app.ipynb

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        "# Convolutional Neural Networks\n",
        "\n",
        "## Project: Write an Algorithm for Landmark Classification\n",
        "\n",
        "### A simple app\n",
        "\n",
        "In this notebook we build a very simple app that uses our exported model.\n",
        "\n",
        "> <img src=\"static_images/icons/noun-info-2558213.png\" alt=\"?\" style=\"width:25px\"/> Note how we are not importing anything from our source code (we do not use any module from the ``src`` directory). This is because the exported model, differently from the model weights, is a standalone serialization of our model and therefore it does not need anything else. You can ship that file to anybody, and as long as they can import ``torch``, they will be able to use your model. This is very important for releasing pytorch models to production.\n",
        "\n",
        "### Test your app\n",
        "Go to a search engine for images (like Google Images) and search for images of some of the landmarks, like the Eiffel Tower, the Golden Gate Bridge, Machu Picchu and so on. Save a few examples locally, then upload them to your app to see how your model behaves!\n",
        "\n",
        "The app will show the top 5 classes that the model think are most relevant for the picture you have uploaded"
      ],
      "id": "0cvQFSQmvQjb"
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    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "k4fe0c4ivi5u",
        "outputId": "ee8d36fa-93d8-43a4-87d1-f427a81a18c1"
      },
      "id": "k4fe0c4ivi5u",
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import os\n",
        "os.chdir(\"/content/drive/MyDrive/cnn_proj_3/\")"
      ],
      "metadata": {
        "id": "-3RxhdXRvt-G"
      },
      "id": "-3RxhdXRvt-G",
      "execution_count": 3,
      "outputs": []
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              "VBox(children=(Label(value='Please upload a picture of a landmark'), FileUpload(value={}, description='Upload'…"
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          "text": [
            "code/__torch__/torchvision/transforms/functional.py:188: UserWarning: The default value of the antialias parameter of all the resizing transforms (Resize(), RandomResizedCrop(), etc.) will change from None to True in v0.17, in order to be consistent across the PIL and Tensor backends. To suppress this warning, directly pass antialias=True (recommended, future default), antialias=None (current default, which means False for Tensors and True for PIL), or antialias=False (only works on Tensors - PIL will still use antialiasing). This also applies if you are using the inference transforms from the models weights: update the call to weights.transforms(antialias=True).\n"
          ]
        }
      ],
      "source": [
        "from ipywidgets import VBox, Button, FileUpload, Output, Label\n",
        "from PIL import Image\n",
        "from IPython.display import display\n",
        "import io\n",
        "import numpy as np\n",
        "import torchvision\n",
        "import torchvision.transforms as T\n",
        "import torch\n",
        "\n",
        "# Decide which model you want to use among the ones exported\n",
        "learn_inf = torch.jit.load(\"/content/drive/MyDrive/cnn_proj_3/checkpoints/transfer_exported.pt\")\n",
        "\n",
        "def on_click_classify(change):\n",
        "\n",
        "    # Load image that has been uploaded\n",
        "    fn = io.BytesIO(btn_upload.data[-1])\n",
        "\n",
        "    img = Image.open(fn)\n",
        "    img.load()\n",
        "\n",
        "    # Let's clear the previous output (if any)\n",
        "    out_pl.clear_output()\n",
        "\n",
        "    # Display the image\n",
        "    with out_pl:\n",
        "\n",
        "        ratio = img.size[0] / img.size[1]\n",
        "        c = img.copy()\n",
        "        c.thumbnail([ratio * 200, 200])\n",
        "        display(c)\n",
        "\n",
        "    # Transform to tensor\n",
        "    timg = T.ToTensor()(img).unsqueeze_(0)\n",
        "\n",
        "    # Calling the model\n",
        "    softmax = learn_inf(timg).data.cpu().numpy().squeeze()\n",
        "\n",
        "    # Get the indexes of the classes ordered by softmax\n",
        "    # (larger first)\n",
        "    idxs = np.argsort(softmax)[::-1]\n",
        "\n",
        "    # Loop over the classes with the largest softmax\n",
        "    for i in range(5):\n",
        "        # Get softmax value\n",
        "        p = softmax[idxs[i]]\n",
        "\n",
        "        # Get class name\n",
        "        landmark_name = learn_inf.class_names[idxs[i]]\n",
        "\n",
        "        labels[i].value = f\"{landmark_name} (prob: {p:.2f})\"\n",
        "\n",
        "\n",
        "# Putting back btn_upload to a widget for next cell\n",
        "btn_upload = FileUpload()\n",
        "\n",
        "btn_run = Button(description=\"Classify\")\n",
        "btn_run.on_click(on_click_classify)\n",
        "\n",
        "labels = []\n",
        "for _ in range(5):\n",
        "    labels.append(Label())\n",
        "\n",
        "out_pl = Output()\n",
        "out_pl.clear_output()\n",
        "\n",
        "wgs = [Label(\"Please upload a picture of a landmark\"), btn_upload, btn_run, out_pl]\n",
        "wgs.extend(labels)\n",
        "\n",
        "VBox(wgs)"
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      "source": [
        "## (optional) Standalone app or web app\n",
        "\n",
        "You can run this notebook as a standalone app on your computer by following these steps:\n",
        "\n",
        "1. Download this notebook in a directory on your machine\n",
        "2. Download the model export (for example, ``checkpoints/transfer_exported.pt``) in a subdirectory called ``checkpoints`` within the directory where you save the app.ipynb notebook\n",
        "3. Install voila if you don't have it already (``pip install voila``)\n",
        "4. Run your app: ``voila app.ipynb --show_tracebacks=True``\n",
        "5. Customize your notebook to make your app prettier and rerun voila\n",
        "\n",
        "You can also deploy this app as a website using Binder: https://voila.readthedocs.io/en/stable/deploy.html#deployment-on-binder"
      ],
      "id": "LA7DBoqGvQjr"
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2Z_ViMcuvQjs"
      },
      "source": [
        "# Create your submission archive\n",
        "\n",
        "Now that you are done with your project, please run the following cell. It will generate a file containing all the code you have written, as well as the notebooks. Please submit that file to complete your project"
      ],
      "id": "2Z_ViMcuvQjs"
    },
    {
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        {
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          "name": "stdout",
          "text": [
            "executing: jupyter nbconvert --to html cnn_from_scratch.ipynb\n",
            "[NbConvertApp] Converting notebook cnn_from_scratch.ipynb to html\n",
            "[NbConvertApp] Writing 621681 bytes to cnn_from_scratch.html\n",
            "executing: jupyter nbconvert --to html app.ipynb\n",
            "[NbConvertApp] Converting notebook app.ipynb to html\n",
            "/usr/local/lib/python3.10/dist-packages/nbformat/__init__.py:93: MissingIDFieldWarning: Code cell is missing an id field, this will become a hard error in future nbformat versions. You may want to use `normalize()` on your notebooks before validations (available since nbformat 5.1.4). Previous versions of nbformat are fixing this issue transparently, and will stop doing so in the future.\n",
            "  validate(nb)\n",
            "[NbConvertApp] Writing 588508 bytes to app.html\n",
            "executing: jupyter nbconvert --to html transfer_learning.ipynb\n",
            "[NbConvertApp] Converting notebook transfer_learning.ipynb to html\n",
            "[NbConvertApp] Writing 634089 bytes to transfer_learning.html\n",
            "Adding files to submission_2023-10-21T15h01m.tar.gz\n",
            "src/helpers.py\n",
            "src/create_submit_pkg.py\n",
            "src/__init__.py\n",
            "src/data.py\n",
            "src/model.py\n",
            "src/optimization.py\n",
            "src/train.py\n",
            "src/predictor.py\n",
            "src/transfer.py\n",
            "cnn_from_scratch.ipynb\n",
            "app.ipynb\n",
            "transfer_learning.ipynb\n",
            "cnn_from_scratch.html\n",
            "app.html\n",
            "transfer_learning.html\n",
            "\n",
            "----------------------------------------------------------------\n",
            "Done. Please submit the file submission_2023-10-21T15h01m.tar.gz\n",
            "----------------------------------------------------------------\n"
          ]
        }
      ],
      "source": [
        "!python src/create_submit_pkg.py"
      ],
      "id": "3y2D9e8BvQjt"
    },
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