pytorch-road-segmentation-syncrack.ipynb

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warnings\n","warnings.filterwarnings('ignore')\n","\n","import pandas as pd\n","import numpy as np\n","import matplotlib.pyplot as plt\n","import cv2\n","from tqdm.autonotebook import tqdm\n","\n","from sklearn.model_selection import train_test_split\n","\n","from glob import glob\n","import torch\n","import torch.nn as nn\n","from torchvision import transforms as T\n","from torch.utils.data import Dataset, DataLoader\n","import torchvision\n","\n","seed = 42"],"metadata":{"execution":{"iopub.status.busy":"2022-11-28T23:02:57.31408Z","iopub.execute_input":"2022-11-28T23:02:57.315102Z","iopub.status.idle":"2022-11-28T23:03:03.597984Z","shell.execute_reply.started":"2022-11-28T23:02:57.314983Z","shell.execute_reply":"2022-11-28T23:03:03.59693Z"},"trusted":true,"id":"9e0RqR3SWY7K","executionInfo":{"status":"ok","timestamp":1686216774689,"user_tz":-300,"elapsed":8354,"user":{"displayName":"ayaz mhmd","userId":"10465759223706889560"}}},"execution_count":1,"outputs":[]},{"cell_type":"code","source":["device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n","print(f'Currently using \"{device}\" device.')"],"metadata":{"execution":{"iopub.status.busy":"2022-11-28T23:03:03.60008Z","iopub.execute_input":"2022-11-28T23:03:03.600636Z","iopub.status.idle":"2022-11-28T23:03:03.726956Z","shell.execute_reply.started":"2022-11-28T23:03:03.600605Z","shell.execute_reply":"2022-11-28T23:03:03.725687Z"},"trusted":true,"colab":{"base_uri":"https://localhost:8080/"},"id":"N5gX8CZpWY7O","executionInfo":{"status":"ok","timestamp":1686216774690,"user_tz":-300,"elapsed":7,"user":{"displayName":"ayaz mhmd","userId":"10465759223706889560"}},"outputId":"1b50e99b-cb46-4dc1-fb4a-6d826d23a652"},"execution_count":2,"outputs":[{"output_type":"stream","name":"stdout","text":["Currently using \"cpu\" device.\n"]}]},{"cell_type":"code","source":[],"metadata":{"id":"4T5Q0MDoWY7P"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["np.random.seed(seed)\n","torch.manual_seed(seed)\n","torch.cuda.manual_seed(seed)\n","\n","batch_size = 4\n","image_size = 256\n","num_classes = 1\n","epochs = 30\n","path = f'/content/drive/MyDrive/CRACK500-Resized/seg_model.pth'"],"metadata":{"execution":{"iopub.status.busy":"2022-11-28T23:03:03.729061Z","iopub.execute_input":"2022-11-28T23:03:03.729907Z","iopub.status.idle":"2022-11-28T23:03:03.74295Z","shell.execute_reply.started":"2022-11-28T23:03:03.72985Z","shell.execute_reply":"2022-11-28T23:03:03.741826Z"},"trusted":true,"id":"2yu1MjOhWY7P","executionInfo":{"status":"ok","timestamp":1686216774691,"user_tz":-300,"elapsed":5,"user":{"displayName":"ayaz mhmd","userId":"10465759223706889560"}}},"execution_count":3,"outputs":[]},{"cell_type":"code","source":["from google.colab import drive\n","drive.mount('/content/drive',force_remount=True)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"VW_c_UJ7Wh6T","executionInfo":{"status":"ok","timestamp":1686216807183,"user_tz":-300,"elapsed":18819,"user":{"displayName":"ayaz mhmd","userId":"10465759223706889560"}},"outputId":"17f87237-0c7a-43a0-94ff-33d10baffe18"},"execution_count":4,"outputs":[{"output_type":"stream","name":"stdout","text":["Mounted at /content/drive\n"]}]},{"cell_type":"code","source":["import pandas as pd\n","from glob import glob\n","\n","train_path_images = r'/content/drive/MyDrive/CRACK500-Resized/Train/images/*.jpg'\n","train_path_masks = r'/content/drive/MyDrive/CRACK500-Resized/Train/masks/*.png'\n","\n","train_images_paths = sorted(glob(train_path_images))\n","train_masks_paths = sorted(glob(train_path_masks))\n","\n","train = pd.DataFrame({'images': train_images_paths, 'masks': train_masks_paths})\n","\n","train.head()\n"],"metadata":{"_kg_hide-input":true,"execution":{"iopub.status.busy":"2022-11-28T23:03:03.746438Z","iopub.execute_input":"2022-11-28T23:03:03.747552Z","iopub.status.idle":"2022-11-28T23:03:04.944969Z","shell.execute_reply.started":"2022-11-28T23:03:03.74751Z","shell.execute_reply":"2022-11-28T23:03:04.943881Z"},"trusted":true,"colab":{"base_uri":"https://localhost:8080/","height":206},"id":"Msje97rqWY7Q","executionInfo":{"status":"ok","timestamp":1686217062406,"user_tz":-300,"elapsed":487,"user":{"displayName":"ayaz mhmd","userId":"10465759223706889560"}},"outputId":"d7ef2c0d-4c78-4e0d-ce42-f42f004e2e63"},"execution_count":9,"outputs":[{"output_type":"execute_result","data":{"text/plain":["                                              images  \\\n","0  /content/drive/MyDrive/CRACK500-Resized/Train/...   \n","1  /content/drive/MyDrive/CRACK500-Resized/Train/...   \n","2  /content/drive/MyDrive/CRACK500-Resized/Train/...   \n","3  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"],"text/html":["\n","  <div id=\"df-108f155e-ab1e-43a8-ad99-cdfa6680bb17\">\n","    <div class=\"colab-df-container\">\n","      <div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>images</th>\n","      <th>masks</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>/content/drive/MyDrive/CRACK500-Resized/Test/i...</td>\n","      <td>/content/drive/MyDrive/CRACK500-Resized/Test/m...</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>/content/drive/MyDrive/CRACK500-Resized/Test/i...</td>\n","      <td>/content/drive/MyDrive/CRACK500-Resized/Test/m...</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>/content/drive/MyDrive/CRACK500-Resized/Test/i...</td>\n","      <td>/content/drive/MyDrive/CRACK500-Resized/Test/m...</td>\n","    </tr>\n","    <tr>\n","      <th>3</th>\n","      <td>/content/drive/MyDrive/CRACK500-Resized/Test/i...</td>\n","      <td>/content/drive/MyDrive/CRACK500-Resized/Test/m...</td>\n","    </tr>\n","    <tr>\n","      <th>4</th>\n","      <td>/content/drive/MyDrive/CRACK500-Resized/Test/i...</td>\n","      <td>/content/drive/MyDrive/CRACK500-Resized/Test/m...</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-108f155e-ab1e-43a8-ad99-cdfa6680bb17')\"\n","              title=\"Convert this dataframe to an interactive table.\"\n","              style=\"display:none;\">\n","        \n","  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n","       width=\"24px\">\n","    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n","    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n","  </svg>\n","      </button>\n","      \n","  <style>\n","    .colab-df-container {\n","      display:flex;\n","      flex-wrap:wrap;\n","      gap: 12px;\n","    }\n","\n","    .colab-df-convert {\n","      background-color: #E8F0FE;\n","      border: none;\n","      border-radius: 50%;\n","      cursor: pointer;\n","      display: none;\n","      fill: #1967D2;\n","      height: 32px;\n","      padding: 0 0 0 0;\n","      width: 32px;\n","    }\n","\n","    .colab-df-convert:hover {\n","      background-color: #E2EBFA;\n","      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n","      fill: #174EA6;\n","    }\n","\n","    [theme=dark] .colab-df-convert {\n","      background-color: #3B4455;\n","      fill: #D2E3FC;\n","    }\n","\n","    [theme=dark] .colab-df-convert:hover {\n","      background-color: #434B5C;\n","      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n","      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n","      fill: #FFFFFF;\n","    }\n","  </style>\n","\n","      <script>\n","        const buttonEl =\n","          document.querySelector('#df-108f155e-ab1e-43a8-ad99-cdfa6680bb17 button.colab-df-convert');\n","        buttonEl.style.display =\n","          google.colab.kernel.accessAllowed ? 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{len(test)}')"],"metadata":{"execution":{"iopub.status.busy":"2022-11-28T23:03:04.946608Z","iopub.execute_input":"2022-11-28T23:03:04.94698Z","iopub.status.idle":"2022-11-28T23:03:04.95966Z","shell.execute_reply.started":"2022-11-28T23:03:04.946943Z","shell.execute_reply":"2022-11-28T23:03:04.958117Z"},"trusted":true,"colab":{"base_uri":"https://localhost:8080/"},"id":"LfDDJtNGWY7R","executionInfo":{"status":"ok","timestamp":1686217191064,"user_tz":-300,"elapsed":4,"user":{"displayName":"ayaz mhmd","userId":"10465759223706889560"}},"outputId":"c79dc6bd-cc12-4f49-bf75-67fd47bb61e0"},"execution_count":13,"outputs":[{"output_type":"stream","name":"stdout","text":["Train size: 1896, validation size: 50 and test size: 1124\n"]}]},{"cell_type":"code","source":["train_transforms = T.Compose([\n","    T.ToPILImage(),\n","    T.Resize((image_size, image_size)),\n","    # add some color augmentations manually if needed\n","    T.ToTensor()\n","])"],"metadata":{"execution":{"iopub.status.busy":"2022-11-28T23:03:04.961057Z","iopub.execute_input":"2022-11-28T23:03:04.961534Z","iopub.status.idle":"2022-11-28T23:03:04.967722Z","shell.execute_reply.started":"2022-11-28T23:03:04.961455Z","shell.execute_reply":"2022-11-28T23:03:04.966679Z"},"trusted":true,"id":"3WesUme0WY7S","executionInfo":{"status":"ok","timestamp":1686217196526,"user_tz":-300,"elapsed":418,"user":{"displayName":"ayaz mhmd","userId":"10465759223706889560"}}},"execution_count":14,"outputs":[]},{"cell_type":"code","source":["class CrackDataset(Dataset):\n","    def __init__(self, dataset, transforms=train_transforms):\n","        self.dataset = dataset.reset_index(drop=True)\n","        self.transforms = transforms\n","        \n","    def __len__(self):\n","        return len(self.dataset)\n","    \n","    def __getitem__(self, ix):\n","        row = self.dataset.loc[ix].squeeze()\n","        image_path = row['images']\n","        mask_path = row['masks']\n","        \n","        image = cv2.imread(image_path)\n","        image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)\n","        image_tensor = self.transforms(image).float()\n","        \n","        mask = cv2.imread(mask_path)\n","        mask = cv2.cvtColor(mask, cv2.COLOR_BGR2GRAY)\n","        mask = cv2.resize(mask, (image_size, image_size))\n","        _, mask = cv2.threshold(mask, 127, 255, cv2.THRESH_BINARY)\n","        \n","        mask_tensor = torch.as_tensor(mask[None], dtype=torch.float32)\n","        \n","        # mask_tensor /= 255.\n","        \n","        return image_tensor, mask_tensor\n","    \n","    def collate_fn(self, batch):\n","        images, masks = tuple(zip(*batch))\n","        images = [img[None] for img in images]\n","        masks = [msk[None] for msk in masks]\n","        images, masks = [torch.cat(i).to(device) for i in [images, masks]]\n","        return images, masks"],"metadata":{"execution":{"iopub.status.busy":"2022-11-28T23:03:04.969121Z","iopub.execute_input":"2022-11-28T23:03:04.970232Z","iopub.status.idle":"2022-11-28T23:03:04.983018Z","shell.execute_reply.started":"2022-11-28T23:03:04.970193Z","shell.execute_reply":"2022-11-28T23:03:04.982027Z"},"trusted":true,"id":"D0-tDTidWY7S","executionInfo":{"status":"ok","timestamp":1686217202627,"user_tz":-300,"elapsed":395,"user":{"displayName":"ayaz mhmd","userId":"10465759223706889560"}}},"execution_count":15,"outputs":[]},{"cell_type":"code","source":["ds = CrackDataset(train)\n","plt.subplot(121)\n","plt.imshow(ds[1][0].cpu().detach().numpy().transpose(1,2,0))\n","plt.subplot(122)\n","plt.imshow(ds[1][1].cpu().detach().numpy().transpose(1,2,0), cmap='gray')"],"metadata":{"execution":{"iopub.status.busy":"2022-11-28T23:03:04.986619Z","iopub.execute_input":"2022-11-28T23:03:04.986978Z","iopub.status.idle":"2022-11-28T23:03:05.54694Z","shell.execute_reply.started":"2022-11-28T23:03:04.986941Z","shell.execute_reply":"2022-11-28T23:03:05.545839Z"},"trusted":true,"colab":{"base_uri":"https://localhost:8080/","height":309},"id":"WYbyutaiWY7T","executionInfo":{"status":"ok","timestamp":1686217208589,"user_tz":-300,"elapsed":1900,"user":{"displayName":"ayaz mhmd","userId":"10465759223706889560"}},"outputId":"bb785f4d-1d3e-4de8-dd53-43f8d4b80d3a"},"execution_count":16,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<matplotlib.image.AxesImage at 0x7f5adb9d2980>"]},"metadata":{},"execution_count":16},{"output_type":"display_data","data":{"text/plain":["<Figure size 640x480 with 2 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"code","source":["@torch.no_grad()\n","def validate_test_image(model, dataset):\n","    idx = np.random.randint(len(dataset))\n","    dataset = dataset.reset_index(drop=True)\n","    row = dataset.loc[idx].squeeze()\n","    \n","    image = cv2.imread(row['images'])\n","    image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)\n","    image_tensor = train_transforms(image).unsqueeze(0).to(device)\n","    \n","    mask = cv2.imread(row['masks'])\n","    mask = cv2.cvtColor(mask, cv2.COLOR_BGR2GRAY)\n","    mask = cv2.resize(mask, (image_size, image_size))\n","    _, mask = cv2.threshold(mask, 127, 255, cv2.THRESH_BINARY)\n","    \n","    model.eval()\n","    output = model(image_tensor)\n","    output = output['out'][0].cpu().detach().numpy().transpose(1,2,0)\n","    \n","    plt.figure(figsize=(8, 4))\n","    plt.subplot(131)\n","    plt.title('Original image')\n","    plt.imshow(image)\n","    \n","    plt.subplot(132)\n","    plt.title('Original mask')\n","    plt.imshow(mask, cmap='gray')\n","    \n","    plt.subplot(133)\n","    plt.title('Predicted mask')\n","    plt.imshow(output, cmap='gray')\n","    \n","    plt.tight_layout()\n","    plt.show()\n","    plt.pause(0.001)"],"metadata":{"execution":{"iopub.status.busy":"2022-11-28T23:03:05.54804Z","iopub.execute_input":"2022-11-28T23:03:05.549246Z","iopub.status.idle":"2022-11-28T23:03:05.560945Z","shell.execute_reply.started":"2022-11-28T23:03:05.549204Z","shell.execute_reply":"2022-11-28T23:03:05.559951Z"},"trusted":true,"id":"DKM0urhnWY7U","executionInfo":{"status":"ok","timestamp":1686217212430,"user_tz":-300,"elapsed":390,"user":{"displayName":"ayaz mhmd","userId":"10465759223706889560"}}},"execution_count":17,"outputs":[]},{"cell_type":"code","source":["train_dataset = CrackDataset(train)\n","valid_dataset = CrackDataset(valid)\n","\n","train_dataloader = DataLoader(train_dataset, batch_size=batch_size, shuffle=True, collate_fn=train_dataset.collate_fn, drop_last=True)\n","valid_dataloader = DataLoader(valid_dataset, batch_size=batch_size, shuffle=False, collate_fn=valid_dataset.collate_fn, drop_last=True)"],"metadata":{"execution":{"iopub.status.busy":"2022-11-28T23:03:05.564981Z","iopub.execute_input":"2022-11-28T23:03:05.566057Z","iopub.status.idle":"2022-11-28T23:03:05.576758Z","shell.execute_reply.started":"2022-11-28T23:03:05.566017Z","shell.execute_reply":"2022-11-28T23:03:05.575836Z"},"trusted":true,"id":"MqiL0o8yWY7V","executionInfo":{"status":"ok","timestamp":1686217234825,"user_tz":-300,"elapsed":390,"user":{"displayName":"ayaz mhmd","userId":"10465759223706889560"}}},"execution_count":18,"outputs":[]},{"cell_type":"code","source":["from torchvision.models.segmentation.deeplabv3 import DeepLabHead\n","\n","def get_model(output_channels=1, unfreeze=True):\n","    model = torchvision.models.segmentation.deeplabv3_resnet101(pretrained=True, progress=False)\n","    \n","    for param in model.parameters():\n","        param.requires_grad = unfreeze\n","    \n","    model.classifier = DeepLabHead(2048, output_channels)\n","    \n","    return model.to(device)\n","\n","model = get_model()  # set output_channels = 3 if we work with colored masks"],"metadata":{"execution":{"iopub.status.busy":"2022-11-28T23:03:05.578099Z","iopub.execute_input":"2022-11-28T23:03:05.578941Z","iopub.status.idle":"2022-11-28T23:03:23.546306Z","shell.execute_reply.started":"2022-11-28T23:03:05.578901Z","shell.execute_reply":"2022-11-28T23:03:23.545264Z"},"trusted":true,"colab":{"base_uri":"https://localhost:8080/"},"id":"WYsh4a38WY7V","executionInfo":{"status":"ok","timestamp":1686217238225,"user_tz":-300,"elapsed":1720,"user":{"displayName":"ayaz mhmd","userId":"10465759223706889560"}},"outputId":"60856537-2d00-41b9-8524-525c68dfb9bf"},"execution_count":19,"outputs":[{"output_type":"stream","name":"stderr","text":["Downloading: \"https://download.pytorch.org/models/deeplabv3_resnet101_coco-586e9e4e.pth\" to /root/.cache/torch/hub/checkpoints/deeplabv3_resnet101_coco-586e9e4e.pth\n"]}]},{"cell_type":"markdown","source":["URLError: Temporary faliure in name resolution"],"metadata":{"id":"DwMkF9T7WY7W"}},{"cell_type":"code","source":["class EarlyStopping:\n","    def __init__(self, patience=5, min_delta=0, path=path):\n","        self.path = path\n","        self.patience = patience\n","        self.min_delta = min_delta\n","        self.counter = 0\n","        self.best_loss = np.inf\n","        self.early_stop = False\n","        \n","    def __call__(self, val_loss, model=None):\n","        if self.best_loss - val_loss > self.min_delta:\n","            torch.save(model.state_dict(), self.path)\n","            print(f'Model saved to: {self.path}')\n","            self.best_loss = val_loss\n","            self.counter = 0\n","        elif self.best_loss - val_loss < self.min_delta:\n","            self.counter += 1\n","            print(f\"INFO: Early stopping counter {self.counter} of {self.patience}\")\n","            if self.counter >= self.patience:\n","                print('INFO: Early stopping')\n","                self.early_stop = True"],"metadata":{"execution":{"iopub.status.busy":"2022-11-28T23:03:23.547819Z","iopub.execute_input":"2022-11-28T23:03:23.548788Z","iopub.status.idle":"2022-11-28T23:03:23.558391Z","shell.execute_reply.started":"2022-11-28T23:03:23.548745Z","shell.execute_reply":"2022-11-28T23:03:23.557386Z"},"trusted":true,"id":"vI_alhd7WY7Y","executionInfo":{"status":"ok","timestamp":1686217244517,"user_tz":-300,"elapsed":715,"user":{"displayName":"ayaz mhmd","userId":"10465759223706889560"}}},"execution_count":20,"outputs":[]},{"cell_type":"code","source":["criterion = nn.MSELoss()\n","optimizer = torch.optim.Adam(model.parameters(), lr=1e-4)  # if unfreeze=True -> 1e-4, 1e-5, so not to ruin good init w\n","scheduler = torch.optim.lr_scheduler.ReduceLROnPlateau(optimizer, patience=3, min_lr=1e-6, factor=0.1)\n","early = EarlyStopping()"],"metadata":{"execution":{"iopub.status.busy":"2022-11-28T23:03:23.560762Z","iopub.execute_input":"2022-11-28T23:03:23.561767Z","iopub.status.idle":"2022-11-28T23:03:23.57794Z","shell.execute_reply.started":"2022-11-28T23:03:23.561729Z","shell.execute_reply":"2022-11-28T23:03:23.576851Z"},"trusted":true,"id":"qfMybyKbWY7Y","executionInfo":{"status":"ok","timestamp":1686217249484,"user_tz":-300,"elapsed":419,"user":{"displayName":"ayaz mhmd","userId":"10465759223706889560"}}},"execution_count":21,"outputs":[]},{"cell_type":"code","source":["def train_one_batch(batch, model, criterion, optimizer):\n","    images, masks = batch\n","    optimizer.zero_grad()\n","    output = model(images)\n","    loss = criterion(output['out'], masks)\n","    loss.backward()\n","    optimizer.step()\n","    \n","    return loss.item()\n","\n","@torch.no_grad()\n","def validate_one_batch(batch, model, criterion):\n","    images, masks = batch\n","    output = model(images)\n","    loss = criterion(output['out'], masks)\n","    return loss.item()"],"metadata":{"execution":{"iopub.status.busy":"2022-11-28T23:03:23.579999Z","iopub.execute_input":"2022-11-28T23:03:23.580308Z","iopub.status.idle":"2022-11-28T23:03:23.588291Z","shell.execute_reply.started":"2022-11-28T23:03:23.580256Z","shell.execute_reply":"2022-11-28T23:03:23.587218Z"},"trusted":true,"id":"_Bz-ynQDWY7Z","executionInfo":{"status":"ok","timestamp":1686217251152,"user_tz":-300,"elapsed":1,"user":{"displayName":"ayaz mhmd","userId":"10465759223706889560"}}},"execution_count":22,"outputs":[]},{"cell_type":"code","source":["train_losses, valid_losses = [], []\n","\n","for epoch in range(epochs):\n","\n","    print(f'Epoch {epoch + 1}/{epochs}')\n","    epoch_train_losses, epoch_valid_losses = [], []\n","    \n","    model.train()\n","    for _, batch in enumerate(tqdm(train_dataloader, leave=False)):\n","        batch_train_loss = train_one_batch(batch, model, criterion, optimizer)\n","        epoch_train_losses.append(batch_train_loss)\n","    epoch_train_loss = np.array(epoch_train_losses).mean()\n","    train_losses.append(epoch_train_loss)\n","\n","    print(f'Train loss: {epoch_train_loss:.4f}.')\n","    \n","    model.eval()\n","    for i, batch in enumerate(tqdm(valid_dataloader, leave=False)):\n","        batch_valid_loss = validate_one_batch(batch, model, criterion)\n","        epoch_valid_losses.append(batch_valid_loss)\n","    epoch_valid_loss = np.array(epoch_valid_losses).mean()\n","    valid_losses.append(epoch_valid_loss)\n","    print(f'Valid loss: {epoch_valid_loss:.4f}.')\n","    print('-'*50)    \n","    \n","    validate_test_image(model, test)\n","    \n","    scheduler.step(epoch_valid_loss)\n","    early(epoch_valid_loss, model=model)\n","    if early.early_stop:\n","        print(f'Validation loss did not improve for {early.patience} epochs. Training stopped.')\n","        model.load_state_dict(torch.load(path))\n","        break"],"metadata":{"execution":{"iopub.status.busy":"2022-11-29T00:36:54.834619Z","iopub.execute_input":"2022-11-29T00:36:54.839853Z","iopub.status.idle":"2022-11-29T00:36:55.027318Z","shell.execute_reply.started":"2022-11-29T00:36:54.839668Z","shell.execute_reply":"2022-11-29T00:36:55.025431Z"},"trusted":true,"colab":{"base_uri":"https://localhost:8080/","height":483,"referenced_widgets":["09496d26e540448981079119aec8a4d5","ef286356ad0a4bde93a8a18d20418f3b","6894b3ceff3745a18683b056e21f8a5f","da5175e79daf4feeb7741c73b0b227f8","15db16343cca49059b6ac029d8e30032","117dca36973a4b4d9bf3aa3c202a6755","c75cd12fbe5b4a7c85ea8fb1cf783f6b","2dae51cc004841a1b46c28736d012612","010f483ca98d4e37b48869e469e1f704","641d86418ff24c659292f1c49a4c424a","ed40d7e8cd4045038786a2ef977b3b6b"]},"id":"ZovgBZQUWY7a","executionInfo":{"status":"error","timestamp":1686221897204,"user_tz":-300,"elapsed":4640634,"user":{"displayName":"ayaz mhmd","userId":"10465759223706889560"}},"outputId":"69f7929c-3073-47a9-f66b-4d0f5feea049"},"execution_count":23,"outputs":[{"output_type":"stream","name":"stdout","text":["Epoch 1/30\n"]},{"output_type":"display_data","data":{"text/plain":["  0%|          | 0/474 [00:00<?, ?it/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"09496d26e540448981079119aec8a4d5"}},"metadata":{}},{"output_type":"error","ename":"KeyboardInterrupt","evalue":"ignored","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)","\u001b[0;32m<ipython-input-23-ef23fdfcb7ff>\u001b[0m in \u001b[0;36m<cell line: 3>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      8\u001b[0m     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\u001b[0mmodel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mimages\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m     \u001b[0mloss\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcriterion\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0moutput\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'out'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmasks\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 6\u001b[0;31m     \u001b[0mloss\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbackward\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      7\u001b[0m     \u001b[0moptimizer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstep\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      8\u001b[0m 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)\n","\u001b[0;32m/usr/local/lib/python3.10/dist-packages/torch/autograd/__init__.py\u001b[0m in \u001b[0;36mbackward\u001b[0;34m(tensors, grad_tensors, retain_graph, create_graph, grad_variables, inputs)\u001b[0m\n\u001b[1;32m    198\u001b[0m     \u001b[0;31m# some Python versions print out the first line of a multi-line function\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    199\u001b[0m     \u001b[0;31m# calls in the traceback and some print out the last line\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 200\u001b[0;31m     Variable._execution_engine.run_backward(  # Calls into the C++ engine to run the backward pass\n\u001b[0m\u001b[1;32m    201\u001b[0m         \u001b[0mtensors\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mgrad_tensors_\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mretain_graph\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcreate_graph\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minputs\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    202\u001b[0m         allow_unreachable=True, accumulate_grad=True)  # Calls into the C++ engine to run the backward pass\n","\u001b[0;31mKeyboardInterrupt\u001b[0m: "]}]},{"cell_type":"code","source":[],"metadata":{"id":"x1k2uU4AYWqQ"},"execution_count":null,"outputs":[]}]}