
|
118 |
+
A "Standard Interface" means an interface that either is an official
|
119 |
+
standard defined by a recognized standards body, or, in the case of
|
120 |
+
interfaces specified for a particular programming language, one that
|
121 |
+
is widely used among developers working in that language.
|
122 |
+
|
123 |
+
The "System Libraries" of an executable work include anything, other
|
124 |
+
than the work as a whole, that (a) is included in the normal form of
|
125 |
+
packaging a Major Component, but which is not part of that Major
|
126 |
+
Component, and (b) serves only to enable use of the work with that
|
127 |
+
Major Component, or to implement a Standard Interface for which an
|
128 |
+
implementation is available to the public in source code form. A
|
129 |
+
"Major Component", in this context, means a major essential component
|
130 |
+
(kernel, window system, and so on) of the specific operating system
|
131 |
+
(if any) on which the executable work runs, or a compiler used to
|
132 |
+
produce the work, or an object code interpreter used to run it.
|
133 |
+
|
134 |
+
The "Corresponding Source" for a work in object code form means all
|
135 |
+
the source code needed to generate, install, and (for an executable
|
136 |
+
work) run the object code and to modify the work, including scripts to
|
137 |
+
control those activities. However, it does not include the work's
|
138 |
+
System Libraries, or general-purpose tools or generally available free
|
139 |
+
programs which are used unmodified in performing those activities but
|
140 |
+
which are not part of the work. For example, Corresponding Source
|
141 |
+
includes interface definition files associated with source files for
|
142 |
+
the work, and the source code for shared libraries and dynamically
|
143 |
+
linked subprograms that the work is specifically designed to require,
|
144 |
+
such as by intimate data communication or control flow between those
|
145 |
+
subprograms and other parts of the work.
|
146 |
+
|
147 |
+
The Corresponding Source need not include anything that users
|
148 |
+
can regenerate automatically from other parts of the Corresponding
|
149 |
+
Source.
|
150 |
+
|
151 |
+
The Corresponding Source for a work in source code form is that
|
152 |
+
same work.
|
153 |
+
|
154 |
+
2. Basic Permissions.
|
155 |
+
|
156 |
+
All rights granted under this License are granted for the term of
|
157 |
+
copyright on the Program, and are irrevocable provided the stated
|
158 |
+
conditions are met. This License explicitly affirms your unlimited
|
159 |
+
permission to run the unmodified Program. The output from running a
|
160 |
+
covered work is covered by this License only if the output, given its
|
161 |
+
content, constitutes a covered work. This License acknowledges your
|
162 |
+
rights of fair use or other equivalent, as provided by copyright law.
|
163 |
+
|
164 |
+
You may make, run and propagate covered works that you do not
|
165 |
+
convey, without conditions so long as your license otherwise remains
|
166 |
+
in force. You may convey covered works to others for the sole purpose
|
167 |
+
of having them make modifications exclusively for you, or provide you
|
168 |
+
with facilities for running those works, provided that you comply with
|
169 |
+
the terms of this License in conveying all material for which you do
|
170 |
+
not control copyright. Those thus making or running the covered works
|
171 |
+
for you must do so exclusively on your behalf, under your direction
|
172 |
+
and control, on terms that prohibit them from making any copies of
|
173 |
+
your copyrighted material outside their relationship with you.
|
174 |
+
|
175 |
+
Conveying under any other circumstances is permitted solely under
|
176 |
+
the conditions stated below. Sublicensing is not allowed; section 10
|
177 |
+
makes it unnecessary.
|
178 |
+
|
179 |
+
3. Protecting Users' Legal Rights From Anti-Circumvention Law.
|
180 |
+
|
181 |
+
No covered work shall be deemed part of an effective technological
|
182 |
+
measure under any applicable law fulfilling obligations under article
|
183 |
+
11 of the WIPO copyright treaty adopted on 20 December 1996, or
|
184 |
+
similar laws prohibiting or restricting circumvention of such
|
185 |
+
measures.
|
186 |
+
|
187 |
+
When you convey a covered work, you waive any legal power to forbid
|
188 |
+
circumvention of technological measures to the extent such circumvention
|
189 |
+
is effected by exercising rights under this License with respect to
|
190 |
+
the covered work, and you disclaim any intention to limit operation or
|
191 |
+
modification of the work as a means of enforcing, against the work's
|
192 |
+
users, your or third parties' legal rights to forbid circumvention of
|
193 |
+
technological measures.
|
194 |
+
|
195 |
+
4. Conveying Verbatim Copies.
|
196 |
+
|
197 |
+
You may convey verbatim copies of the Program's source code as you
|
198 |
+
receive it, in any medium, provided that you conspicuously and
|
199 |
+
appropriately publish on each copy an appropriate copyright notice;
|
200 |
+
keep intact all notices stating that this License and any
|
201 |
+
non-permissive terms added in accord with section 7 apply to the code;
|
202 |
+
keep intact all notices of the absence of any warranty; and give all
|
203 |
+
recipients a copy of this License along with the Program.
|
204 |
+
|
205 |
+
You may charge any price or no price for each copy that you convey,
|
206 |
+
and you may offer support or warranty protection for a fee.
|
207 |
+
|
208 |
+
5. Conveying Modified Source Versions.
|
209 |
+
|
210 |
+
You may convey a work based on the Program, or the modifications to
|
211 |
+
produce it from the Program, in the form of source code under the
|
212 |
+
terms of section 4, provided that you also meet all of these conditions:
|
213 |
+
|
214 |
+
a) The work must carry prominent notices stating that you modified
|
215 |
+
it, and giving a relevant date.
|
216 |
+
|
217 |
+
b) The work must carry prominent notices stating that it is
|
218 |
+
released under this License and any conditions added under section
|
219 |
+
7. This requirement modifies the requirement in section 4 to
|
220 |
+
"keep intact all notices".
|
221 |
+
|
222 |
+
c) You must license the entire work, as a whole, under this
|
223 |
+
License to anyone who comes into possession of a copy. This
|
224 |
+
License will therefore apply, along with any applicable section 7
|
225 |
+
additional terms, to the whole of the work, and all its parts,
|
226 |
+
regardless of how they are packaged. This License gives no
|
227 |
+
permission to license the work in any other way, but it does not
|
228 |
+
invalidate such permission if you have separately received it.
|
229 |
+
|
230 |
+
d) If the work has interactive user interfaces, each must display
|
231 |
+
Appropriate Legal Notices; however, if the Program has interactive
|
232 |
+
interfaces that do not display Appropriate Legal Notices, your
|
233 |
+
work need not make them do so.
|
234 |
+
|
235 |
+
A compilation of a covered work with other separate and independent
|
236 |
+
works, which are not by their nature extensions of the covered work,
|
237 |
+
and which are not combined with it such as to form a larger program,
|
238 |
+
in or on a volume of a storage or distribution medium, is called an
|
239 |
+
"aggregate" if the compilation and its resulting copyright are not
|
240 |
+
used to limit the access or legal rights of the compilation's users
|
241 |
+
beyond what the individual works permit. Inclusion of a covered work
|
242 |
+
in an aggregate does not cause this License to apply to the other
|
243 |
+
parts of the aggregate.
|
244 |
+
|
245 |
+
6. Conveying Non-Source Forms.
|
246 |
+
|
247 |
+
You may convey a covered work in object code form under the terms
|
248 |
+
of sections 4 and 5, provided that you also convey the
|
249 |
+
machine-readable Corresponding Source under the terms of this License,
|
250 |
+
in one of these ways:
|
251 |
+
|
252 |
+
a) Convey the object code in, or embodied in, a physical product
|
253 |
+
(including a physical distribution medium), accompanied by the
|
254 |
+
Corresponding Source fixed on a durable physical medium
|
255 |
+
customarily used for software interchange.
|
256 |
+
|
257 |
+
b) Convey the object code in, or embodied in, a physical product
|
258 |
+
(including a physical distribution medium), accompanied by a
|
259 |
+
written offer, valid for at least three years and valid for as
|
260 |
+
long as you offer spare parts or customer support for that product
|
261 |
+
model, to give anyone who possesses the object code either (1) a
|
262 |
+
copy of the Corresponding Source for all the software in the
|
263 |
+
product that is covered by this License, on a durable physical
|
264 |
+
medium customarily used for software interchange, for a price no
|
265 |
+
more than your reasonable cost of physically performing this
|
266 |
+
conveying of source, or (2) access to copy the
|
267 |
+
Corresponding Source from a network server at no charge.
|
268 |
+
|
269 |
+
c) Convey individual copies of the object code with a copy of the
|
270 |
+
written offer to provide the Corresponding Source. This
|
271 |
+
alternative is allowed only occasionally and noncommercially, and
|
272 |
+
only if you received the object code with such an offer, in accord
|
273 |
+
with subsection 6b.
|
274 |
+
|
275 |
+
d) Convey the object code by offering access from a designated
|
276 |
+
place (gratis or for a charge), and offer equivalent access to the
|
277 |
+
Corresponding Source in the same way through the same place at no
|
278 |
+
further charge. You need not require recipients to copy the
|
279 |
+
Corresponding Source along with the object code. If the place to
|
280 |
+
copy the object code is a network server, the Corresponding Source
|
281 |
+
may be on a different server (operated by you or a third party)
|
282 |
+
that supports equivalent copying facilities, provided you maintain
|
283 |
+
clear directions next to the object code saying where to find the
|
284 |
+
Corresponding Source. Regardless of what server hosts the
|
285 |
+
Corresponding Source, you remain obligated to ensure that it is
|
286 |
+
available for as long as needed to satisfy these requirements.
|
287 |
+
|
288 |
+
e) Convey the object code using peer-to-peer transmission, provided
|
289 |
+
you inform other peers where the object code and Corresponding
|
290 |
+
Source of the work are being offered to the general public at no
|
291 |
+
charge under subsection 6d.
|
292 |
+
|
293 |
+
A separable portion of the object code, whose source code is excluded
|
294 |
+
from the Corresponding Source as a System Library, need not be
|
295 |
+
included in conveying the object code work.
|
296 |
+
|
297 |
+
A "User Product" is either (1) a "consumer product", which means any
|
298 |
+
tangible personal property which is normally used for personal, family,
|
299 |
+
or household purposes, or (2) anything designed or sold for incorporation
|
300 |
+
into a dwelling. In determining whether a product is a consumer product,
|
301 |
+
doubtful cases shall be resolved in favor of coverage. For a particular
|
302 |
+
product received by a particular user, "normally used" refers to a
|
303 |
+
typical or common use of that class of product, regardless of the status
|
304 |
+
of the particular user or of the way in which the particular user
|
305 |
+
actually uses, or expects or is expected to use, the product. A product
|
306 |
+
is a consumer product regardless of whether the product has substantial
|
307 |
+
commercial, industrial or non-consumer uses, unless such uses represent
|
308 |
+
the only significant mode of use of the product.
|
309 |
+
|
310 |
+
"Installation Information" for a User Product means any methods,
|
311 |
+
procedures, authorization keys, or other information required to install
|
312 |
+
and execute modified versions of a covered work in that User Product from
|
313 |
+
a modified version of its Corresponding Source. The information must
|
314 |
+
suffice to ensure that the continued functioning of the modified object
|
315 |
+
code is in no case prevented or interfered with solely because
|
316 |
+
modification has been made.
|
317 |
+
|
318 |
+
If you convey an object code work under this section in, or with, or
|
319 |
+
specifically for use in, a User Product, and the conveying occurs as
|
320 |
+
part of a transaction in which the right of possession and use of the
|
321 |
+
User Product is transferred to the recipient in perpetuity or for a
|
322 |
+
fixed term (regardless of how the transaction is characterized), the
|
323 |
+
Corresponding Source conveyed under this section must be accompanied
|
324 |
+
by the Installation Information. But this requirement does not apply
|
325 |
+
if neither you nor any third party retains the ability to install
|
326 |
+
modified object code on the User Product (for example, the work has
|
327 |
+
been installed in ROM).
|
328 |
+
|
329 |
+
The requirement to provide Installation Information does not include a
|
330 |
+
requirement to continue to provide support service, warranty, or updates
|
331 |
+
for a work that has been modified or installed by the recipient, or for
|
332 |
+
the User Product in which it has been modified or installed. Access to a
|
333 |
+
network may be denied when the modification itself materially and
|
334 |
+
adversely affects the operation of the network or violates the rules and
|
335 |
+
protocols for communication across the network.
|
336 |
+
|
337 |
+
Corresponding Source conveyed, and Installation Information provided,
|
338 |
+
in accord with this section must be in a format that is publicly
|
339 |
+
documented (and with an implementation available to the public in
|
340 |
+
source code form), and must require no special password or key for
|
341 |
+
unpacking, reading or copying.
|
342 |
+
|
343 |
+
7. Additional Terms.
|
344 |
+
|
345 |
+
"Additional permissions" are terms that supplement the terms of this
|
346 |
+
License by making exceptions from one or more of its conditions.
|
347 |
+
Additional permissions that are applicable to the entire Program shall
|
348 |
+
be treated as though they were included in this License, to the extent
|
349 |
+
that they are valid under applicable law. If additional permissions
|
350 |
+
apply only to part of the Program, that part may be used separately
|
351 |
+
under those permissions, but the entire Program remains governed by
|
352 |
+
this License without regard to the additional permissions.
|
353 |
+
|
354 |
+
When you convey a copy of a covered work, you may at your option
|
355 |
+
remove any additional permissions from that copy, or from any part of
|
356 |
+
it. (Additional permissions may be written to require their own
|
357 |
+
removal in certain cases when you modify the work.) You may place
|
358 |
+
additional permissions on material, added by you to a covered work,
|
359 |
+
for which you have or can give appropriate copyright permission.
|
360 |
+
|
361 |
+
Notwithstanding any other provision of this License, for material you
|
362 |
+
add to a covered work, you may (if authorized by the copyright holders of
|
363 |
+
that material) supplement the terms of this License with terms:
|
364 |
+
|
365 |
+
a) Disclaiming warranty or limiting liability differently from the
|
366 |
+
terms of sections 15 and 16 of this License; or
|
367 |
+
|
368 |
+
b) Requiring preservation of specified reasonable legal notices or
|
369 |
+
author attributions in that material or in the Appropriate Legal
|
370 |
+
Notices displayed by works containing it; or
|
371 |
+
|
372 |
+
c) Prohibiting misrepresentation of the origin of that material, or
|
373 |
+
requiring that modified versions of such material be marked in
|
374 |
+
reasonable ways as different from the original version; or
|
375 |
+
|
376 |
+
d) Limiting the use for publicity purposes of names of licensors or
|
377 |
+
authors of the material; or
|
378 |
+
|
379 |
+
e) Declining to grant rights under trademark law for use of some
|
380 |
+
trade names, trademarks, or service marks; or
|
381 |
+
|
382 |
+
f) Requiring indemnification of licensors and authors of that
|
383 |
+
material by anyone who conveys the material (or modified versions of
|
384 |
+
it) with contractual assumptions of liability to the recipient, for
|
385 |
+
any liability that these contractual assumptions directly impose on
|
386 |
+
those licensors and authors.
|
387 |
+
|
388 |
+
All other non-permissive additional terms are considered "further
|
389 |
+
restrictions" within the meaning of section 10. If the Program as you
|
390 |
+
received it, or any part of it, contains a notice stating that it is
|
391 |
+
governed by this License along with a term that is a further
|
392 |
+
restriction, you may remove that term. If a license document contains
|
393 |
+
a further restriction but permits relicensing or conveying under this
|
394 |
+
License, you may add to a covered work material governed by the terms
|
395 |
+
of that license document, provided that the further restriction does
|
396 |
+
not survive such relicensing or conveying.
|
397 |
+
|
398 |
+
If you add terms to a covered work in accord with this section, you
|
399 |
+
must place, in the relevant source files, a statement of the
|
400 |
+
additional terms that apply to those files, or a notice indicating
|
401 |
+
where to find the applicable terms.
|
402 |
+
|
403 |
+
Additional terms, permissive or non-permissive, may be stated in the
|
404 |
+
form of a separately written license, or stated as exceptions;
|
405 |
+
the above requirements apply either way.
|
406 |
+
|
407 |
+
8. Termination.
|
408 |
+
|
409 |
+
You may not propagate or modify a covered work except as expressly
|
410 |
+
provided under this License. Any attempt otherwise to propagate or
|
411 |
+
modify it is void, and will automatically terminate your rights under
|
412 |
+
this License (including any patent licenses granted under the third
|
413 |
+
paragraph of section 11).
|
414 |
+
|
415 |
+
However, if you cease all violation of this License, then your
|
416 |
+
license from a particular copyright holder is reinstated (a)
|
417 |
+
provisionally, unless and until the copyright holder explicitly and
|
418 |
+
finally terminates your license, and (b) permanently, if the copyright
|
419 |
+
holder fails to notify you of the violation by some reasonable means
|
420 |
+
prior to 60 days after the cessation.
|
421 |
+
|
422 |
+
Moreover, your license from a particular copyright holder is
|
423 |
+
reinstated permanently if the copyright holder notifies you of the
|
424 |
+
violation by some reasonable means, this is the first time you have
|
425 |
+
received notice of violation of this License (for any work) from that
|
426 |
+
copyright holder, and you cure the violation prior to 30 days after
|
427 |
+
your receipt of the notice.
|
428 |
+
|
429 |
+
Termination of your rights under this section does not terminate the
|
430 |
+
licenses of parties who have received copies or rights from you under
|
431 |
+
this License. If your rights have been terminated and not permanently
|
432 |
+
reinstated, you do not qualify to receive new licenses for the same
|
433 |
+
material under section 10.
|
434 |
+
|
435 |
+
9. Acceptance Not Required for Having Copies.
|
436 |
+
|
437 |
+
You are not required to accept this License in order to receive or
|
438 |
+
run a copy of the Program. Ancillary propagation of a covered work
|
439 |
+
occurring solely as a consequence of using peer-to-peer transmission
|
440 |
+
to receive a copy likewise does not require acceptance. However,
|
441 |
+
nothing other than this License grants you permission to propagate or
|
442 |
+
modify any covered work. These actions infringe copyright if you do
|
443 |
+
not accept this License. Therefore, by modifying or propagating a
|
444 |
+
covered work, you indicate your acceptance of this License to do so.
|
445 |
+
|
446 |
+
10. Automatic Licensing of Downstream Recipients.
|
447 |
+
|
448 |
+
Each time you convey a covered work, the recipient automatically
|
449 |
+
receives a license from the original licensors, to run, modify and
|
450 |
+
propagate that work, subject to this License. You are not responsible
|
451 |
+
for enforcing compliance by third parties with this License.
|
452 |
+
|
453 |
+
An "entity transaction" is a transaction transferring control of an
|
454 |
+
organization, or substantially all assets of one, or subdividing an
|
455 |
+
organization, or merging organizations. If propagation of a covered
|
456 |
+
work results from an entity transaction, each party to that
|
457 |
+
transaction who receives a copy of the work also receives whatever
|
458 |
+
licenses to the work the party's predecessor in interest had or could
|
459 |
+
give under the previous paragraph, plus a right to possession of the
|
460 |
+
Corresponding Source of the work from the predecessor in interest, if
|
461 |
+
the predecessor has it or can get it with reasonable efforts.
|
462 |
+
|
463 |
+
You may not impose any further restrictions on the exercise of the
|
464 |
+
rights granted or affirmed under this License. For example, you may
|
465 |
+
not impose a license fee, royalty, or other charge for exercise of
|
466 |
+
rights granted under this License, and you may not initiate litigation
|
467 |
+
(including a cross-claim or counterclaim in a lawsuit) alleging that
|
468 |
+
any patent claim is infringed by making, using, selling, offering for
|
469 |
+
sale, or importing the Program or any portion of it.
|
470 |
+
|
471 |
+
11. Patents.
|
472 |
+
|
473 |
+
A "contributor" is a copyright holder who authorizes use under this
|
474 |
+
License of the Program or a work on which the Program is based. The
|
475 |
+
work thus licensed is called the contributor's "contributor version".
|
476 |
+
|
477 |
+
A contributor's "essential patent claims" are all patent claims
|
478 |
+
owned or controlled by the contributor, whether already acquired or
|
479 |
+
hereafter acquired, that would be infringed by some manner, permitted
|
480 |
+
by this License, of making, using, or selling its contributor version,
|
481 |
+
but do not include claims that would be infringed only as a
|
482 |
+
consequence of further modification of the contributor version. For
|
483 |
+
purposes of this definition, "control" includes the right to grant
|
484 |
+
patent sublicenses in a manner consistent with the requirements of
|
485 |
+
this License.
|
486 |
+
|
487 |
+
Each contributor grants you a non-exclusive, worldwide, royalty-free
|
488 |
+
patent license under the contributor's essential patent claims, to
|
489 |
+
make, use, sell, offer for sale, import and otherwise run, modify and
|
490 |
+
propagate the contents of its contributor version.
|
491 |
+
|
492 |
+
In the following three paragraphs, a "patent license" is any express
|
493 |
+
agreement or commitment, however denominated, not to enforce a patent
|
494 |
+
(such as an express permission to practice a patent or covenant not to
|
495 |
+
sue for patent infringement). To "grant" such a patent license to a
|
496 |
+
party means to make such an agreement or commitment not to enforce a
|
497 |
+
patent against the party.
|
498 |
+
|
499 |
+
If you convey a covered work, knowingly relying on a patent license,
|
500 |
+
and the Corresponding Source of the work is not available for anyone
|
501 |
+
to copy, free of charge and under the terms of this License, through a
|
502 |
+
publicly available network server or other readily accessible means,
|
503 |
+
then you must either (1) cause the Corresponding Source to be so
|
504 |
+
available, or (2) arrange to deprive yourself of the benefit of the
|
505 |
+
patent license for this particular work, or (3) arrange, in a manner
|
506 |
+
consistent with the requirements of this License, to extend the patent
|
507 |
+
license to downstream recipients. "Knowingly relying" means you have
|
508 |
+
actual knowledge that, but for the patent license, your conveying the
|
509 |
+
covered work in a country, or your recipient's use of the covered work
|
510 |
+
in a country, would infringe one or more identifiable patents in that
|
511 |
+
country that you have reason to believe are valid.
|
512 |
+
|
513 |
+
If, pursuant to or in connection with a single transaction or
|
514 |
+
arrangement, you convey, or propagate by procuring conveyance of, a
|
515 |
+
covered work, and grant a patent license to some of the parties
|
516 |
+
receiving the covered work authorizing them to use, propagate, modify
|
517 |
+
or convey a specific copy of the covered work, then the patent license
|
518 |
+
you grant is automatically extended to all recipients of the covered
|
519 |
+
work and works based on it.
|
520 |
+
|
521 |
+
A patent license is "discriminatory" if it does not include within
|
522 |
+
the scope of its coverage, prohibits the exercise of, or is
|
523 |
+
conditioned on the non-exercise of one or more of the rights that are
|
524 |
+
specifically granted under this License. You may not convey a covered
|
525 |
+
work if you are a party to an arrangement with a third party that is
|
526 |
+
in the business of distributing software, under which you make payment
|
527 |
+
to the third party based on the extent of your activity of conveying
|
528 |
+
the work, and under which the third party grants, to any of the
|
529 |
+
parties who would receive the covered work from you, a discriminatory
|
530 |
+
patent license (a) in connection with copies of the covered work
|
531 |
+
conveyed by you (or copies made from those copies), or (b) primarily
|
532 |
+
for and in connection with specific products or compilations that
|
533 |
+
contain the covered work, unless you entered into that arrangement,
|
534 |
+
or that patent license was granted, prior to 28 March 2007.
|
535 |
+
|
536 |
+
Nothing in this License shall be construed as excluding or limiting
|
537 |
+
any implied license or other defenses to infringement that may
|
538 |
+
otherwise be available to you under applicable patent law.
|
539 |
+
|
540 |
+
12. No Surrender of Others' Freedom.
|
541 |
+
|
542 |
+
If conditions are imposed on you (whether by court order, agreement or
|
543 |
+
otherwise) that contradict the conditions of this License, they do not
|
544 |
+
excuse you from the conditions of this License. If you cannot convey a
|
545 |
+
covered work so as to satisfy simultaneously your obligations under this
|
546 |
+
License and any other pertinent obligations, then as a consequence you may
|
547 |
+
not convey it at all. For example, if you agree to terms that obligate you
|
548 |
+
to collect a royalty for further conveying from those to whom you convey
|
549 |
+
the Program, the only way you could satisfy both those terms and this
|
550 |
+
License would be to refrain entirely from conveying the Program.
|
551 |
+
|
552 |
+
13. Use with the GNU Affero General Public License.
|
553 |
+
|
554 |
+
Notwithstanding any other provision of this License, you have
|
555 |
+
permission to link or combine any covered work with a work licensed
|
556 |
+
under version 3 of the GNU Affero General Public License into a single
|
557 |
+
combined work, and to convey the resulting work. The terms of this
|
558 |
+
License will continue to apply to the part which is the covered work,
|
559 |
+
but the special requirements of the GNU Affero General Public License,
|
560 |
+
section 13, concerning interaction through a network will apply to the
|
561 |
+
combination as such.
|
562 |
+
|
563 |
+
14. Revised Versions of this License.
|
564 |
+
|
565 |
+
The Free Software Foundation may publish revised and/or new versions of
|
566 |
+
the GNU General Public License from time to time. Such new versions will
|
567 |
+
be similar in spirit to the present version, but may differ in detail to
|
568 |
+
address new problems or concerns.
|
569 |
+
|
570 |
+
Each version is given a distinguishing version number. If the
|
571 |
+
Program specifies that a certain numbered version of the GNU General
|
572 |
+
Public License "or any later version" applies to it, you have the
|
573 |
+
option of following the terms and conditions either of that numbered
|
574 |
+
version or of any later version published by the Free Software
|
575 |
+
Foundation. If the Program does not specify a version number of the
|
576 |
+
GNU General Public License, you may choose any version ever published
|
577 |
+
by the Free Software Foundation.
|
578 |
+
|
579 |
+
If the Program specifies that a proxy can decide which future
|
580 |
+
versions of the GNU General Public License can be used, that proxy's
|
581 |
+
public statement of acceptance of a version permanently authorizes you
|
582 |
+
to choose that version for the Program.
|
583 |
+
|
584 |
+
Later license versions may give you additional or different
|
585 |
+
permissions. However, no additional obligations are imposed on any
|
586 |
+
author or copyright holder as a result of your choosing to follow a
|
587 |
+
later version.
|
588 |
+
|
589 |
+
15. Disclaimer of Warranty.
|
590 |
+
|
591 |
+
THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
|
592 |
+
APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
|
593 |
+
HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY
|
594 |
+
OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO,
|
595 |
+
THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
|
596 |
+
PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM
|
597 |
+
IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF
|
598 |
+
ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
|
599 |
+
|
600 |
+
16. Limitation of Liability.
|
601 |
+
|
602 |
+
IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
|
603 |
+
WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS
|
604 |
+
THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY
|
605 |
+
GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE
|
606 |
+
USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF
|
607 |
+
DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD
|
608 |
+
PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),
|
609 |
+
EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF
|
610 |
+
SUCH DAMAGES.
|
611 |
+
|
612 |
+
17. Interpretation of Sections 15 and 16.
|
613 |
+
|
614 |
+
If the disclaimer of warranty and limitation of liability provided
|
615 |
+
above cannot be given local legal effect according to their terms,
|
616 |
+
reviewing courts shall apply local law that most closely approximates
|
617 |
+
an absolute waiver of all civil liability in connection with the
|
618 |
+
Program, unless a warranty or assumption of liability accompanies a
|
619 |
+
copy of the Program in return for a fee.
|
620 |
+
|
621 |
+
END OF TERMS AND CONDITIONS
|
622 |
+
|
623 |
+
How to Apply These Terms to Your New Programs
|
624 |
+
|
625 |
+
If you develop a new program, and you want it to be of the greatest
|
626 |
+
possible use to the public, the best way to achieve this is to make it
|
627 |
+
free software which everyone can redistribute and change under these terms.
|
628 |
+
|
629 |
+
To do so, attach the following notices to the program. It is safest
|
630 |
+
to attach them to the start of each source file to most effectively
|
631 |
+
state the exclusion of warranty; and each file should have at least
|
632 |
+
the "copyright" line and a pointer to where the full notice is found.
|
633 |
+
|
634 |
+
<one line to give the program's name and a brief idea of what it does.>
|
635 |
+
Copyright (C) <year> <name of author>
|
636 |
+
|
637 |
+
This program is free software: you can redistribute it and/or modify
|
638 |
+
it under the terms of the GNU General Public License as published by
|
639 |
+
the Free Software Foundation, either version 3 of the License, or
|
640 |
+
(at your option) any later version.
|
641 |
+
|
642 |
+
This program is distributed in the hope that it will be useful,
|
643 |
+
but WITHOUT ANY WARRANTY; without even the implied warranty of
|
644 |
+
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
645 |
+
GNU General Public License for more details.
|
646 |
+
|
647 |
+
You should have received a copy of the GNU General Public License
|
648 |
+
along with this program. If not, see <http://www.gnu.org/licenses/>.
|
649 |
+
|
650 |
+
Also add information on how to contact you by electronic and paper mail.
|
651 |
+
|
652 |
+
If the program does terminal interaction, make it output a short
|
653 |
+
notice like this when it starts in an interactive mode:
|
654 |
+
|
655 |
+
<program> Copyright (C) <year> <name of author>
|
656 |
+
This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
|
657 |
+
This is free software, and you are welcome to redistribute it
|
658 |
+
under certain conditions; type `show c' for details.
|
659 |
+
|
660 |
+
The hypothetical commands `show w' and `show c' should show the appropriate
|
661 |
+
parts of the General Public License. Of course, your program's commands
|
662 |
+
might be different; for a GUI interface, you would use an "about box".
|
663 |
+
|
664 |
+
You should also get your employer (if you work as a programmer) or school,
|
665 |
+
if any, to sign a "copyright disclaimer" for the program, if necessary.
|
666 |
+
For more information on this, and how to apply and follow the GNU GPL, see
|
667 |
+
<http://www.gnu.org/licenses/>.
|
668 |
+
|
669 |
+
The GNU General Public License does not permit incorporating your program
|
670 |
+
into proprietary programs. If your program is a subroutine library, you
|
671 |
+
may consider it more useful to permit linking proprietary applications with
|
672 |
+
the library. If this is what you want to do, use the GNU Lesser General
|
673 |
+
Public License instead of this License. But first, please read
|
674 |
+
<http://www.gnu.org/philosophy/why-not-lgpl.html>.
|
yolov5/README.md
ADDED
@@ -0,0 +1,300 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
<div align="center">
|
2 |
+
<p>
|
3 |
+
<a align="left" href="https://ultralytics.com/yolov5" target="_blank">
|
4 |
+
<img width="850" src="https://github.com/ultralytics/yolov5/releases/download/v1.0/splash.jpg"></a>
|
5 |
+
</p>
|
6 |
+
<br>
|
7 |
+
<div>
|
8 |
+
<a href="https://github.com/ultralytics/yolov5/actions/workflows/ci-testing.yml"><img src="https://github.com/ultralytics/yolov5/actions/workflows/ci-testing.yml/badge.svg" alt="CI CPU testing"></a>
|
9 |
+
<a href="https://zenodo.org/badge/latestdoi/264818686"><img src="https://zenodo.org/badge/264818686.svg" alt="YOLOv5 Citation"></a>
|
10 |
+
<a href="https://hub.docker.com/r/ultralytics/yolov5"><img src="https://img.shields.io/docker/pulls/ultralytics/yolov5?logo=docker" alt="Docker Pulls"></a>
|
11 |
+
<br>
|
12 |
+
<a href="https://colab.research.google.com/github/ultralytics/yolov5/blob/master/tutorial.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a>
|
13 |
+
<a href="https://www.kaggle.com/ultralytics/yolov5"><img src="https://kaggle.com/static/images/open-in-kaggle.svg" alt="Open In Kaggle"></a>
|
14 |
+
<a href="https://join.slack.com/t/ultralytics/shared_invite/zt-w29ei8bp-jczz7QYUmDtgo6r6KcMIAg"><img src="https://img.shields.io/badge/Slack-Join_Forum-blue.svg?logo=slack" alt="Join Forum"></a>
|
15 |
+
</div>
|
16 |
+
|
17 |
+
<br>
|
18 |
+
<p>
|
19 |
+
YOLOv5 π is a family of object detection architectures and models pretrained on the COCO dataset, and represents <a href="https://ultralytics.com">Ultralytics</a>
|
20 |
+
open-source research into future vision AI methods, incorporating lessons learned and best practices evolved over thousands of hours of research and development.
|
21 |
+
</p>
|
22 |
+
|
23 |
+
<div align="center">
|
24 |
+
<a href="https://github.com/ultralytics">
|
25 |
+
<img src="https://github.com/ultralytics/yolov5/releases/download/v1.0/logo-social-github.png" width="2%"/>
|
26 |
+
</a>
|
27 |
+
<img width="2%" />
|
28 |
+
<a href="https://www.linkedin.com/company/ultralytics">
|
29 |
+
<img src="https://github.com/ultralytics/yolov5/releases/download/v1.0/logo-social-linkedin.png" width="2%"/>
|
30 |
+
</a>
|
31 |
+
<img width="2%" />
|
32 |
+
<a href="https://twitter.com/ultralytics">
|
33 |
+
<img src="https://github.com/ultralytics/yolov5/releases/download/v1.0/logo-social-twitter.png" width="2%"/>
|
34 |
+
</a>
|
35 |
+
<img width="2%" />
|
36 |
+
<a href="https://www.producthunt.com/@glenn_jocher">
|
37 |
+
<img src="https://github.com/ultralytics/yolov5/releases/download/v1.0/logo-social-producthunt.png" width="2%"/>
|
38 |
+
</a>
|
39 |
+
<img width="2%" />
|
40 |
+
<a href="https://youtube.com/ultralytics">
|
41 |
+
<img src="https://github.com/ultralytics/yolov5/releases/download/v1.0/logo-social-youtube.png" width="2%"/>
|
42 |
+
</a>
|
43 |
+
<img width="2%" />
|
44 |
+
<a href="https://www.facebook.com/ultralytics">
|
45 |
+
<img src="https://github.com/ultralytics/yolov5/releases/download/v1.0/logo-social-facebook.png" width="2%"/>
|
46 |
+
</a>
|
47 |
+
<img width="2%" />
|
48 |
+
<a href="https://www.instagram.com/ultralytics/">
|
49 |
+
<img src="https://github.com/ultralytics/yolov5/releases/download/v1.0/logo-social-instagram.png" width="2%"/>
|
50 |
+
</a>
|
51 |
+
</div>
|
52 |
+
|
53 |
+
<!--
|
54 |
+
<a align="center" href="https://ultralytics.com/yolov5" target="_blank">
|
55 |
+
<img width="800" src="https://github.com/ultralytics/yolov5/releases/download/v1.0/banner-api.png"></a>
|
56 |
+
-->
|
57 |
+
|
58 |
+
</div>
|
59 |
+
|
60 |
+
## <div align="center">Documentation</div>
|
61 |
+
|
62 |
+
See the [YOLOv5 Docs](https://docs.ultralytics.com) for full documentation on training, testing and deployment.
|
63 |
+
|
64 |
+
## <div align="center">Quick Start Examples</div>
|
65 |
+
|
66 |
+
<details open>
|
67 |
+
<summary>Install</summary>
|
68 |
+
|
69 |
+
Clone repo and install [requirements.txt](https://github.com/ultralytics/yolov5/blob/master/requirements.txt) in a
|
70 |
+
[**Python>=3.7.0**](https://www.python.org/) environment, including
|
71 |
+
[**PyTorch>=1.7**](https://pytorch.org/get-started/locally/).
|
72 |
+
|
73 |
+
```bash
|
74 |
+
git clone https://github.com/ultralytics/yolov5 # clone
|
75 |
+
cd yolov5
|
76 |
+
pip install -r requirements.txt # install
|
77 |
+
```
|
78 |
+
|
79 |
+
</details>
|
80 |
+
|
81 |
+
<details open>
|
82 |
+
<summary>Inference</summary>
|
83 |
+
|
84 |
+
YOLOv5 [PyTorch Hub](https://github.com/ultralytics/yolov5/issues/36) inference. [Models](https://github.com/ultralytics/yolov5/tree/master/models) download automatically from the latest
|
85 |
+
YOLOv5 [release](https://github.com/ultralytics/yolov5/releases).
|
86 |
+
|
87 |
+
```python
|
88 |
+
import torch
|
89 |
+
|
90 |
+
# Model
|
91 |
+
model = torch.hub.load('ultralytics/yolov5', 'yolov5s') # or yolov5n - yolov5x6, custom
|
92 |
+
|
93 |
+
# Images
|
94 |
+
img = 'https://ultralytics.com/images/zidane.jpg' # or file, Path, PIL, OpenCV, numpy, list
|
95 |
+
|
96 |
+
# Inference
|
97 |
+
results = model(img)
|
98 |
+
|
99 |
+
# Results
|
100 |
+
results.print() # or .show(), .save(), .crop(), .pandas(), etc.
|
101 |
+
```
|
102 |
+
|
103 |
+
</details>
|
104 |
+
|
105 |
+
<details>
|
106 |
+
<summary>Inference with detect.py</summary>
|
107 |
+
|
108 |
+
`detect.py` runs inference on a variety of sources, downloading [models](https://github.com/ultralytics/yolov5/tree/master/models) automatically from
|
109 |
+
the latest YOLOv5 [release](https://github.com/ultralytics/yolov5/releases) and saving results to `runs/detect`.
|
110 |
+
|
111 |
+
```bash
|
112 |
+
python detect.py --source 0 # webcam
|
113 |
+
img.jpg # image
|
114 |
+
vid.mp4 # video
|
115 |
+
path/ # directory
|
116 |
+
path/*.jpg # glob
|
117 |
+
'https://youtu.be/Zgi9g1ksQHc' # YouTube
|
118 |
+
'rtsp://example.com/media.mp4' # RTSP, RTMP, HTTP stream
|
119 |
+
```
|
120 |
+
|
121 |
+
</details>
|
122 |
+
|
123 |
+
<details>
|
124 |
+
<summary>Training</summary>
|
125 |
+
|
126 |
+
The commands below reproduce YOLOv5 [COCO](https://github.com/ultralytics/yolov5/blob/master/data/scripts/get_coco.sh)
|
127 |
+
results. [Models](https://github.com/ultralytics/yolov5/tree/master/models)
|
128 |
+
and [datasets](https://github.com/ultralytics/yolov5/tree/master/data) download automatically from the latest
|
129 |
+
YOLOv5 [release](https://github.com/ultralytics/yolov5/releases). Training times for YOLOv5n/s/m/l/x are
|
130 |
+
1/2/4/6/8 days on a V100 GPU ([Multi-GPU](https://github.com/ultralytics/yolov5/issues/475) times faster). Use the
|
131 |
+
largest `--batch-size` possible, or pass `--batch-size -1` for
|
132 |
+
YOLOv5 [AutoBatch](https://github.com/ultralytics/yolov5/pull/5092). Batch sizes shown for V100-16GB.
|
133 |
+
|
134 |
+
```bash
|
135 |
+
python train.py --data coco.yaml --cfg yolov5n.yaml --weights '' --batch-size 128
|
136 |
+
yolov5s 64
|
137 |
+
yolov5m 40
|
138 |
+
yolov5l 24
|
139 |
+
yolov5x 16
|
140 |
+
```
|
141 |
+
|
142 |
+
<img width="800" src="https://user-images.githubusercontent.com/26833433/90222759-949d8800-ddc1-11ea-9fa1-1c97eed2b963.png">
|
143 |
+
|
144 |
+
</details>
|
145 |
+
|
146 |
+
<details open>
|
147 |
+
<summary>Tutorials</summary>
|
148 |
+
|
149 |
+
- [Train Custom Data](https://github.com/ultralytics/yolov5/wiki/Train-Custom-Data)Β π RECOMMENDED
|
150 |
+
- [Tips for Best Training Results](https://github.com/ultralytics/yolov5/wiki/Tips-for-Best-Training-Results)Β βοΈ
|
151 |
+
RECOMMENDED
|
152 |
+
- [Weights & Biases Logging](https://github.com/ultralytics/yolov5/issues/1289)Β π NEW
|
153 |
+
- [Roboflow for Datasets, Labeling, and Active Learning](https://github.com/ultralytics/yolov5/issues/4975)Β π NEW
|
154 |
+
- [Multi-GPU Training](https://github.com/ultralytics/yolov5/issues/475)
|
155 |
+
- [PyTorch Hub](https://github.com/ultralytics/yolov5/issues/36)Β β NEW
|
156 |
+
- [TFLite, ONNX, CoreML, TensorRT Export](https://github.com/ultralytics/yolov5/issues/251) π
|
157 |
+
- [Test-Time Augmentation (TTA)](https://github.com/ultralytics/yolov5/issues/303)
|
158 |
+
- [Model Ensembling](https://github.com/ultralytics/yolov5/issues/318)
|
159 |
+
- [Model Pruning/Sparsity](https://github.com/ultralytics/yolov5/issues/304)
|
160 |
+
- [Hyperparameter Evolution](https://github.com/ultralytics/yolov5/issues/607)
|
161 |
+
- [Transfer Learning with Frozen Layers](https://github.com/ultralytics/yolov5/issues/1314)Β β NEW
|
162 |
+
- [Architecture Summary](https://github.com/ultralytics/yolov5/issues/6998)Β β NEW
|
163 |
+
|
164 |
+
</details>
|
165 |
+
|
166 |
+
## <div align="center">Environments</div>
|
167 |
+
|
168 |
+
Get started in seconds with our verified environments. Click each icon below for details.
|
169 |
+
|
170 |
+
<div align="center">
|
171 |
+
<a href="https://colab.research.google.com/github/ultralytics/yolov5/blob/master/tutorial.ipynb">
|
172 |
+
<img src="https://github.com/ultralytics/yolov5/releases/download/v1.0/logo-colab-small.png" width="15%"/>
|
173 |
+
</a>
|
174 |
+
<a href="https://www.kaggle.com/ultralytics/yolov5">
|
175 |
+
<img src="https://github.com/ultralytics/yolov5/releases/download/v1.0/logo-kaggle-small.png" width="15%"/>
|
176 |
+
</a>
|
177 |
+
<a href="https://hub.docker.com/r/ultralytics/yolov5">
|
178 |
+
<img src="https://github.com/ultralytics/yolov5/releases/download/v1.0/logo-docker-small.png" width="15%"/>
|
179 |
+
</a>
|
180 |
+
<a href="https://github.com/ultralytics/yolov5/wiki/AWS-Quickstart">
|
181 |
+
<img src="https://github.com/ultralytics/yolov5/releases/download/v1.0/logo-aws-small.png" width="15%"/>
|
182 |
+
</a>
|
183 |
+
<a href="https://github.com/ultralytics/yolov5/wiki/GCP-Quickstart">
|
184 |
+
<img src="https://github.com/ultralytics/yolov5/releases/download/v1.0/logo-gcp-small.png" width="15%"/>
|
185 |
+
</a>
|
186 |
+
</div>
|
187 |
+
|
188 |
+
## <div align="center">Integrations</div>
|
189 |
+
|
190 |
+
<div align="center">
|
191 |
+
<a href="https://wandb.ai/site?utm_campaign=repo_yolo_readme">
|
192 |
+
<img src="https://github.com/ultralytics/yolov5/releases/download/v1.0/logo-wb-long.png" width="49%"/>
|
193 |
+
</a>
|
194 |
+
<a href="https://roboflow.com/?ref=ultralytics">
|
195 |
+
<img src="https://github.com/ultralytics/yolov5/releases/download/v1.0/logo-roboflow-long.png" width="49%"/>
|
196 |
+
</a>
|
197 |
+
</div>
|
198 |
+
|
199 |
+
|Weights and Biases|Roboflow β NEW|
|
200 |
+
|:-:|:-:|
|
201 |
+
|Automatically track and visualize all your YOLOv5 training runs in the cloud with [Weights & Biases](https://wandb.ai/site?utm_campaign=repo_yolo_readme)|Label and export your custom datasets directly to YOLOv5 for training with [Roboflow](https://roboflow.com/?ref=ultralytics) |
|
202 |
+
|
203 |
+
<!-- ## <div align="center">Compete and Win</div>
|
204 |
+
|
205 |
+
We are super excited about our first-ever Ultralytics YOLOv5 π EXPORT Competition with **$10,000** in cash prizes!
|
206 |
+
|
207 |
+
<p align="center">
|
208 |
+
<a href="https://github.com/ultralytics/yolov5/discussions/3213">
|
209 |
+
<img width="850" src="https://github.com/ultralytics/yolov5/releases/download/v1.0/banner-export-competition.png"></a>
|
210 |
+
</p> -->
|
211 |
+
|
212 |
+
## <div align="center">Why YOLOv5</div>
|
213 |
+
|
214 |
+
<p align="left"><img width="800" src="https://user-images.githubusercontent.com/26833433/155040763-93c22a27-347c-4e3c-847a-8094621d3f4e.png"></p>
|
215 |
+
<details>
|
216 |
+
<summary>YOLOv5-P5 640 Figure (click to expand)</summary>
|
217 |
+
|
218 |
+
<p align="left"><img width="800" src="https://user-images.githubusercontent.com/26833433/155040757-ce0934a3-06a6-43dc-a979-2edbbd69ea0e.png"></p>
|
219 |
+
</details>
|
220 |
+
<details>
|
221 |
+
<summary>Figure Notes (click to expand)</summary>
|
222 |
+
|
223 |
+
- **COCO AP val** denotes mAP@0.5:0.95 metric measured on the 5000-image [COCO val2017](http://cocodataset.org) dataset over various inference sizes from 256 to 1536.
|
224 |
+
- **GPU Speed** measures average inference time per image on [COCO val2017](http://cocodataset.org) dataset using a [AWS p3.2xlarge](https://aws.amazon.com/ec2/instance-types/p3/) V100 instance at batch-size 32.
|
225 |
+
- **EfficientDet** data from [google/automl](https://github.com/google/automl) at batch size 8.
|
226 |
+
- **Reproduce** by `python val.py --task study --data coco.yaml --iou 0.7 --weights yolov5n6.pt yolov5s6.pt yolov5m6.pt yolov5l6.pt yolov5x6.pt`
|
227 |
+
|
228 |
+
</details>
|
229 |
+
|
230 |
+
### Pretrained Checkpoints
|
231 |
+
|
232 |
+
|Model |size<br><sup>(pixels) |mAP<sup>val<br>0.5:0.95 |mAP<sup>val<br>0.5 |Speed<br><sup>CPU b1<br>(ms) |Speed<br><sup>V100 b1<br>(ms) |Speed<br><sup>V100 b32<br>(ms) |params<br><sup>(M) |FLOPs<br><sup>@640 (B)
|
233 |
+
|--- |--- |--- |--- |--- |--- |--- |--- |---
|
234 |
+
|[YOLOv5n][assets] |640 |28.0 |45.7 |**45** |**6.3**|**0.6**|**1.9**|**4.5**
|
235 |
+
|[YOLOv5s][assets] |640 |37.4 |56.8 |98 |6.4 |0.9 |7.2 |16.5
|
236 |
+
|[YOLOv5m][assets] |640 |45.4 |64.1 |224 |8.2 |1.7 |21.2 |49.0
|
237 |
+
|[YOLOv5l][assets] |640 |49.0 |67.3 |430 |10.1 |2.7 |46.5 |109.1
|
238 |
+
|[YOLOv5x][assets] |640 |50.7 |68.9 |766 |12.1 |4.8 |86.7 |205.7
|
239 |
+
| | | | | | | | |
|
240 |
+
|[YOLOv5n6][assets] |1280 |36.0 |54.4 |153 |8.1 |2.1 |3.2 |4.6
|
241 |
+
|[YOLOv5s6][assets] |1280 |44.8 |63.7 |385 |8.2 |3.6 |12.6 |16.8
|
242 |
+
|[YOLOv5m6][assets] |1280 |51.3 |69.3 |887 |11.1 |6.8 |35.7 |50.0
|
243 |
+
|[YOLOv5l6][assets] |1280 |53.7 |71.3 |1784 |15.8 |10.5 |76.8 |111.4
|
244 |
+
|[YOLOv5x6][assets]<br>+ [TTA][TTA]|1280<br>1536 |55.0<br>**55.8** |72.7<br>**72.7** |3136<br>- |26.2<br>- |19.4<br>- |140.7<br>- |209.8<br>-
|
245 |
+
|
246 |
+
<details>
|
247 |
+
<summary>Table Notes (click to expand)</summary>
|
248 |
+
|
249 |
+
- All checkpoints are trained to 300 epochs with default settings. Nano and Small models use [hyp.scratch-low.yaml](https://github.com/ultralytics/yolov5/blob/master/data/hyps/hyp.scratch-low.yaml) hyps, all others use [hyp.scratch-high.yaml](https://github.com/ultralytics/yolov5/blob/master/data/hyps/hyp.scratch-high.yaml).
|
250 |
+
- **mAP<sup>val</sup>** values are for single-model single-scale on [COCO val2017](http://cocodataset.org) dataset.<br>Reproduce by `python val.py --data coco.yaml --img 640 --conf 0.001 --iou 0.65`
|
251 |
+
- **Speed** averaged over COCO val images using a [AWS p3.2xlarge](https://aws.amazon.com/ec2/instance-types/p3/) instance. NMS times (~1 ms/img) not included.<br>Reproduce by `python val.py --data coco.yaml --img 640 --task speed --batch 1`
|
252 |
+
- **TTA** [Test Time Augmentation](https://github.com/ultralytics/yolov5/issues/303) includes reflection and scale augmentations.<br>Reproduce by `python val.py --data coco.yaml --img 1536 --iou 0.7 --augment`
|
253 |
+
|
254 |
+
</details>
|
255 |
+
|
256 |
+
## <div align="center">Contribute</div>
|
257 |
+
|
258 |
+
We love your input! We want to make contributing to YOLOv5 as easy and transparent as possible. Please see our [Contributing Guide](CONTRIBUTING.md) to get started, and fill out the [YOLOv5 Survey](https://ultralytics.com/survey?utm_source=github&utm_medium=social&utm_campaign=Survey) to send us feedback on your experiences. Thank you to all our contributors!
|
259 |
+
|
260 |
+
<a href="https://github.com/ultralytics/yolov5/graphs/contributors"><img src="https://opencollective.com/ultralytics/contributors.svg?width=990" /></a>
|
261 |
+
|
262 |
+
## <div align="center">Contact</div>
|
263 |
+
|
264 |
+
For YOLOv5 bugs and feature requests please visit [GitHub Issues](https://github.com/ultralytics/yolov5/issues). For business inquiries or
|
265 |
+
professional support requests please visit [https://ultralytics.com/contact](https://ultralytics.com/contact).
|
266 |
+
|
267 |
+
<br>
|
268 |
+
|
269 |
+
<div align="center">
|
270 |
+
<a href="https://github.com/ultralytics">
|
271 |
+
<img src="https://github.com/ultralytics/yolov5/releases/download/v1.0/logo-social-github.png" width="3%"/>
|
272 |
+
</a>
|
273 |
+
<img width="3%" />
|
274 |
+
<a href="https://www.linkedin.com/company/ultralytics">
|
275 |
+
<img src="https://github.com/ultralytics/yolov5/releases/download/v1.0/logo-social-linkedin.png" width="3%"/>
|
276 |
+
</a>
|
277 |
+
<img width="3%" />
|
278 |
+
<a href="https://twitter.com/ultralytics">
|
279 |
+
<img src="https://github.com/ultralytics/yolov5/releases/download/v1.0/logo-social-twitter.png" width="3%"/>
|
280 |
+
</a>
|
281 |
+
<img width="3%" />
|
282 |
+
<a href="https://www.producthunt.com/@glenn_jocher">
|
283 |
+
<img src="https://github.com/ultralytics/yolov5/releases/download/v1.0/logo-social-producthunt.png" width="3%"/>
|
284 |
+
</a>
|
285 |
+
<img width="3%" />
|
286 |
+
<a href="https://youtube.com/ultralytics">
|
287 |
+
<img src="https://github.com/ultralytics/yolov5/releases/download/v1.0/logo-social-youtube.png" width="3%"/>
|
288 |
+
</a>
|
289 |
+
<img width="3%" />
|
290 |
+
<a href="https://www.facebook.com/ultralytics">
|
291 |
+
<img src="https://github.com/ultralytics/yolov5/releases/download/v1.0/logo-social-facebook.png" width="3%"/>
|
292 |
+
</a>
|
293 |
+
<img width="3%" />
|
294 |
+
<a href="https://www.instagram.com/ultralytics/">
|
295 |
+
<img src="https://github.com/ultralytics/yolov5/releases/download/v1.0/logo-social-instagram.png" width="3%"/>
|
296 |
+
</a>
|
297 |
+
</div>
|
298 |
+
|
299 |
+
[assets]: https://github.com/ultralytics/yolov5/releases
|
300 |
+
[tta]: https://github.com/ultralytics/yolov5/issues/303
|
yolov5/data/Argoverse.yaml
ADDED
@@ -0,0 +1,67 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
# YOLOv5 π by Ultralytics, GPL-3.0 license
|
2 |
+
# Argoverse-HD dataset (ring-front-center camera) http://www.cs.cmu.edu/~mengtial/proj/streaming/ by Argo AI
|
3 |
+
# Example usage: python train.py --data Argoverse.yaml
|
4 |
+
# parent
|
5 |
+
# βββ yolov5
|
6 |
+
# βββ datasets
|
7 |
+
# βββ Argoverse β downloads here (31.3 GB)
|
8 |
+
|
9 |
+
|
10 |
+
# Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..]
|
11 |
+
path: ../datasets/Argoverse # dataset root dir
|
12 |
+
train: Argoverse-1.1/images/train/ # train images (relative to 'path') 39384 images
|
13 |
+
val: Argoverse-1.1/images/val/ # val images (relative to 'path') 15062 images
|
14 |
+
test: Argoverse-1.1/images/test/ # test images (optional) https://eval.ai/web/challenges/challenge-page/800/overview
|
15 |
+
|
16 |
+
# Classes
|
17 |
+
nc: 8 # number of classes
|
18 |
+
names: ['person', 'bicycle', 'car', 'motorcycle', 'bus', 'truck', 'traffic_light', 'stop_sign'] # class names
|
19 |
+
|
20 |
+
|
21 |
+
# Download script/URL (optional) ---------------------------------------------------------------------------------------
|
22 |
+
download: |
|
23 |
+
import json
|
24 |
+
|
25 |
+
from tqdm import tqdm
|
26 |
+
from utils.general import download, Path
|
27 |
+
|
28 |
+
|
29 |
+
def argoverse2yolo(set):
|
30 |
+
labels = {}
|
31 |
+
a = json.load(open(set, "rb"))
|
32 |
+
for annot in tqdm(a['annotations'], desc=f"Converting {set} to YOLOv5 format..."):
|
33 |
+
img_id = annot['image_id']
|
34 |
+
img_name = a['images'][img_id]['name']
|
35 |
+
img_label_name = f'{img_name[:-3]}txt'
|
36 |
+
|
37 |
+
cls = annot['category_id'] # instance class id
|
38 |
+
x_center, y_center, width, height = annot['bbox']
|
39 |
+
x_center = (x_center + width / 2) / 1920.0 # offset and scale
|
40 |
+
y_center = (y_center + height / 2) / 1200.0 # offset and scale
|
41 |
+
width /= 1920.0 # scale
|
42 |
+
height /= 1200.0 # scale
|
43 |
+
|
44 |
+
img_dir = set.parents[2] / 'Argoverse-1.1' / 'labels' / a['seq_dirs'][a['images'][annot['image_id']]['sid']]
|
45 |
+
if not img_dir.exists():
|
46 |
+
img_dir.mkdir(parents=True, exist_ok=True)
|
47 |
+
|
48 |
+
k = str(img_dir / img_label_name)
|
49 |
+
if k not in labels:
|
50 |
+
labels[k] = []
|
51 |
+
labels[k].append(f"{cls} {x_center} {y_center} {width} {height}\n")
|
52 |
+
|
53 |
+
for k in labels:
|
54 |
+
with open(k, "w") as f:
|
55 |
+
f.writelines(labels[k])
|
56 |
+
|
57 |
+
|
58 |
+
# Download
|
59 |
+
dir = Path('../datasets/Argoverse') # dataset root dir
|
60 |
+
urls = ['https://argoverse-hd.s3.us-east-2.amazonaws.com/Argoverse-HD-Full.zip']
|
61 |
+
download(urls, dir=dir, delete=False)
|
62 |
+
|
63 |
+
# Convert
|
64 |
+
annotations_dir = 'Argoverse-HD/annotations/'
|
65 |
+
(dir / 'Argoverse-1.1' / 'tracking').rename(dir / 'Argoverse-1.1' / 'images') # rename 'tracking' to 'images'
|
66 |
+
for d in "train.json", "val.json":
|
67 |
+
argoverse2yolo(dir / annotations_dir / d) # convert VisDrone annotations to YOLO labels
|
yolov5/data/GlobalWheat2020.yaml
ADDED
@@ -0,0 +1,54 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
# YOLOv5 π by Ultralytics, GPL-3.0 license
|
2 |
+
# Global Wheat 2020 dataset http://www.global-wheat.com/ by University of Saskatchewan
|
3 |
+
# Example usage: python train.py --data GlobalWheat2020.yaml
|
4 |
+
# parent
|
5 |
+
# βββ yolov5
|
6 |
+
# βββ datasets
|
7 |
+
# βββ GlobalWheat2020 β downloads here (7.0 GB)
|
8 |
+
|
9 |
+
|
10 |
+
# Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..]
|
11 |
+
path: ../datasets/GlobalWheat2020 # dataset root dir
|
12 |
+
train: # train images (relative to 'path') 3422 images
|
13 |
+
- images/arvalis_1
|
14 |
+
- images/arvalis_2
|
15 |
+
- images/arvalis_3
|
16 |
+
- images/ethz_1
|
17 |
+
- images/rres_1
|
18 |
+
- images/inrae_1
|
19 |
+
- images/usask_1
|
20 |
+
val: # val images (relative to 'path') 748 images (WARNING: train set contains ethz_1)
|
21 |
+
- images/ethz_1
|
22 |
+
test: # test images (optional) 1276 images
|
23 |
+
- images/utokyo_1
|
24 |
+
- images/utokyo_2
|
25 |
+
- images/nau_1
|
26 |
+
- images/uq_1
|
27 |
+
|
28 |
+
# Classes
|
29 |
+
nc: 1 # number of classes
|
30 |
+
names: ['wheat_head'] # class names
|
31 |
+
|
32 |
+
|
33 |
+
# Download script/URL (optional) ---------------------------------------------------------------------------------------
|
34 |
+
download: |
|
35 |
+
from utils.general import download, Path
|
36 |
+
|
37 |
+
|
38 |
+
# Download
|
39 |
+
dir = Path(yaml['path']) # dataset root dir
|
40 |
+
urls = ['https://zenodo.org/record/4298502/files/global-wheat-codalab-official.zip',
|
41 |
+
'https://github.com/ultralytics/yolov5/releases/download/v1.0/GlobalWheat2020_labels.zip']
|
42 |
+
download(urls, dir=dir)
|
43 |
+
|
44 |
+
# Make Directories
|
45 |
+
for p in 'annotations', 'images', 'labels':
|
46 |
+
(dir / p).mkdir(parents=True, exist_ok=True)
|
47 |
+
|
48 |
+
# Move
|
49 |
+
for p in 'arvalis_1', 'arvalis_2', 'arvalis_3', 'ethz_1', 'rres_1', 'inrae_1', 'usask_1', \
|
50 |
+
'utokyo_1', 'utokyo_2', 'nau_1', 'uq_1':
|
51 |
+
(dir / p).rename(dir / 'images' / p) # move to /images
|
52 |
+
f = (dir / p).with_suffix('.json') # json file
|
53 |
+
if f.exists():
|
54 |
+
f.rename((dir / 'annotations' / p).with_suffix('.json')) # move to /annotations
|
yolov5/data/Objects365.yaml
ADDED
@@ -0,0 +1,114 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
# YOLOv5 π by Ultralytics, GPL-3.0 license
|
2 |
+
# Objects365 dataset https://www.objects365.org/ by Megvii
|
3 |
+
# Example usage: python train.py --data Objects365.yaml
|
4 |
+
# parent
|
5 |
+
# βββ yolov5
|
6 |
+
# βββ datasets
|
7 |
+
# βββ Objects365 β downloads here (712 GB = 367G data + 345G zips)
|
8 |
+
|
9 |
+
|
10 |
+
# Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..]
|
11 |
+
path: ../datasets/Objects365 # dataset root dir
|
12 |
+
train: images/train # train images (relative to 'path') 1742289 images
|
13 |
+
val: images/val # val images (relative to 'path') 80000 images
|
14 |
+
test: # test images (optional)
|
15 |
+
|
16 |
+
# Classes
|
17 |
+
nc: 365 # number of classes
|
18 |
+
names: ['Person', 'Sneakers', 'Chair', 'Other Shoes', 'Hat', 'Car', 'Lamp', 'Glasses', 'Bottle', 'Desk', 'Cup',
|
19 |
+
'Street Lights', 'Cabinet/shelf', 'Handbag/Satchel', 'Bracelet', 'Plate', 'Picture/Frame', 'Helmet', 'Book',
|
20 |
+
'Gloves', 'Storage box', 'Boat', 'Leather Shoes', 'Flower', 'Bench', 'Potted Plant', 'Bowl/Basin', 'Flag',
|
21 |
+
'Pillow', 'Boots', 'Vase', 'Microphone', 'Necklace', 'Ring', 'SUV', 'Wine Glass', 'Belt', 'Monitor/TV',
|
22 |
+
'Backpack', 'Umbrella', 'Traffic Light', 'Speaker', 'Watch', 'Tie', 'Trash bin Can', 'Slippers', 'Bicycle',
|
23 |
+
'Stool', 'Barrel/bucket', 'Van', 'Couch', 'Sandals', 'Basket', 'Drum', 'Pen/Pencil', 'Bus', 'Wild Bird',
|
24 |
+
'High Heels', 'Motorcycle', 'Guitar', 'Carpet', 'Cell Phone', 'Bread', 'Camera', 'Canned', 'Truck',
|
25 |
+
'Traffic cone', 'Cymbal', 'Lifesaver', 'Towel', 'Stuffed Toy', 'Candle', 'Sailboat', 'Laptop', 'Awning',
|
26 |
+
'Bed', 'Faucet', 'Tent', 'Horse', 'Mirror', 'Power outlet', 'Sink', 'Apple', 'Air Conditioner', 'Knife',
|
27 |
+
'Hockey Stick', 'Paddle', 'Pickup Truck', 'Fork', 'Traffic Sign', 'Balloon', 'Tripod', 'Dog', 'Spoon', 'Clock',
|
28 |
+
'Pot', 'Cow', 'Cake', 'Dinning Table', 'Sheep', 'Hanger', 'Blackboard/Whiteboard', 'Napkin', 'Other Fish',
|
29 |
+
'Orange/Tangerine', 'Toiletry', 'Keyboard', 'Tomato', 'Lantern', 'Machinery Vehicle', 'Fan',
|
30 |
+
'Green Vegetables', 'Banana', 'Baseball Glove', 'Airplane', 'Mouse', 'Train', 'Pumpkin', 'Soccer', 'Skiboard',
|
31 |
+
'Luggage', 'Nightstand', 'Tea pot', 'Telephone', 'Trolley', 'Head Phone', 'Sports Car', 'Stop Sign',
|
32 |
+
'Dessert', 'Scooter', 'Stroller', 'Crane', 'Remote', 'Refrigerator', 'Oven', 'Lemon', 'Duck', 'Baseball Bat',
|
33 |
+
'Surveillance Camera', 'Cat', 'Jug', 'Broccoli', 'Piano', 'Pizza', 'Elephant', 'Skateboard', 'Surfboard',
|
34 |
+
'Gun', 'Skating and Skiing shoes', 'Gas stove', 'Donut', 'Bow Tie', 'Carrot', 'Toilet', 'Kite', 'Strawberry',
|
35 |
+
'Other Balls', 'Shovel', 'Pepper', 'Computer Box', 'Toilet Paper', 'Cleaning Products', 'Chopsticks',
|
36 |
+
'Microwave', 'Pigeon', 'Baseball', 'Cutting/chopping Board', 'Coffee Table', 'Side Table', 'Scissors',
|
37 |
+
'Marker', 'Pie', 'Ladder', 'Snowboard', 'Cookies', 'Radiator', 'Fire Hydrant', 'Basketball', 'Zebra', 'Grape',
|
38 |
+
'Giraffe', 'Potato', 'Sausage', 'Tricycle', 'Violin', 'Egg', 'Fire Extinguisher', 'Candy', 'Fire Truck',
|
39 |
+
'Billiards', 'Converter', 'Bathtub', 'Wheelchair', 'Golf Club', 'Briefcase', 'Cucumber', 'Cigar/Cigarette',
|
40 |
+
'Paint Brush', 'Pear', 'Heavy Truck', 'Hamburger', 'Extractor', 'Extension Cord', 'Tong', 'Tennis Racket',
|
41 |
+
'Folder', 'American Football', 'earphone', 'Mask', 'Kettle', 'Tennis', 'Ship', 'Swing', 'Coffee Machine',
|
42 |
+
'Slide', 'Carriage', 'Onion', 'Green beans', 'Projector', 'Frisbee', 'Washing Machine/Drying Machine',
|
43 |
+
'Chicken', 'Printer', 'Watermelon', 'Saxophone', 'Tissue', 'Toothbrush', 'Ice cream', 'Hot-air balloon',
|
44 |
+
'Cello', 'French Fries', 'Scale', 'Trophy', 'Cabbage', 'Hot dog', 'Blender', 'Peach', 'Rice', 'Wallet/Purse',
|
45 |
+
'Volleyball', 'Deer', 'Goose', 'Tape', 'Tablet', 'Cosmetics', 'Trumpet', 'Pineapple', 'Golf Ball',
|
46 |
+
'Ambulance', 'Parking meter', 'Mango', 'Key', 'Hurdle', 'Fishing Rod', 'Medal', 'Flute', 'Brush', 'Penguin',
|
47 |
+
'Megaphone', 'Corn', 'Lettuce', 'Garlic', 'Swan', 'Helicopter', 'Green Onion', 'Sandwich', 'Nuts',
|
48 |
+
'Speed Limit Sign', 'Induction Cooker', 'Broom', 'Trombone', 'Plum', 'Rickshaw', 'Goldfish', 'Kiwi fruit',
|
49 |
+
'Router/modem', 'Poker Card', 'Toaster', 'Shrimp', 'Sushi', 'Cheese', 'Notepaper', 'Cherry', 'Pliers', 'CD',
|
50 |
+
'Pasta', 'Hammer', 'Cue', 'Avocado', 'Hamimelon', 'Flask', 'Mushroom', 'Screwdriver', 'Soap', 'Recorder',
|
51 |
+
'Bear', 'Eggplant', 'Board Eraser', 'Coconut', 'Tape Measure/Ruler', 'Pig', 'Showerhead', 'Globe', 'Chips',
|
52 |
+
'Steak', 'Crosswalk Sign', 'Stapler', 'Camel', 'Formula 1', 'Pomegranate', 'Dishwasher', 'Crab',
|
53 |
+
'Hoverboard', 'Meat ball', 'Rice Cooker', 'Tuba', 'Calculator', 'Papaya', 'Antelope', 'Parrot', 'Seal',
|
54 |
+
'Butterfly', 'Dumbbell', 'Donkey', 'Lion', 'Urinal', 'Dolphin', 'Electric Drill', 'Hair Dryer', 'Egg tart',
|
55 |
+
'Jellyfish', 'Treadmill', 'Lighter', 'Grapefruit', 'Game board', 'Mop', 'Radish', 'Baozi', 'Target', 'French',
|
56 |
+
'Spring Rolls', 'Monkey', 'Rabbit', 'Pencil Case', 'Yak', 'Red Cabbage', 'Binoculars', 'Asparagus', 'Barbell',
|
57 |
+
'Scallop', 'Noddles', 'Comb', 'Dumpling', 'Oyster', 'Table Tennis paddle', 'Cosmetics Brush/Eyeliner Pencil',
|
58 |
+
'Chainsaw', 'Eraser', 'Lobster', 'Durian', 'Okra', 'Lipstick', 'Cosmetics Mirror', 'Curling', 'Table Tennis']
|
59 |
+
|
60 |
+
|
61 |
+
# Download script/URL (optional) ---------------------------------------------------------------------------------------
|
62 |
+
download: |
|
63 |
+
from tqdm import tqdm
|
64 |
+
|
65 |
+
from utils.general import Path, check_requirements, download, np, xyxy2xywhn
|
66 |
+
|
67 |
+
check_requirements(('pycocotools>=2.0',))
|
68 |
+
from pycocotools.coco import COCO
|
69 |
+
|
70 |
+
# Make Directories
|
71 |
+
dir = Path(yaml['path']) # dataset root dir
|
72 |
+
for p in 'images', 'labels':
|
73 |
+
(dir / p).mkdir(parents=True, exist_ok=True)
|
74 |
+
for q in 'train', 'val':
|
75 |
+
(dir / p / q).mkdir(parents=True, exist_ok=True)
|
76 |
+
|
77 |
+
# Train, Val Splits
|
78 |
+
for split, patches in [('train', 50 + 1), ('val', 43 + 1)]:
|
79 |
+
print(f"Processing {split} in {patches} patches ...")
|
80 |
+
images, labels = dir / 'images' / split, dir / 'labels' / split
|
81 |
+
|
82 |
+
# Download
|
83 |
+
url = f"https://dorc.ks3-cn-beijing.ksyun.com/data-set/2020Objects365%E6%95%B0%E6%8D%AE%E9%9B%86/{split}/"
|
84 |
+
if split == 'train':
|
85 |
+
download([f'{url}zhiyuan_objv2_{split}.tar.gz'], dir=dir, delete=False) # annotations json
|
86 |
+
download([f'{url}patch{i}.tar.gz' for i in range(patches)], dir=images, curl=True, delete=False, threads=8)
|
87 |
+
elif split == 'val':
|
88 |
+
download([f'{url}zhiyuan_objv2_{split}.json'], dir=dir, delete=False) # annotations json
|
89 |
+
download([f'{url}images/v1/patch{i}.tar.gz' for i in range(15 + 1)], dir=images, curl=True, delete=False, threads=8)
|
90 |
+
download([f'{url}images/v2/patch{i}.tar.gz' for i in range(16, patches)], dir=images, curl=True, delete=False, threads=8)
|
91 |
+
|
92 |
+
# Move
|
93 |
+
for f in tqdm(images.rglob('*.jpg'), desc=f'Moving {split} images'):
|
94 |
+
f.rename(images / f.name) # move to /images/{split}
|
95 |
+
|
96 |
+
# Labels
|
97 |
+
coco = COCO(dir / f'zhiyuan_objv2_{split}.json')
|
98 |
+
names = [x["name"] for x in coco.loadCats(coco.getCatIds())]
|
99 |
+
for cid, cat in enumerate(names):
|
100 |
+
catIds = coco.getCatIds(catNms=[cat])
|
101 |
+
imgIds = coco.getImgIds(catIds=catIds)
|
102 |
+
for im in tqdm(coco.loadImgs(imgIds), desc=f'Class {cid + 1}/{len(names)} {cat}'):
|
103 |
+
width, height = im["width"], im["height"]
|
104 |
+
path = Path(im["file_name"]) # image filename
|
105 |
+
try:
|
106 |
+
with open(labels / path.with_suffix('.txt').name, 'a') as file:
|
107 |
+
annIds = coco.getAnnIds(imgIds=im["id"], catIds=catIds, iscrowd=None)
|
108 |
+
for a in coco.loadAnns(annIds):
|
109 |
+
x, y, w, h = a['bbox'] # bounding box in xywh (xy top-left corner)
|
110 |
+
xyxy = np.array([x, y, x + w, y + h])[None] # pixels(1,4)
|
111 |
+
x, y, w, h = xyxy2xywhn(xyxy, w=width, h=height, clip=True)[0] # normalized and clipped
|
112 |
+
file.write(f"{cid} {x:.5f} {y:.5f} {w:.5f} {h:.5f}\n")
|
113 |
+
except Exception as e:
|
114 |
+
print(e)
|
yolov5/data/SKU-110K.yaml
ADDED
@@ -0,0 +1,53 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
# YOLOv5 π by Ultralytics, GPL-3.0 license
|
2 |
+
# SKU-110K retail items dataset https://github.com/eg4000/SKU110K_CVPR19 by Trax Retail
|
3 |
+
# Example usage: python train.py --data SKU-110K.yaml
|
4 |
+
# parent
|
5 |
+
# βββ yolov5
|
6 |
+
# βββ datasets
|
7 |
+
# βββ SKU-110K β downloads here (13.6 GB)
|
8 |
+
|
9 |
+
|
10 |
+
# Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..]
|
11 |
+
path: ../datasets/SKU-110K # dataset root dir
|
12 |
+
train: train.txt # train images (relative to 'path') 8219 images
|
13 |
+
val: val.txt # val images (relative to 'path') 588 images
|
14 |
+
test: test.txt # test images (optional) 2936 images
|
15 |
+
|
16 |
+
# Classes
|
17 |
+
nc: 1 # number of classes
|
18 |
+
names: ['object'] # class names
|
19 |
+
|
20 |
+
|
21 |
+
# Download script/URL (optional) ---------------------------------------------------------------------------------------
|
22 |
+
download: |
|
23 |
+
import shutil
|
24 |
+
from tqdm import tqdm
|
25 |
+
from utils.general import np, pd, Path, download, xyxy2xywh
|
26 |
+
|
27 |
+
|
28 |
+
# Download
|
29 |
+
dir = Path(yaml['path']) # dataset root dir
|
30 |
+
parent = Path(dir.parent) # download dir
|
31 |
+
urls = ['http://trax-geometry.s3.amazonaws.com/cvpr_challenge/SKU110K_fixed.tar.gz']
|
32 |
+
download(urls, dir=parent, delete=False)
|
33 |
+
|
34 |
+
# Rename directories
|
35 |
+
if dir.exists():
|
36 |
+
shutil.rmtree(dir)
|
37 |
+
(parent / 'SKU110K_fixed').rename(dir) # rename dir
|
38 |
+
(dir / 'labels').mkdir(parents=True, exist_ok=True) # create labels dir
|
39 |
+
|
40 |
+
# Convert labels
|
41 |
+
names = 'image', 'x1', 'y1', 'x2', 'y2', 'class', 'image_width', 'image_height' # column names
|
42 |
+
for d in 'annotations_train.csv', 'annotations_val.csv', 'annotations_test.csv':
|
43 |
+
x = pd.read_csv(dir / 'annotations' / d, names=names).values # annotations
|
44 |
+
images, unique_images = x[:, 0], np.unique(x[:, 0])
|
45 |
+
with open((dir / d).with_suffix('.txt').__str__().replace('annotations_', ''), 'w') as f:
|
46 |
+
f.writelines(f'./images/{s}\n' for s in unique_images)
|
47 |
+
for im in tqdm(unique_images, desc=f'Converting {dir / d}'):
|
48 |
+
cls = 0 # single-class dataset
|
49 |
+
with open((dir / 'labels' / im).with_suffix('.txt'), 'a') as f:
|
50 |
+
for r in x[images == im]:
|
51 |
+
w, h = r[6], r[7] # image width, height
|
52 |
+
xywh = xyxy2xywh(np.array([[r[1] / w, r[2] / h, r[3] / w, r[4] / h]]))[0] # instance
|
53 |
+
f.write(f"{cls} {xywh[0]:.5f} {xywh[1]:.5f} {xywh[2]:.5f} {xywh[3]:.5f}\n") # write label
|
yolov5/data/VOC.yaml
ADDED
@@ -0,0 +1,81 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
# YOLOv5 π by Ultralytics, GPL-3.0 license
|
2 |
+
# PASCAL VOC dataset http://host.robots.ox.ac.uk/pascal/VOC by University of Oxford
|
3 |
+
# Example usage: python train.py --data VOC.yaml
|
4 |
+
# parent
|
5 |
+
# βββ yolov5
|
6 |
+
# βββ datasets
|
7 |
+
# βββ VOC β downloads here (2.8 GB)
|
8 |
+
|
9 |
+
|
10 |
+
# Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..]
|
11 |
+
path: ../datasets/VOC
|
12 |
+
train: # train images (relative to 'path') 16551 images
|
13 |
+
- images/train2012
|
14 |
+
- images/train2007
|
15 |
+
- images/val2012
|
16 |
+
- images/val2007
|
17 |
+
val: # val images (relative to 'path') 4952 images
|
18 |
+
- images/test2007
|
19 |
+
test: # test images (optional)
|
20 |
+
- images/test2007
|
21 |
+
|
22 |
+
# Classes
|
23 |
+
nc: 20 # number of classes
|
24 |
+
names: ['aeroplane', 'bicycle', 'bird', 'boat', 'bottle', 'bus', 'car', 'cat', 'chair', 'cow', 'diningtable', 'dog',
|
25 |
+
'horse', 'motorbike', 'person', 'pottedplant', 'sheep', 'sofa', 'train', 'tvmonitor'] # class names
|
26 |
+
|
27 |
+
|
28 |
+
# Download script/URL (optional) ---------------------------------------------------------------------------------------
|
29 |
+
download: |
|
30 |
+
import xml.etree.ElementTree as ET
|
31 |
+
|
32 |
+
from tqdm import tqdm
|
33 |
+
from utils.general import download, Path
|
34 |
+
|
35 |
+
|
36 |
+
def convert_label(path, lb_path, year, image_id):
|
37 |
+
def convert_box(size, box):
|
38 |
+
dw, dh = 1. / size[0], 1. / size[1]
|
39 |
+
x, y, w, h = (box[0] + box[1]) / 2.0 - 1, (box[2] + box[3]) / 2.0 - 1, box[1] - box[0], box[3] - box[2]
|
40 |
+
return x * dw, y * dh, w * dw, h * dh
|
41 |
+
|
42 |
+
in_file = open(path / f'VOC{year}/Annotations/{image_id}.xml')
|
43 |
+
out_file = open(lb_path, 'w')
|
44 |
+
tree = ET.parse(in_file)
|
45 |
+
root = tree.getroot()
|
46 |
+
size = root.find('size')
|
47 |
+
w = int(size.find('width').text)
|
48 |
+
h = int(size.find('height').text)
|
49 |
+
|
50 |
+
for obj in root.iter('object'):
|
51 |
+
cls = obj.find('name').text
|
52 |
+
if cls in yaml['names'] and not int(obj.find('difficult').text) == 1:
|
53 |
+
xmlbox = obj.find('bndbox')
|
54 |
+
bb = convert_box((w, h), [float(xmlbox.find(x).text) for x in ('xmin', 'xmax', 'ymin', 'ymax')])
|
55 |
+
cls_id = yaml['names'].index(cls) # class id
|
56 |
+
out_file.write(" ".join([str(a) for a in (cls_id, *bb)]) + '\n')
|
57 |
+
|
58 |
+
|
59 |
+
# Download
|
60 |
+
dir = Path(yaml['path']) # dataset root dir
|
61 |
+
url = 'https://github.com/ultralytics/yolov5/releases/download/v1.0/'
|
62 |
+
urls = [f'{url}VOCtrainval_06-Nov-2007.zip', # 446MB, 5012 images
|
63 |
+
f'{url}VOCtest_06-Nov-2007.zip', # 438MB, 4953 images
|
64 |
+
f'{url}VOCtrainval_11-May-2012.zip'] # 1.95GB, 17126 images
|
65 |
+
download(urls, dir=dir / 'images', delete=False, curl=True, threads=3)
|
66 |
+
|
67 |
+
# Convert
|
68 |
+
path = dir / 'images/VOCdevkit'
|
69 |
+
for year, image_set in ('2012', 'train'), ('2012', 'val'), ('2007', 'train'), ('2007', 'val'), ('2007', 'test'):
|
70 |
+
imgs_path = dir / 'images' / f'{image_set}{year}'
|
71 |
+
lbs_path = dir / 'labels' / f'{image_set}{year}'
|
72 |
+
imgs_path.mkdir(exist_ok=True, parents=True)
|
73 |
+
lbs_path.mkdir(exist_ok=True, parents=True)
|
74 |
+
|
75 |
+
with open(path / f'VOC{year}/ImageSets/Main/{image_set}.txt') as f:
|
76 |
+
image_ids = f.read().strip().split()
|
77 |
+
for id in tqdm(image_ids, desc=f'{image_set}{year}'):
|
78 |
+
f = path / f'VOC{year}/JPEGImages/{id}.jpg' # old img path
|
79 |
+
lb_path = (lbs_path / f.name).with_suffix('.txt') # new label path
|
80 |
+
f.rename(imgs_path / f.name) # move image
|
81 |
+
convert_label(path, lb_path, year, id) # convert labels to YOLO format
|
yolov5/data/VisDrone.yaml
ADDED
@@ -0,0 +1,61 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
# YOLOv5 π by Ultralytics, GPL-3.0 license
|
2 |
+
# VisDrone2019-DET dataset https://github.com/VisDrone/VisDrone-Dataset by Tianjin University
|
3 |
+
# Example usage: python train.py --data VisDrone.yaml
|
4 |
+
# parent
|
5 |
+
# βββ yolov5
|
6 |
+
# βββ datasets
|
7 |
+
# βββ VisDrone β downloads here (2.3 GB)
|
8 |
+
|
9 |
+
|
10 |
+
# Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..]
|
11 |
+
path: ../datasets/VisDrone # dataset root dir
|
12 |
+
train: VisDrone2019-DET-train/images # train images (relative to 'path') 6471 images
|
13 |
+
val: VisDrone2019-DET-val/images # val images (relative to 'path') 548 images
|
14 |
+
test: VisDrone2019-DET-test-dev/images # test images (optional) 1610 images
|
15 |
+
|
16 |
+
# Classes
|
17 |
+
nc: 10 # number of classes
|
18 |
+
names: ['pedestrian', 'people', 'bicycle', 'car', 'van', 'truck', 'tricycle', 'awning-tricycle', 'bus', 'motor']
|
19 |
+
|
20 |
+
|
21 |
+
# Download script/URL (optional) ---------------------------------------------------------------------------------------
|
22 |
+
download: |
|
23 |
+
from utils.general import download, os, Path
|
24 |
+
|
25 |
+
def visdrone2yolo(dir):
|
26 |
+
from PIL import Image
|
27 |
+
from tqdm import tqdm
|
28 |
+
|
29 |
+
def convert_box(size, box):
|
30 |
+
# Convert VisDrone box to YOLO xywh box
|
31 |
+
dw = 1. / size[0]
|
32 |
+
dh = 1. / size[1]
|
33 |
+
return (box[0] + box[2] / 2) * dw, (box[1] + box[3] / 2) * dh, box[2] * dw, box[3] * dh
|
34 |
+
|
35 |
+
(dir / 'labels').mkdir(parents=True, exist_ok=True) # make labels directory
|
36 |
+
pbar = tqdm((dir / 'annotations').glob('*.txt'), desc=f'Converting {dir}')
|
37 |
+
for f in pbar:
|
38 |
+
img_size = Image.open((dir / 'images' / f.name).with_suffix('.jpg')).size
|
39 |
+
lines = []
|
40 |
+
with open(f, 'r') as file: # read annotation.txt
|
41 |
+
for row in [x.split(',') for x in file.read().strip().splitlines()]:
|
42 |
+
if row[4] == '0': # VisDrone 'ignored regions' class 0
|
43 |
+
continue
|
44 |
+
cls = int(row[5]) - 1
|
45 |
+
box = convert_box(img_size, tuple(map(int, row[:4])))
|
46 |
+
lines.append(f"{cls} {' '.join(f'{x:.6f}' for x in box)}\n")
|
47 |
+
with open(str(f).replace(os.sep + 'annotations' + os.sep, os.sep + 'labels' + os.sep), 'w') as fl:
|
48 |
+
fl.writelines(lines) # write label.txt
|
49 |
+
|
50 |
+
|
51 |
+
# Download
|
52 |
+
dir = Path(yaml['path']) # dataset root dir
|
53 |
+
urls = ['https://github.com/ultralytics/yolov5/releases/download/v1.0/VisDrone2019-DET-train.zip',
|
54 |
+
'https://github.com/ultralytics/yolov5/releases/download/v1.0/VisDrone2019-DET-val.zip',
|
55 |
+
'https://github.com/ultralytics/yolov5/releases/download/v1.0/VisDrone2019-DET-test-dev.zip',
|
56 |
+
'https://github.com/ultralytics/yolov5/releases/download/v1.0/VisDrone2019-DET-test-challenge.zip']
|
57 |
+
download(urls, dir=dir, curl=True, threads=4)
|
58 |
+
|
59 |
+
# Convert
|
60 |
+
for d in 'VisDrone2019-DET-train', 'VisDrone2019-DET-val', 'VisDrone2019-DET-test-dev':
|
61 |
+
visdrone2yolo(dir / d) # convert VisDrone annotations to YOLO labels
|
yolov5/data/coco.yaml
ADDED
@@ -0,0 +1,45 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
# YOLOv5 π by Ultralytics, GPL-3.0 license
|
2 |
+
# COCO 2017 dataset http://cocodataset.org by Microsoft
|
3 |
+
# Example usage: python train.py --data coco.yaml
|
4 |
+
# parent
|
5 |
+
# βββ yolov5
|
6 |
+
# βββ datasets
|
7 |
+
# βββ coco β downloads here (20.1 GB)
|
8 |
+
|
9 |
+
|
10 |
+
# Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..]
|
11 |
+
path: ../datasets/coco # dataset root dir
|
12 |
+
train: train2017.txt # train images (relative to 'path') 118287 images
|
13 |
+
val: val2017.txt # val images (relative to 'path') 5000 images
|
14 |
+
test: test-dev2017.txt # 20288 of 40670 images, submit to https://competitions.codalab.org/competitions/20794
|
15 |
+
|
16 |
+
# Classes
|
17 |
+
nc: 80 # number of classes
|
18 |
+
names: ['person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'traffic light',
|
19 |
+
'fire hydrant', 'stop sign', 'parking meter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow',
|
20 |
+
'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee',
|
21 |
+
'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard',
|
22 |
+
'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple',
|
23 |
+
'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'donut', 'cake', 'chair', 'couch',
|
24 |
+
'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone',
|
25 |
+
'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear',
|
26 |
+
'hair drier', 'toothbrush'] # class names
|
27 |
+
|
28 |
+
|
29 |
+
# Download script/URL (optional)
|
30 |
+
download: |
|
31 |
+
from utils.general import download, Path
|
32 |
+
|
33 |
+
|
34 |
+
# Download labels
|
35 |
+
segments = False # segment or box labels
|
36 |
+
dir = Path(yaml['path']) # dataset root dir
|
37 |
+
url = 'https://github.com/ultralytics/yolov5/releases/download/v1.0/'
|
38 |
+
urls = [url + ('coco2017labels-segments.zip' if segments else 'coco2017labels.zip')] # labels
|
39 |
+
download(urls, dir=dir.parent)
|
40 |
+
|
41 |
+
# Download data
|
42 |
+
urls = ['http://images.cocodataset.org/zips/train2017.zip', # 19G, 118k images
|
43 |
+
'http://images.cocodataset.org/zips/val2017.zip', # 1G, 5k images
|
44 |
+
'http://images.cocodataset.org/zips/test2017.zip'] # 7G, 41k images (optional)
|
45 |
+
download(urls, dir=dir / 'images', threads=3)
|
yolov5/data/coco128.yaml
ADDED
@@ -0,0 +1,30 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
# YOLOv5 π by Ultralytics, GPL-3.0 license
|
2 |
+
# COCO128 dataset https://www.kaggle.com/ultralytics/coco128 (first 128 images from COCO train2017) by Ultralytics
|
3 |
+
# Example usage: python train.py --data coco128.yaml
|
4 |
+
# parent
|
5 |
+
# βββ yolov5
|
6 |
+
# βββ datasets
|
7 |
+
# βββ coco128 β downloads here (7 MB)
|
8 |
+
|
9 |
+
|
10 |
+
# Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..]
|
11 |
+
path: ../datasets/coco128 # dataset root dir
|
12 |
+
train: images/train2017 # train images (relative to 'path') 128 images
|
13 |
+
val: images/train2017 # val images (relative to 'path') 128 images
|
14 |
+
test: # test images (optional)
|
15 |
+
|
16 |
+
# Classes
|
17 |
+
nc: 80 # number of classes
|
18 |
+
names: ['person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train', 'truck', 'boat', 'traffic light',
|
19 |
+
'fire hydrant', 'stop sign', 'parking meter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep', 'cow',
|
20 |
+
'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella', 'handbag', 'tie', 'suitcase', 'frisbee',
|
21 |
+
'skis', 'snowboard', 'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard', 'surfboard',
|
22 |
+
'tennis racket', 'bottle', 'wine glass', 'cup', 'fork', 'knife', 'spoon', 'bowl', 'banana', 'apple',
|
23 |
+
'sandwich', 'orange', 'broccoli', 'carrot', 'hot dog', 'pizza', 'donut', 'cake', 'chair', 'couch',
|
24 |
+
'potted plant', 'bed', 'dining table', 'toilet', 'tv', 'laptop', 'mouse', 'remote', 'keyboard', 'cell phone',
|
25 |
+
'microwave', 'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase', 'scissors', 'teddy bear',
|
26 |
+
'hair drier', 'toothbrush'] # class names
|
27 |
+
|
28 |
+
|
29 |
+
# Download script/URL (optional)
|
30 |
+
download: https://ultralytics.com/assets/coco128.zip
|
yolov5/data/hyps/hyp.Objects365.yaml
ADDED
@@ -0,0 +1,34 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
# YOLOv5 π by Ultralytics, GPL-3.0 license
|
2 |
+
# Hyperparameters for Objects365 training
|
3 |
+
# python train.py --weights yolov5m.pt --data Objects365.yaml --evolve
|
4 |
+
# See Hyperparameter Evolution tutorial for details https://github.com/ultralytics/yolov5#tutorials
|
5 |
+
|
6 |
+
lr0: 0.00258
|
7 |
+
lrf: 0.17
|
8 |
+
momentum: 0.779
|
9 |
+
weight_decay: 0.00058
|
10 |
+
warmup_epochs: 1.33
|
11 |
+
warmup_momentum: 0.86
|
12 |
+
warmup_bias_lr: 0.0711
|
13 |
+
box: 0.0539
|
14 |
+
cls: 0.299
|
15 |
+
cls_pw: 0.825
|
16 |
+
obj: 0.632
|
17 |
+
obj_pw: 1.0
|
18 |
+
iou_t: 0.2
|
19 |
+
anchor_t: 3.44
|
20 |
+
anchors: 3.2
|
21 |
+
fl_gamma: 0.0
|
22 |
+
hsv_h: 0.0188
|
23 |
+
hsv_s: 0.704
|
24 |
+
hsv_v: 0.36
|
25 |
+
degrees: 0.0
|
26 |
+
translate: 0.0902
|
27 |
+
scale: 0.491
|
28 |
+
shear: 0.0
|
29 |
+
perspective: 0.0
|
30 |
+
flipud: 0.0
|
31 |
+
fliplr: 0.5
|
32 |
+
mosaic: 1.0
|
33 |
+
mixup: 0.0
|
34 |
+
copy_paste: 0.0
|
yolov5/data/hyps/hyp.VOC.yaml
ADDED
@@ -0,0 +1,40 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
# YOLOv5 π by Ultralytics, GPL-3.0 license
|
2 |
+
# Hyperparameters for VOC training
|
3 |
+
# python train.py --batch 128 --weights yolov5m6.pt --data VOC.yaml --epochs 50 --img 512 --hyp hyp.scratch-med.yaml --evolve
|
4 |
+
# See Hyperparameter Evolution tutorial for details https://github.com/ultralytics/yolov5#tutorials
|
5 |
+
|
6 |
+
# YOLOv5 Hyperparameter Evolution Results
|
7 |
+
# Best generation: 467
|
8 |
+
# Last generation: 996
|
9 |
+
# metrics/precision, metrics/recall, metrics/mAP_0.5, metrics/mAP_0.5:0.95, val/box_loss, val/obj_loss, val/cls_loss
|
10 |
+
# 0.87729, 0.85125, 0.91286, 0.72664, 0.0076739, 0.0042529, 0.0013865
|
11 |
+
|
12 |
+
lr0: 0.00334
|
13 |
+
lrf: 0.15135
|
14 |
+
momentum: 0.74832
|
15 |
+
weight_decay: 0.00025
|
16 |
+
warmup_epochs: 3.3835
|
17 |
+
warmup_momentum: 0.59462
|
18 |
+
warmup_bias_lr: 0.18657
|
19 |
+
box: 0.02
|
20 |
+
cls: 0.21638
|
21 |
+
cls_pw: 0.5
|
22 |
+
obj: 0.51728
|
23 |
+
obj_pw: 0.67198
|
24 |
+
iou_t: 0.2
|
25 |
+
anchor_t: 3.3744
|
26 |
+
fl_gamma: 0.0
|
27 |
+
hsv_h: 0.01041
|
28 |
+
hsv_s: 0.54703
|
29 |
+
hsv_v: 0.27739
|
30 |
+
degrees: 0.0
|
31 |
+
translate: 0.04591
|
32 |
+
scale: 0.75544
|
33 |
+
shear: 0.0
|
34 |
+
perspective: 0.0
|
35 |
+
flipud: 0.0
|
36 |
+
fliplr: 0.5
|
37 |
+
mosaic: 0.85834
|
38 |
+
mixup: 0.04266
|
39 |
+
copy_paste: 0.0
|
40 |
+
anchors: 3.412
|
yolov5/data/hyps/hyp.scratch-high.yaml
ADDED
@@ -0,0 +1,34 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
# YOLOv5 π by Ultralytics, GPL-3.0 license
|
2 |
+
# Hyperparameters for high-augmentation COCO training from scratch
|
3 |
+
# python train.py --batch 32 --cfg yolov5m6.yaml --weights '' --data coco.yaml --img 1280 --epochs 300
|
4 |
+
# See tutorials for hyperparameter evolution https://github.com/ultralytics/yolov5#tutorials
|
5 |
+
|
6 |
+
lr0: 0.01 # initial learning rate (SGD=1E-2, Adam=1E-3)
|
7 |
+
lrf: 0.1 # final OneCycleLR learning rate (lr0 * lrf)
|
8 |
+
momentum: 0.937 # SGD momentum/Adam beta1
|
9 |
+
weight_decay: 0.0005 # optimizer weight decay 5e-4
|
10 |
+
warmup_epochs: 3.0 # warmup epochs (fractions ok)
|
11 |
+
warmup_momentum: 0.8 # warmup initial momentum
|
12 |
+
warmup_bias_lr: 0.1 # warmup initial bias lr
|
13 |
+
box: 0.05 # box loss gain
|
14 |
+
cls: 0.3 # cls loss gain
|
15 |
+
cls_pw: 1.0 # cls BCELoss positive_weight
|
16 |
+
obj: 0.7 # obj loss gain (scale with pixels)
|
17 |
+
obj_pw: 1.0 # obj BCELoss positive_weight
|
18 |
+
iou_t: 0.20 # IoU training threshold
|
19 |
+
anchor_t: 4.0 # anchor-multiple threshold
|
20 |
+
# anchors: 3 # anchors per output layer (0 to ignore)
|
21 |
+
fl_gamma: 0.0 # focal loss gamma (efficientDet default gamma=1.5)
|
22 |
+
hsv_h: 0.015 # image HSV-Hue augmentation (fraction)
|
23 |
+
hsv_s: 0.7 # image HSV-Saturation augmentation (fraction)
|
24 |
+
hsv_v: 0.4 # image HSV-Value augmentation (fraction)
|
25 |
+
degrees: 0.0 # image rotation (+/- deg)
|
26 |
+
translate: 0.1 # image translation (+/- fraction)
|
27 |
+
scale: 0.9 # image scale (+/- gain)
|
28 |
+
shear: 0.0 # image shear (+/- deg)
|
29 |
+
perspective: 0.0 # image perspective (+/- fraction), range 0-0.001
|
30 |
+
flipud: 0.0 # image flip up-down (probability)
|
31 |
+
fliplr: 0.5 # image flip left-right (probability)
|
32 |
+
mosaic: 1.0 # image mosaic (probability)
|
33 |
+
mixup: 0.1 # image mixup (probability)
|
34 |
+
copy_paste: 0.1 # segment copy-paste (probability)
|
yolov5/data/hyps/hyp.scratch-low.yaml
ADDED
@@ -0,0 +1,34 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
# YOLOv5 π by Ultralytics, GPL-3.0 license
|
2 |
+
# Hyperparameters for low-augmentation COCO training from scratch
|
3 |
+
# python train.py --batch 64 --cfg yolov5n6.yaml --weights '' --data coco.yaml --img 640 --epochs 300 --linear
|
4 |
+
# See tutorials for hyperparameter evolution https://github.com/ultralytics/yolov5#tutorials
|
5 |
+
|
6 |
+
lr0: 0.01 # initial learning rate (SGD=1E-2, Adam=1E-3)
|
7 |
+
lrf: 0.01 # final OneCycleLR learning rate (lr0 * lrf)
|
8 |
+
momentum: 0.937 # SGD momentum/Adam beta1
|
9 |
+
weight_decay: 0.0005 # optimizer weight decay 5e-4
|
10 |
+
warmup_epochs: 3.0 # warmup epochs (fractions ok)
|
11 |
+
warmup_momentum: 0.8 # warmup initial momentum
|
12 |
+
warmup_bias_lr: 0.1 # warmup initial bias lr
|
13 |
+
box: 0.05 # box loss gain
|
14 |
+
cls: 0.5 # cls loss gain
|
15 |
+
cls_pw: 1.0 # cls BCELoss positive_weight
|
16 |
+
obj: 1.0 # obj loss gain (scale with pixels)
|
17 |
+
obj_pw: 1.0 # obj BCELoss positive_weight
|
18 |
+
iou_t: 0.20 # IoU training threshold
|
19 |
+
anchor_t: 4.0 # anchor-multiple threshold
|
20 |
+
# anchors: 3 # anchors per output layer (0 to ignore)
|
21 |
+
fl_gamma: 0.0 # focal loss gamma (efficientDet default gamma=1.5)
|
22 |
+
hsv_h: 0.015 # image HSV-Hue augmentation (fraction)
|
23 |
+
hsv_s: 0.7 # image HSV-Saturation augmentation (fraction)
|
24 |
+
hsv_v: 0.4 # image HSV-Value augmentation (fraction)
|
25 |
+
degrees: 0.0 # image rotation (+/- deg)
|
26 |
+
translate: 0.1 # image translation (+/- fraction)
|
27 |
+
scale: 0.5 # image scale (+/- gain)
|
28 |
+
shear: 0.0 # image shear (+/- deg)
|
29 |
+
perspective: 0.0 # image perspective (+/- fraction), range 0-0.001
|
30 |
+
flipud: 0.0 # image flip up-down (probability)
|
31 |
+
fliplr: 0.5 # image flip left-right (probability)
|
32 |
+
mosaic: 1.0 # image mosaic (probability)
|
33 |
+
mixup: 0.0 # image mixup (probability)
|
34 |
+
copy_paste: 0.0 # segment copy-paste (probability)
|
yolov5/data/hyps/hyp.scratch-med.yaml
ADDED
@@ -0,0 +1,34 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
# YOLOv5 π by Ultralytics, GPL-3.0 license
|
2 |
+
# Hyperparameters for medium-augmentation COCO training from scratch
|
3 |
+
# python train.py --batch 32 --cfg yolov5m6.yaml --weights '' --data coco.yaml --img 1280 --epochs 300
|
4 |
+
# See tutorials for hyperparameter evolution https://github.com/ultralytics/yolov5#tutorials
|
5 |
+
|
6 |
+
lr0: 0.01 # initial learning rate (SGD=1E-2, Adam=1E-3)
|
7 |
+
lrf: 0.1 # final OneCycleLR learning rate (lr0 * lrf)
|
8 |
+
momentum: 0.937 # SGD momentum/Adam beta1
|
9 |
+
weight_decay: 0.0005 # optimizer weight decay 5e-4
|
10 |
+
warmup_epochs: 3.0 # warmup epochs (fractions ok)
|
11 |
+
warmup_momentum: 0.8 # warmup initial momentum
|
12 |
+
warmup_bias_lr: 0.1 # warmup initial bias lr
|
13 |
+
box: 0.05 # box loss gain
|
14 |
+
cls: 0.3 # cls loss gain
|
15 |
+
cls_pw: 1.0 # cls BCELoss positive_weight
|
16 |
+
obj: 0.7 # obj loss gain (scale with pixels)
|
17 |
+
obj_pw: 1.0 # obj BCELoss positive_weight
|
18 |
+
iou_t: 0.20 # IoU training threshold
|
19 |
+
anchor_t: 4.0 # anchor-multiple threshold
|
20 |
+
# anchors: 3 # anchors per output layer (0 to ignore)
|
21 |
+
fl_gamma: 0.0 # focal loss gamma (efficientDet default gamma=1.5)
|
22 |
+
hsv_h: 0.015 # image HSV-Hue augmentation (fraction)
|
23 |
+
hsv_s: 0.7 # image HSV-Saturation augmentation (fraction)
|
24 |
+
hsv_v: 0.4 # image HSV-Value augmentation (fraction)
|
25 |
+
degrees: 0.0 # image rotation (+/- deg)
|
26 |
+
translate: 0.1 # image translation (+/- fraction)
|
27 |
+
scale: 0.9 # image scale (+/- gain)
|
28 |
+
shear: 0.0 # image shear (+/- deg)
|
29 |
+
perspective: 0.0 # image perspective (+/- fraction), range 0-0.001
|
30 |
+
flipud: 0.0 # image flip up-down (probability)
|
31 |
+
fliplr: 0.5 # image flip left-right (probability)
|
32 |
+
mosaic: 1.0 # image mosaic (probability)
|
33 |
+
mixup: 0.1 # image mixup (probability)
|
34 |
+
copy_paste: 0.0 # segment copy-paste (probability)
|
yolov5/data/images/bus.jpg
ADDED
![]() |
yolov5/data/images/zidane.jpg
ADDED
![]() |
yolov5/data/scripts/download_weights.sh
ADDED
@@ -0,0 +1,20 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
#!/bin/bash
|
2 |
+
# YOLOv5 π by Ultralytics, GPL-3.0 license
|
3 |
+
# Download latest models from https://github.com/ultralytics/yolov5/releases
|
4 |
+
# Example usage: bash path/to/download_weights.sh
|
5 |
+
# parent
|
6 |
+
# βββ yolov5
|
7 |
+
# βββ yolov5s.pt β downloads here
|
8 |
+
# βββ yolov5m.pt
|
9 |
+
# βββ ...
|
10 |
+
|
11 |
+
python - <<EOF
|
12 |
+
from utils.downloads import attempt_download
|
13 |
+
|
14 |
+
models = ['n', 's', 'm', 'l', 'x']
|
15 |
+
models.extend([x + '6' for x in models]) # add P6 models
|
16 |
+
|
17 |
+
for x in models:
|
18 |
+
attempt_download(f'yolov5{x}.pt')
|
19 |
+
|
20 |
+
EOF
|
yolov5/data/scripts/get_coco.sh
ADDED
@@ -0,0 +1,27 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
#!/bin/bash
|
2 |
+
# YOLOv5 π by Ultralytics, GPL-3.0 license
|
3 |
+
# Download COCO 2017 dataset http://cocodataset.org
|
4 |
+
# Example usage: bash data/scripts/get_coco.sh
|
5 |
+
# parent
|
6 |
+
# βββ yolov5
|
7 |
+
# βββ datasets
|
8 |
+
# βββ coco β downloads here
|
9 |
+
|
10 |
+
# Download/unzip labels
|
11 |
+
d='../datasets' # unzip directory
|
12 |
+
url=https://github.com/ultralytics/yolov5/releases/download/v1.0/
|
13 |
+
f='coco2017labels.zip' # or 'coco2017labels-segments.zip', 68 MB
|
14 |
+
echo 'Downloading' $url$f ' ...'
|
15 |
+
curl -L $url$f -o $f && unzip -q $f -d $d && rm $f &
|
16 |
+
|
17 |
+
# Download/unzip images
|
18 |
+
d='../datasets/coco/images' # unzip directory
|
19 |
+
url=http://images.cocodataset.org/zips/
|
20 |
+
f1='train2017.zip' # 19G, 118k images
|
21 |
+
f2='val2017.zip' # 1G, 5k images
|
22 |
+
f3='test2017.zip' # 7G, 41k images (optional)
|
23 |
+
for f in $f1 $f2; do
|
24 |
+
echo 'Downloading' $url$f '...'
|
25 |
+
curl -L $url$f -o $f && unzip -q $f -d $d && rm $f &
|
26 |
+
done
|
27 |
+
wait # finish background tasks
|
yolov5/data/scripts/get_coco128.sh
ADDED
@@ -0,0 +1,17 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
#!/bin/bash
|
2 |
+
# YOLOv5 π by Ultralytics, GPL-3.0 license
|
3 |
+
# Download COCO128 dataset https://www.kaggle.com/ultralytics/coco128 (first 128 images from COCO train2017)
|
4 |
+
# Example usage: bash data/scripts/get_coco128.sh
|
5 |
+
# parent
|
6 |
+
# βββ yolov5
|
7 |
+
# βββ datasets
|
8 |
+
# βββ coco128 β downloads here
|
9 |
+
|
10 |
+
# Download/unzip images and labels
|
11 |
+
d='../datasets' # unzip directory
|
12 |
+
url=https://github.com/ultralytics/yolov5/releases/download/v1.0/
|
13 |
+
f='coco128.zip' # or 'coco128-segments.zip', 68 MB
|
14 |
+
echo 'Downloading' $url$f ' ...'
|
15 |
+
curl -L $url$f -o $f && unzip -q $f -d $d && rm $f &
|
16 |
+
|
17 |
+
wait # finish background tasks
|
yolov5/data/xView.yaml
ADDED
@@ -0,0 +1,102 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
# YOLOv5 π by Ultralytics, GPL-3.0 license
|
2 |
+
# DIUx xView 2018 Challenge https://challenge.xviewdataset.org by U.S. National Geospatial-Intelligence Agency (NGA)
|
3 |
+
# -------- DOWNLOAD DATA MANUALLY and jar xf val_images.zip to 'datasets/xView' before running train command! --------
|
4 |
+
# Example usage: python train.py --data xView.yaml
|
5 |
+
# parent
|
6 |
+
# βββ yolov5
|
7 |
+
# βββ datasets
|
8 |
+
# βββ xView β downloads here (20.7 GB)
|
9 |
+
|
10 |
+
|
11 |
+
# Train/val/test sets as 1) dir: path/to/imgs, 2) file: path/to/imgs.txt, or 3) list: [path/to/imgs1, path/to/imgs2, ..]
|
12 |
+
path: ../datasets/xView # dataset root dir
|
13 |
+
train: images/autosplit_train.txt # train images (relative to 'path') 90% of 847 train images
|
14 |
+
val: images/autosplit_val.txt # train images (relative to 'path') 10% of 847 train images
|
15 |
+
|
16 |
+
# Classes
|
17 |
+
nc: 60 # number of classes
|
18 |
+
names: ['Fixed-wing Aircraft', 'Small Aircraft', 'Cargo Plane', 'Helicopter', 'Passenger Vehicle', 'Small Car', 'Bus',
|
19 |
+
'Pickup Truck', 'Utility Truck', 'Truck', 'Cargo Truck', 'Truck w/Box', 'Truck Tractor', 'Trailer',
|
20 |
+
'Truck w/Flatbed', 'Truck w/Liquid', 'Crane Truck', 'Railway Vehicle', 'Passenger Car', 'Cargo Car',
|
21 |
+
'Flat Car', 'Tank car', 'Locomotive', 'Maritime Vessel', 'Motorboat', 'Sailboat', 'Tugboat', 'Barge',
|
22 |
+
'Fishing Vessel', 'Ferry', 'Yacht', 'Container Ship', 'Oil Tanker', 'Engineering Vehicle', 'Tower crane',
|
23 |
+
'Container Crane', 'Reach Stacker', 'Straddle Carrier', 'Mobile Crane', 'Dump Truck', 'Haul Truck',
|
24 |
+
'Scraper/Tractor', 'Front loader/Bulldozer', 'Excavator', 'Cement Mixer', 'Ground Grader', 'Hut/Tent', 'Shed',
|
25 |
+
'Building', 'Aircraft Hangar', 'Damaged Building', 'Facility', 'Construction Site', 'Vehicle Lot', 'Helipad',
|
26 |
+
'Storage Tank', 'Shipping container lot', 'Shipping Container', 'Pylon', 'Tower'] # class names
|
27 |
+
|
28 |
+
|
29 |
+
# Download script/URL (optional) ---------------------------------------------------------------------------------------
|
30 |
+
download: |
|
31 |
+
import json
|
32 |
+
import os
|
33 |
+
from pathlib import Path
|
34 |
+
|
35 |
+
import numpy as np
|
36 |
+
from PIL import Image
|
37 |
+
from tqdm import tqdm
|
38 |
+
|
39 |
+
from utils.datasets import autosplit
|
40 |
+
from utils.general import download, xyxy2xywhn
|
41 |
+
|
42 |
+
|
43 |
+
def convert_labels(fname=Path('xView/xView_train.geojson')):
|
44 |
+
# Convert xView geoJSON labels to YOLO format
|
45 |
+
path = fname.parent
|
46 |
+
with open(fname) as f:
|
47 |
+
print(f'Loading {fname}...')
|
48 |
+
data = json.load(f)
|
49 |
+
|
50 |
+
# Make dirs
|
51 |
+
labels = Path(path / 'labels' / 'train')
|
52 |
+
os.system(f'rm -rf {labels}')
|
53 |
+
labels.mkdir(parents=True, exist_ok=True)
|
54 |
+
|
55 |
+
# xView classes 11-94 to 0-59
|
56 |
+
xview_class2index = [-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, 0, 1, 2, -1, 3, -1, 4, 5, 6, 7, 8, -1, 9, 10, 11,
|
57 |
+
12, 13, 14, 15, -1, -1, 16, 17, 18, 19, 20, 21, 22, -1, 23, 24, 25, -1, 26, 27, -1, 28, -1,
|
58 |
+
29, 30, 31, 32, 33, 34, 35, 36, 37, -1, 38, 39, 40, 41, 42, 43, 44, 45, -1, -1, -1, -1, 46,
|
59 |
+
47, 48, 49, -1, 50, 51, -1, 52, -1, -1, -1, 53, 54, -1, 55, -1, -1, 56, -1, 57, -1, 58, 59]
|
60 |
+
|
61 |
+
shapes = {}
|
62 |
+
for feature in tqdm(data['features'], desc=f'Converting {fname}'):
|
63 |
+
p = feature['properties']
|
64 |
+
if p['bounds_imcoords']:
|
65 |
+
id = p['image_id']
|
66 |
+
file = path / 'train_images' / id
|
67 |
+
if file.exists(): # 1395.tif missing
|
68 |
+
try:
|
69 |
+
box = np.array([int(num) for num in p['bounds_imcoords'].split(",")])
|
70 |
+
assert box.shape[0] == 4, f'incorrect box shape {box.shape[0]}'
|
71 |
+
cls = p['type_id']
|
72 |
+
cls = xview_class2index[int(cls)] # xView class to 0-60
|
73 |
+
assert 59 >= cls >= 0, f'incorrect class index {cls}'
|
74 |
+
|
75 |
+
# Write YOLO label
|
76 |
+
if id not in shapes:
|
77 |
+
shapes[id] = Image.open(file).size
|
78 |
+
box = xyxy2xywhn(box[None].astype(np.float), w=shapes[id][0], h=shapes[id][1], clip=True)
|
79 |
+
with open((labels / id).with_suffix('.txt'), 'a') as f:
|
80 |
+
f.write(f"{cls} {' '.join(f'{x:.6f}' for x in box[0])}\n") # write label.txt
|
81 |
+
except Exception as e:
|
82 |
+
print(f'WARNING: skipping one label for {file}: {e}')
|
83 |
+
|
84 |
+
|
85 |
+
# Download manually from https://challenge.xviewdataset.org
|
86 |
+
dir = Path(yaml['path']) # dataset root dir
|
87 |
+
# urls = ['https://d307kc0mrhucc3.cloudfront.net/train_labels.zip', # train labels
|
88 |
+
# 'https://d307kc0mrhucc3.cloudfront.net/train_images.zip', # 15G, 847 train images
|
89 |
+
# 'https://d307kc0mrhucc3.cloudfront.net/val_images.zip'] # 5G, 282 val images (no labels)
|
90 |
+
# download(urls, dir=dir, delete=False)
|
91 |
+
|
92 |
+
# Convert labels
|
93 |
+
convert_labels(dir / 'xView_train.geojson')
|
94 |
+
|
95 |
+
# Move images
|
96 |
+
images = Path(dir / 'images')
|
97 |
+
images.mkdir(parents=True, exist_ok=True)
|
98 |
+
Path(dir / 'train_images').rename(dir / 'images' / 'train')
|
99 |
+
Path(dir / 'val_images').rename(dir / 'images' / 'val')
|
100 |
+
|
101 |
+
# Split
|
102 |
+
autosplit(dir / 'images' / 'train')
|