Delete 恶劣天气识别部署到gradio.ipynb

恶劣天气识别部署到gradio.ipynb

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-{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"provenance":[],"collapsed_sections":[]},"kernelspec":{"name":"python3","display_name":"Python 3"},"gpuClass":"standard"},"cells":[{"cell_type":"markdown","metadata":{"id":"D_XJcxqx22uj"},"source":["## Using Gradio to create a simple interface.\n","\n","Check out the library on [github](https://github.com/gradio-app/gradio-UI) and see the [getting started](https://gradio.app/getting_started.html) page for more demos."]},{"cell_type":"markdown","metadata":{"id":"AUHtJ20jYqd9"},"source":["We'll start with a basic function that greets an input name."]},{"cell_type":"markdown","metadata":{"id":"R06dbZZaYJDq"},"source":["Now we'll wrap this function with a Gradio interface."]},{"cell_type":"code","metadata":{"id":"fJUJLWQ92g6R","executionInfo":{"status":"ok","timestamp":1665584386249,"user_tz":-480,"elapsed":21161,"user":{"displayName":"金先生","userId":"07679655535683887373"}},"colab":{"base_uri":"https://localhost:8080/"},"outputId":"9ba21fe3-b6d3-4cb4-8d13-98ae8c94931b"},"source":["!pip install -q gradio"],"execution_count":1,"outputs":[{"output_type":"stream","name":"stdout","text":["\u001b[K     |████████████████████████████████| 5.3 MB 5.3 MB/s \n","\u001b[K     |████████████████████████████████| 112 kB 66.5 MB/s \n","\u001b[K     |████████████████████████████████| 212 kB 58.1 MB/s \n","\u001b[K     |████████████████████████████████| 57 kB 5.5 MB/s \n","\u001b[K     |████████████████████████████████| 84 kB 3.6 MB/s \n","\u001b[K     |████████████████████████████████| 2.3 MB 41.4 MB/s \n","\u001b[K     |████████████████████████████████| 270 kB 75.7 MB/s \n","\u001b[K     |████████████████████████████████| 54 kB 3.1 MB/s \n","\u001b[K     |████████████████████████████████| 55 kB 3.7 MB/s \n","\u001b[K     |████████████████████████████████| 84 kB 3.0 MB/s \n","\u001b[K     |████████████████████████████████| 63 kB 2.0 MB/s \n","\u001b[K     |████████████████████████████████| 80 kB 8.9 MB/s \n","\u001b[K     |████████████████████████████████| 68 kB 6.8 MB/s \n","\u001b[K     |████████████████████████████████| 46 kB 4.2 MB/s \n","\u001b[K     |████████████████████████████████| 4.1 MB 38.1 MB/s \n","\u001b[K     |████████████████████████████████| 593 kB 54.1 MB/s \n","\u001b[K     |████████████████████████████████| 856 kB 57.6 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"]}]},{"cell_type":"markdown","metadata":{"id":"uQheRaw5YVTL"},"source":["That's all! Go ahead and open that share link in a new tab. Check out our [getting started](https://gradio.app/getting_started.html) page for more complicated demos."]},{"cell_type":"code","source":["from google.colab import drive\n","drive.mount('/content/drive')"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"KlZeF5loRGRe","executionInfo":{"status":"ok","timestamp":1665584414521,"user_tz":-480,"elapsed":28277,"user":{"displayName":"金先生","userId":"07679655535683887373"}},"outputId":"3eb19891-35d9-4332-9c63-5a8a347cd34a"},"execution_count":2,"outputs":[{"output_type":"stream","name":"stdout","text":["Mounted at /content/drive\n"]}]},{"cell_type":"code","source":["from keras.datasets import mnist\n","from keras.utils import np_utils\n","from keras.models import Sequential\n","from keras.layers import Dense,Activation"],"metadata":{"id":"4OpspV6iV1wS","executionInfo":{"status":"ok","timestamp":1665584417575,"user_tz":-480,"elapsed":3059,"user":{"displayName":"金先生","userId":"07679655535683887373"}}},"execution_count":3,"outputs":[]},{"cell_type":"code","metadata":{"id":"e200MmBU2aLT","executionInfo":{"status":"ok","timestamp":1665584417575,"user_tz":-480,"elapsed":4,"user":{"displayName":"金先生","userId":"07679655535683887373"}}},"source":["# import gradio\n","# gradio.Interface(greet, \"text\", \"text\").launch(share=True)\n","from keras.models import load_model\n","#import tensorflow as tf\n","# 替换自己的模型\n","#inception_net = tf.keras.applications.MobileNetV2()\n"],"execution_count":4,"outputs":[]},{"cell_type":"code","source":["from keras.models import load_model\n","import numpy as np\n","from keras.preprocessing import image\n","from keras.preprocessing.image import load_img\n","from PIL import ImageFilter\n","from PIL import Image\n","import cv2\n","import os\n","\n","#PHOTO_SIZE = 120  #对图片大小进行限制，低于120KB的抛弃\n","#path = r'/content/sunny.jpg'  # 目标\n","weight_path = r'/content/drive/MyDrive/恶劣天气图像识别代码-毕业设计-戴一凡/basic.h5' #权重文件\n","\n","#re_x =256  #输入到神经网络中的文件的大小\n","\n","model = load_model(weight_path)\n","#img = Image.open(path)\n","#img = img.resize((re_x,re_x), Image.ANTIALIAS) #缩放到事先指定的大小\n","#img = np.expand_dims(img, axis=0)\n","#print(img)\n","#inception_net=model.predict(img)#获取预测值\n"],"metadata":{"id":"V1H-DJgUZ3YX","executionInfo":{"status":"ok","timestamp":1665584473831,"user_tz":-480,"elapsed":1068,"user":{"displayName":"金先生","userId":"07679655535683887373"}}},"execution_count":6,"outputs":[]},{"cell_type":"code","source":["#labels =['Srainy', 'Mrainy', 'Lrainy', 'Sfoggy', 'Mfoggy','Lfoggy','sunny']\n","labels=['天气:小雨，  降雨强度(mm/min):0.8，  能见度(m):500，  道路摩擦系数:0.64,  限速(km/h):80',\n","    '天气:中雨，  降雨强度(mm/min):1.2，  能见度(m):250，  道路摩擦系数:0.58,  限速(km/h):50',\n","    '天气:大雨，  降雨强度(mm/min):1.6，  能见度(m):50-150， 道路摩擦系数:0.45,  限速(km/h):30',\n","    '天气:薄雾，  降雨强度(mm/min):0，   能见度(m):500:，  道路摩擦系数:0.8,  限速(km/h):110',\n","    '天气:大雾，  降雨强度(mm/min):0，   能见度(m):200，   道路摩擦系数:0.8,  限速(km/h):70',\n","    '天气:浓雾，  降雨强度(mm/min):0:，   能见度(m):50-100， 道路摩擦系数:0.8,  限速(km/h):40',\n","    '天气:晴，   降雨强度(mm/min):0，   能见度(m):>1000:，  道路摩擦系数:0.8,  限速(km/h):120']\n","def classify_image(inp):\n","  inp = inp.resize((256,256), Image.ANTIALIAS) #缩放到事先指定的大小\n","  inp = np.expand_dims(inp, axis=0)\n","  prediction = model.predict(inp)\n","  confidences = {labels[i]: float(prediction[0][i]) for i in range(7)}\n","  return confidences\n","#path = r'/content/rainy.jpg'\n","\n","#img = Image.open(path)\n","#print(classify_image(img))"],"metadata":{"id":"Og4_R6lN49al","executionInfo":{"status":"ok","timestamp":1665584477391,"user_tz":-480,"elapsed":2,"user":{"displayName":"金先生","userId":"07679655535683887373"}}},"execution_count":7,"outputs":[]},{"cell_type":"code","source":["import gradio as gr\n","git clone https://huggingface.co/spaces/WWt/zz12\n","gr.Interface(\n","    fn=classify_image,\n","    inputs=gr.Image(type=\"pil\",shape=(256,256)),\n","    outputs=gr.Label(num_top_classes=1),\n","    examples=[\"rainy.jpg\", \"sunny.jpg\"],\n","    interpretation=\"default\",cache_examples=True,title=\"恶劣天气图像识别与预警\"\n",").launch(enable_queue=True)\n","git add app.py\n","git commit -m \"Add application file\"\n","git push\n"],"metadata":{"id":"8Ls0etEpC1h4","colab":{"base_uri":"https://localhost:8080/","height":134},"executionInfo":{"status":"error","timestamp":1665585158903,"user_tz":-480,"elapsed":455,"user":{"displayName":"金先生","userId":"07679655535683887373"}},"outputId":"2fb94f86-c054-44ad-ed79-0e39eb6177e7"},"execution_count":17,"outputs":[{"output_type":"error","ename":"SyntaxError","evalue":"ignored","traceback":["\u001b[0;36m  File \u001b[0;32m\"<ipython-input-17-0a596af2e30b>\"\u001b[0;36m, line \u001b[0;32m2\u001b[0m\n\u001b[0;31m    git clone https://huggingface.co/spaces/WWt/zz12\u001b[0m\n\u001b[0m            ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m invalid syntax\n"]}]},{"cell_type":"code","source":["import gradio as gr\n","def generate_mutimodal(title, context, senti, num, img):\n","    return f\"Title:{title}\\nContext:{context}\\nSenti:{senti}\\nNum:{num}...{img}\"\n","    \n","server = gr.Interface(\n","    fn=generate_mutimodal, \n","    inputs=[\n","        gr.Textbox(lines=1, placeholder=\"请输入标题\", label=\"标题\", interactive=True),  # interactive指定该组件是否允许用户输入或者交互\n","        gr.Textbox(lines=2, placeholder=\"请输入正文\", label=\"正文\"),\n","        gr.Radio([\"0\", \"1\", \"随机\"], label=\"倾向\"),\n","        gr.Number(label='条数'),\n","        gr.Image(shape=(200, 200),  label=\"请上传图片(可选)\").style(height='24', rounded=True)\n","    ], \n","    outputs=\"text\",\n","    examples=[\n","        [\"标题1\", \"正文1\", \"0\", None],\n","        [\"标题2\", \"正文2\", \"随机\"],\n","    ],\n","    title=\"可控文本生成\",\n","    description=\"标题和正文至少一个非空，图片可选是否上传\",\n","    article=\"\"\"\n","        ### 这里是底部的article\n","        #### article 1\n","        This is article 1\n","    \"\"\",\n","    css=\"body {background-color: red; font-size: large}\",\n","    allow_flagging=\"never\",     # 输出侧是否开启flag功能 比如让用户去标记输出结果是否正确 写到日志\n","    live=False,                 # live: 用户输入改变时是否自动计算结果\n","    cache_examples=False,       # cache_examples: 是否将example里的结果提前算好存到缓存里\n",")\n","\n","server.launch(\n","    enable_queue=False,         # enable_queue: 如果app流量很大，需设置参数以防止超时。这将使用长轮询对调用进行排队，一次仅处理一个调用。长轮询还可以防止网络超时，因此，如果函数的推理时间很长（> 1 分钟），则应使用队列。\n","    auth=(\"admin\", \"admin\"),    # auth: 参数值可以是 (user, pwd) 的元组，也可以是一个函数名（用户名和密码是参数, 并返回 True/False）。enable_queue=True 时，auth不能传元组。\n","    share=True                 # share: 可生成 72h 的公网访问地址，原理相当于 gradio 提供了一个内网穿透的代理，并没有把代码+环境上传到他们服务器\n",")\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"h0SZKbaerIST","executionInfo":{"status":"ok","timestamp":1665552816914,"user_tz":-480,"elapsed":5630,"user":{"displayName":"金先生","userId":"07679655535683887373"}},"outputId":"6e12b243-6d41-4fcb-ecce-c27255a0b8f7"},"execution_count":7,"outputs":[{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.7/dist-packages/gradio/components.py:197: UserWarning: 'rounded' styling is no longer supported. To round adjacent components together, place them in a Column(variant='box').\n","  \"'rounded' styling is no longer supported. To round adjacent components together, place them in a Column(variant='box').\"\n"]},{"output_type":"stream","name":"stdout","text":["Colab notebook detected. To show errors in colab notebook, set `debug=True` in `launch()`\n","Running on public URL: https://17915.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":"execute_result","data":{"text/plain":["(<gradio.routes.App at 0x7f9d6e3bfb10>,\n"," 'http://127.0.0.1:7861/',\n"," 'https://17915.gradio.app')"]},"metadata":{},"execution_count":7}]},{"cell_type":"code","source":[],"metadata":{"id":"t86gBSOLMFmX"},"execution_count":null,"outputs":[]}]}