app.py

{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.10.12","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load\n\n!pip install gradio\n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the read-only \"../input/\" directory\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n    for filename in filenames:\n        print(os.path.join(dirname, filename))\n\n# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","execution":{"iopub.status.busy":"2023-07-31T16:51:35.137587Z","iopub.execute_input":"2023-07-31T16:51:35.137972Z","iopub.status.idle":"2023-07-31T16:51:49.983937Z","shell.execute_reply.started":"2023-07-31T16:51:35.137942Z","shell.execute_reply":"2023-07-31T16:51:49.982981Z"},"trusted":true},"execution_count":4,"outputs":[{"name":"stdout","text":"Collecting gradio\n  Downloading gradio-3.39.0-py3-none-any.whl (19.9 MB)\n\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m 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in /opt/conda/lib/python3.10/site-packages (from httpcore<0.18.0,>=0.15.0->httpx->gradio) (3.7.0)\nRequirement already satisfied: pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0 in /opt/conda/lib/python3.10/site-packages (from jsonschema>=3.0->altair<6.0,>=4.2.0->gradio) (0.19.3)\nRequirement already satisfied: uc-micro-py in /opt/conda/lib/python3.10/site-packages (from linkify-it-py<3,>=1->markdown-it-py[linkify]>=2.0.0->gradio) (1.0.2)\nRequirement already satisfied: six>=1.5 in /opt/conda/lib/python3.10/site-packages (from python-dateutil>=2.7->matplotlib~=3.0->gradio) (1.16.0)\nRequirement already satisfied: exceptiongroup in /opt/conda/lib/python3.10/site-packages (from anyio<5.0,>=3.0->httpcore<0.18.0,>=0.15.0->httpx->gradio) (1.1.1)\nBuilding wheels for collected packages: ffmpy\n  Building wheel for ffmpy (setup.py) ... \u001b[?25ldone\n\u001b[?25h  Created wheel for ffmpy: filename=ffmpy-0.3.1-py3-none-any.whl size=5596 sha256=16e2d73fa9e26b4f018ce9b90ebf21cbdf6f84c3782b40830c35f79e76b9f3d7\n  Stored in directory: /root/.cache/pip/wheels/01/a6/d1/1c0828c304a4283b2c1639a09ad86f83d7c487ef34c6b4a1bf\nSuccessfully built ffmpy\nInstalling collected packages: ffmpy, semantic-version, python-multipart, mdit-py-plugins, httpcore, httpx, gradio-client, gradio\n  Attempting uninstall: mdit-py-plugins\n    Found existing installation: mdit-py-plugins 0.4.0\n    Uninstalling mdit-py-plugins-0.4.0:\n      Successfully uninstalled mdit-py-plugins-0.4.0\nSuccessfully installed ffmpy-0.3.1 gradio-3.39.0 gradio-client-0.3.0 httpcore-0.17.3 httpx-0.24.1 mdit-py-plugins-0.3.3 python-multipart-0.0.6 semantic-version-2.10.0\n/kaggle/input/bicycle-model/model.pkl\n","output_type":"stream"}]},{"cell_type":"code","source":"import gradio as gr\nfrom fastai.vision.all import *\nimport skimage\n\nlearn = load_learner('/kaggle/input/bicycle-model/model.pkl')","metadata":{"execution":{"iopub.status.busy":"2023-07-31T16:52:23.519405Z","iopub.execute_input":"2023-07-31T16:52:23.519821Z","iopub.status.idle":"2023-07-31T16:52:30.470389Z","shell.execute_reply.started":"2023-07-31T16:52:23.519792Z","shell.execute_reply":"2023-07-31T16:52:30.469705Z"},"trusted":true},"execution_count":5,"outputs":[{"name":"stderr","text":"/opt/conda/lib/python3.10/site-packages/scipy/__init__.py:146: UserWarning: A NumPy version >=1.16.5 and <1.23.0 is required for this version of SciPy (detected version 1.23.5\n  warnings.warn(f\"A NumPy version >={np_minversion} and <{np_maxversion}\"\n","output_type":"stream"}]},{"cell_type":"code","source":"labels = learn.dls.vocab\n\ndef predict(img):\n    img = PILImage.create(img)\n    pred, idx, probs = learn.predict(img)\n    return {labels[i]: float(probs[i]) for i in range(len(labels))}","metadata":{"execution":{"iopub.status.busy":"2023-07-31T16:52:36.499387Z","iopub.execute_input":"2023-07-31T16:52:36.499737Z","iopub.status.idle":"2023-07-31T16:52:36.506774Z","shell.execute_reply.started":"2023-07-31T16:52:36.499713Z","shell.execute_reply":"2023-07-31T16:52:36.505348Z"},"trusted":true},"execution_count":6,"outputs":[]},{"cell_type":"code","source":"examples = ['/kaggle/input/examples/street_bicycle.jpg',\n           '/kaggle/input/examples/street_image.jpg']\n\ngr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(512, 512)),\n             title = \"bicycle detector\",\n             examples = examples,\n             interpretation = 'default',\n             enable_queue = True,\n             outputs = gr.outputs.Label(num_top_classes=3)).launch(share=True),\n","metadata":{"execution":{"iopub.status.busy":"2023-07-31T17:01:15.166908Z","iopub.execute_input":"2023-07-31T17:01:15.168263Z","iopub.status.idle":"2023-07-31T17:01:25.050227Z","shell.execute_reply.started":"2023-07-31T17:01:15.168215Z","shell.execute_reply":"2023-07-31T17:01:25.049147Z"},"trusted":true},"execution_count":11,"outputs":[{"name":"stderr","text":"/tmp/ipykernel_32/2811948349.py:4: GradioDeprecationWarning: Usage of gradio.inputs is deprecated, and will not be supported in the future, please import your component from gradio.components\n  gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(512, 512)),\n/tmp/ipykernel_32/2811948349.py:4: GradioDeprecationWarning: `optional` parameter is deprecated, and it has no effect\n  gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(512, 512)),\n/tmp/ipykernel_32/2811948349.py:9: GradioDeprecationWarning: Usage of gradio.outputs is deprecated, and will not be supported in the future, please import your components from gradio.components\n  outputs = gr.outputs.Label(num_top_classes=3)).launch(share=True),\n/tmp/ipykernel_32/2811948349.py:9: GradioUnusedKwargWarning: You have unused kwarg parameters in Label, please remove them: {'type': 'auto'}\n  outputs = gr.outputs.Label(num_top_classes=3)).launch(share=True),\n/tmp/ipykernel_32/2811948349.py:4: GradioDeprecationWarning: `enable_queue` is deprecated in `Interface()`, please use it within `launch()` instead.\n  gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(512, 512)),\n","output_type":"stream"},{"name":"stdout","text":"Running on local URL:  http://127.0.0.1:7861\nRunning on public URL: https://c7c444abbdd5476b8a.gradio.live\n\nThis share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces)\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"<IPython.core.display.HTML object>","text/html":"<div><iframe src=\"https://c7c444abbdd5476b8a.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"},"metadata":{}},{"execution_count":11,"output_type":"execute_result","data":{"text/plain":"(,)"},"metadata":{}}]}]}