dog_breed_classifier_app.ipynb

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    },
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     "status": "ok",
     "timestamp": 1616668074794,
     "user": {
      "displayName": "Daniel Sobien",
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    },
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    "outputId": "1f2254a3-0dd9-445a-f2d2-700164081d99"
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   "outputs": [
    {
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     "text": [
      "/home/dan/anaconda3/envs/fastai/lib/python3.8/site-packages/torch/cuda/__init__.py:52: UserWarning: CUDA initialization: Found no NVIDIA driver on your system. Please check that you have an NVIDIA GPU and installed a driver from http://www.nvidia.com/Download/index.aspx (Triggered internally at  /opt/conda/conda-bld/pytorch_1607370172916/work/c10/cuda/CUDAFunctions.cpp:100.)\n",
      "  return torch._C._cuda_getDeviceCount() > 0\n"
     ]
    }
   ],
   "source": [
    "from fastai.vision.all import *\n",
    "from fastai.vision.widgets import *"
   ]
  },
  {
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   "execution_count": 2,
   "metadata": {
    "cellView": "form",
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      "userId": "05479789194651770839"
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    },
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   "outputs": [],
   "source": [
    "path = Path()\n",
    "learn_inf = load_learner(path/'dog_breed_resnet34.pkl')\n",
    "btn_upload = widgets.FileUpload()\n",
    "out_pl = widgets.Output()\n",
    "lbl_pred = widgets.Label()\n",
    "btn_run = widgets.Button(description='Classify')\n",
    "\n",
    "def on_click_classify(change):\n",
    "    img = PILImage.create(btn_upload.data[-1])\n",
    "    out_pl.clear_output()\n",
    "    with out_pl: display(img.to_thumb(128, 128))\n",
    "    pred, pred_idx, probs = learn_inf.predict(img)\n",
    "    lbl_pred.value = f'Prediction: {pred}; Probability: {probs[pred_idx]:.04f}'\n",
    "\n",
    "btn_run.on_click(on_click_classify)"
   ]
  },
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       "VBox(children=(Label(value='Select your dog!'), FileUpload(value={}, description='Upload'), Button(description…"
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     },
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   "source": [
    "VBox([widgets.Label('Select your dog!'),\n",
    "      btn_upload, btn_run, out_pl, lbl_pred])"
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