modified: app.py

.ipynb_checkpoints/app-checkpoint.ipynb

@@ -0,0 +1,298 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "d2c2b738",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from fastai.vision.all import *\n",
+    "import gradio as gr"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "b92d24f3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# search_terms = ('hard hat','construction gloves','safety glasses','construction boots', 'screw driver','hammer','f150')\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "34ebdca4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "path = Path('construction_photos')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "04347f65",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['construction boots', 'construction gloves', 'f150', 'hammer', 'hard hat', 'safety glasses', 'screw driver']"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "dls = DataBlock(\n",
+    "    blocks=(ImageBlock,CategoryBlock),\n",
+    "    getters=None,\n",
+    "    n_inp=None,\n",
+    "    item_tfms=[Resize(224,method='squish')],\n",
+    "    get_items=get_image_files,\n",
+    "    splitter=RandomSplitter(seed=42),\n",
+    "    get_y=parent_label,\n",
+    ").dataloaders('../python_clean_code_book/construction_photos/',bs=128)\n",
+    "# ).dataloaders()\n",
+    "#['construction boots', 'construction gloves', 'f150', 'hammer', 'hard hat', 'safety glasses', 'screw driver']\n",
+    "dls.vocab"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "85098e65",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "learn = load_learner('construction_things.pkl')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "a6ed198b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def classify_image(img):\n",
+    "    pred,idx,probs = learn.predict(img)\n",
+    "    return dict(zip(['construction boots', 'construction gloves', 'f150', 'hammer', 'hard hat', 'safety glasses', 'screw driver'],map(float,probs)))\n",
+    "# classify_image(get_image_files(path)[100])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "dccf379e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "<style>\n",
+       "    /* Turns off some styling */\n",
+       "    progress {\n",
+       "        /* gets rid of default border in Firefox and Opera. */\n",
+       "        border: none;\n",
+       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
+       "        background-size: auto;\n",
+       "    }\n",
+       "    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
+       "        background: #F44336;\n",
+       "    }\n",
+       "</style>\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "{'construction boots': 5.033571142121218e-07,\n",
+       " 'construction gloves': 1.9164571085639182e-07,\n",
+       " 'f150': 0.9999986886978149,\n",
+       " 'hammer': 2.487358869984746e-07,\n",
+       " 'hard hat': 9.779357412753598e-08,\n",
+       " 'safety glasses': 2.88559984795711e-08,\n",
+       " 'screw driver': 1.963149287576016e-07}"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "classify_image('../../ebs1/python_clean_code_book/construction_photos/f150/00000000.jpg')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "b2f582a8",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Running on local URL:  http://127.0.0.1:7861/\n",
+      "Running on public URL: https://54519.gradio.app\n",
+      "\n",
+      "This share link expires in 72 hours. For free permanent hosting, check out Spaces (https://huggingface.co/spaces)\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "        <iframe\n",
+       "            width=\"900\"\n",
+       "            height=\"500\"\n",
+       "            src=\"https://54519.gradio.app\"\n",
+       "            frameborder=\"0\"\n",
+       "            allowfullscreen\n",
+       "            \n",
+       "        ></iframe>\n",
+       "        "
+      ],
+      "text/plain": [
+       "<IPython.lib.display.IFrame at 0x7f2dc985d640>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "(<fastapi.applications.FastAPI at 0x7f2de255f3d0>,\n",
+       " 'http://127.0.0.1:7861/',\n",
+       " 'https://54519.gradio.app')"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "<style>\n",
+       "    /* Turns off some styling */\n",
+       "    progress {\n",
+       "        /* gets rid of default border in Firefox and Opera. */\n",
+       "        border: none;\n",
+       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
+       "        background-size: auto;\n",
+       "    }\n",
+       "    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
+       "        background: #F44336;\n",
+       "    }\n",
+       "</style>\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Traceback (most recent call last):\n",
+      "  File \"/root/miniconda/lib/python3.9/site-packages/gradio/routes.py\", line 269, in predict\n",
+      "    output = await run_in_threadpool(app.launchable.process_api, body, username)\n",
+      "  File \"/root/miniconda/lib/python3.9/site-packages/starlette/concurrency.py\", line 45, in run_in_threadpool\n",
+      "    return await anyio.to_thread.run_sync(func, *args)\n",
+      "  File \"/root/miniconda/lib/python3.9/site-packages/anyio/to_thread.py\", line 28, in run_sync\n",
+      "    return await get_asynclib().run_sync_in_worker_thread(func, *args, cancellable=cancellable,\n",
+      "  File \"/root/miniconda/lib/python3.9/site-packages/anyio/_backends/_asyncio.py\", line 818, in run_sync_in_worker_thread\n",
+      "    return await future\n",
+      "  File \"/root/miniconda/lib/python3.9/site-packages/anyio/_backends/_asyncio.py\", line 754, in run\n",
+      "    result = context.run(func, *args)\n",
+      "  File \"/root/miniconda/lib/python3.9/site-packages/gradio/interface.py\", line 573, in process_api\n",
+      "    prediction, durations = self.process(raw_input)\n",
+      "  File \"/root/miniconda/lib/python3.9/site-packages/gradio/interface.py\", line 615, in process\n",
+      "    predictions, durations = self.run_prediction(\n",
+      "  File \"/root/miniconda/lib/python3.9/site-packages/gradio/interface.py\", line 531, in run_prediction\n",
+      "    prediction = predict_fn(*processed_input)\n",
+      "  File \"/tmp/ipykernel_11528/2341249033.py\", line 3, in classify_image\n",
+      "    return dict(zip(dls.vocab,map(float,probs)))\n",
+      "NameError: name 'dls' is not defined\n"
+     ]
+    }
+   ],
+   "source": [
+    "image = gr.inputs.Image(shape=(192,192))\n",
+    "label = gr.outputs.Label()\n",
+    "interface = gr.Interface(fn=classify_image,inputs=image,outputs=label)\n",
+    "interface.launch(inline=True,share=True)\n",
+    "# interface.launch(inline=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4b39ddcb",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.7"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

app.ipynb

@@ -23,30 +23,44 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 9,
    "id": "34ebdca4",
    "metadata": {},
    "outputs": [],
    "source": [
-    "# path = Path('construction_photos')"
+    "path = Path('construction_photos')"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 12,
    "id": "04347f65",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['construction boots', 'construction gloves', 'f150', 'hammer', 'hard hat', 'safety glasses', 'screw driver']"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "# dls = DataBlock(\n",
-    "#     blocks=(ImageBlock,CategoryBlock),\n",
-    "#     getters=None,\n",
-    "#     n_inp=None,\n",
-    "#     item_tfms=[Resize(224,method='squish')],\n",
-    "#     get_items=get_image_files,\n",
-    "#     splitter=RandomSplitter(seed=42),\n",
-    "#     get_y=parent_label,\n",
-    "# ).dataloaders(path,bs=128)"
+    "dls = DataBlock(\n",
+    "    blocks=(ImageBlock,CategoryBlock),\n",
+    "    getters=None,\n",
+    "    n_inp=None,\n",
+    "    item_tfms=[Resize(224,method='squish')],\n",
+    "    get_items=get_image_files,\n",
+    "    splitter=RandomSplitter(seed=42),\n",
+    "    get_y=parent_label,\n",
+    ").dataloaders('../python_clean_code_book/construction_photos/',bs=128)\n",
+    "# ).dataloaders()\n",
+    "#['construction boots', 'construction gloves', 'f150', 'hammer', 'hard hat', 'safety glasses', 'screw driver']\n",
+    "dls.vocab"
    ]
   },
   {
@@ -61,20 +75,81 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 13,
    "id": "a6ed198b",
    "metadata": {},
    "outputs": [],
    "source": [
     "def classify_image(img):\n",
     "    pred,idx,probs = learn.predict(img)\n",
-    "    return dict(zip(dls.vocab,map(float,probs)))\n",
+    "    return dict(zip(['construction boots', 'construction gloves', 'f150', 'hammer', 'hard hat', 'safety glasses', 'screw driver'],map(float,probs)))\n",
     "# classify_image(get_image_files(path)[100])"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 14,
+   "id": "dccf379e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "<style>\n",
+       "    /* Turns off some styling */\n",
+       "    progress {\n",
+       "        /* gets rid of default border in Firefox and Opera. */\n",
+       "        border: none;\n",
+       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
+       "        background-size: auto;\n",
+       "    }\n",
+       "    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
+       "        background: #F44336;\n",
+       "    }\n",
+       "</style>\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "{'construction boots': 5.033571142121218e-07,\n",
+       " 'construction gloves': 1.9164571085639182e-07,\n",
+       " 'f150': 0.9999986886978149,\n",
+       " 'hammer': 2.487358869984746e-07,\n",
+       " 'hard hat': 9.779357412753598e-08,\n",
+       " 'safety glasses': 2.88559984795711e-08,\n",
+       " 'screw driver': 1.963149287576016e-07}"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "classify_image('../../ebs1/python_clean_code_book/construction_photos/f150/00000000.jpg')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
    "id": "b2f582a8",
    "metadata": {},
    "outputs": [
@@ -82,31 +157,121 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Running on local URL:  http://127.0.0.1:7860/\n",
+      "Running on local URL:  http://127.0.0.1:7861/\n",
+      "Running on public URL: https://54519.gradio.app\n",
       "\n",
-      "To create a public link, set `share=True` in `launch()`.\n"
+      "This share link expires in 72 hours. For free permanent hosting, check out Spaces (https://huggingface.co/spaces)\n"
      ]
     },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "        <iframe\n",
+       "            width=\"900\"\n",
+       "            height=\"500\"\n",
+       "            src=\"https://54519.gradio.app\"\n",
+       "            frameborder=\"0\"\n",
+       "            allowfullscreen\n",
+       "            \n",
+       "        ></iframe>\n",
+       "        "
+      ],
+      "text/plain": [
+       "<IPython.lib.display.IFrame at 0x7f2dc985d640>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
     {
      "data": {
       "text/plain": [
-       "(<fastapi.applications.FastAPI at 0x7ff6a8761430>,\n",
-       " 'http://127.0.0.1:7860/',\n",
-       " None)"
+       "(<fastapi.applications.FastAPI at 0x7f2de255f3d0>,\n",
+       " 'http://127.0.0.1:7861/',\n",
+       " 'https://54519.gradio.app')"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "<style>\n",
+       "    /* Turns off some styling */\n",
+       "    progress {\n",
+       "        /* gets rid of default border in Firefox and Opera. */\n",
+       "        border: none;\n",
+       "        /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
+       "        background-size: auto;\n",
+       "    }\n",
+       "    .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
+       "        background: #F44336;\n",
+       "    }\n",
+       "</style>\n"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Traceback (most recent call last):\n",
+      "  File \"/root/miniconda/lib/python3.9/site-packages/gradio/routes.py\", line 269, in predict\n",
+      "    output = await run_in_threadpool(app.launchable.process_api, body, username)\n",
+      "  File \"/root/miniconda/lib/python3.9/site-packages/starlette/concurrency.py\", line 45, in run_in_threadpool\n",
+      "    return await anyio.to_thread.run_sync(func, *args)\n",
+      "  File \"/root/miniconda/lib/python3.9/site-packages/anyio/to_thread.py\", line 28, in run_sync\n",
+      "    return await get_asynclib().run_sync_in_worker_thread(func, *args, cancellable=cancellable,\n",
+      "  File \"/root/miniconda/lib/python3.9/site-packages/anyio/_backends/_asyncio.py\", line 818, in run_sync_in_worker_thread\n",
+      "    return await future\n",
+      "  File \"/root/miniconda/lib/python3.9/site-packages/anyio/_backends/_asyncio.py\", line 754, in run\n",
+      "    result = context.run(func, *args)\n",
+      "  File \"/root/miniconda/lib/python3.9/site-packages/gradio/interface.py\", line 573, in process_api\n",
+      "    prediction, durations = self.process(raw_input)\n",
+      "  File \"/root/miniconda/lib/python3.9/site-packages/gradio/interface.py\", line 615, in process\n",
+      "    predictions, durations = self.run_prediction(\n",
+      "  File \"/root/miniconda/lib/python3.9/site-packages/gradio/interface.py\", line 531, in run_prediction\n",
+      "    prediction = predict_fn(*processed_input)\n",
+      "  File \"/tmp/ipykernel_11528/2341249033.py\", line 3, in classify_image\n",
+      "    return dict(zip(dls.vocab,map(float,probs)))\n",
+      "NameError: name 'dls' is not defined\n"
+     ]
     }
    ],
    "source": [
     "image = gr.inputs.Image(shape=(192,192))\n",
     "label = gr.outputs.Label()\n",
     "interface = gr.Interface(fn=classify_image,inputs=image,outputs=label)\n",
-    "# interface.launch(inline=True)\n",
-    "interface.launch(inline=False)"
+    "interface.launch(inline=True,share=True)\n",
+    "# interface.launch(inline=False)"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4b39ddcb",
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {

app.py

@@ -5,7 +5,7 @@ learn = load_learner('construction_things.pkl')
 
 def classify_image(img):
     pred,idx,probs = learn.predict(img)
-    return dict(zip(dls.vocab,map(float,probs)))
+    return dict(zip(['construction boots', 'construction gloves', 'f150', 'hammer', 'hard hat', 'safety glasses', 'screw driver'],map(float,probs)))
     
 image = gr.inputs.Image(shape=(192,192))
 label = gr.outputs.Label()