{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.10.12","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"gpu","dataSources":[{"sourceId":10338,"databundleVersionId":862042,"sourceType":"competition"}],"dockerImageVersionId":30823,"isInternetEnabled":true,"language":"python","sourceType":"notebook","isGpuEnabled":true}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load\n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the read-only \"../input/\" directory\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n    for filename in filenames:\n        os.path.join(dirname, filename)\n\n# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true,"execution":{"iopub.status.busy":"2025-05-02T14:55:36.470556Z","iopub.execute_input":"2025-05-02T14:55:36.471034Z","iopub.status.idle":"2025-05-02T14:56:48.460289Z","shell.execute_reply.started":"2025-05-02T14:55:36.471002Z","shell.execute_reply":"2025-05-02T14:56:48.459537Z"}},"outputs":[],"execution_count":2},{"cell_type":"code","source":"import cv2 as cv\nimport numpy as np\nfrom matplotlib import pyplot as plt\nimport pandas as pd\nimport pydicom\nfrom skimage.transform import resize\nimport matplotlib.patches as patches\nimport tensorflow as tf\nimport cv2\nimport numpy as np\nfrom skimage.feature import hog\nimport os\nimport pandas as pd\nimport pydicom\nimport tensorflow as tf\nfrom tensorflow.keras.models import Sequential\nfrom tensorflow.keras.layers import Dense, Dropout\nfrom tensorflow.keras.optimizers import Adam\nfrom sklearn.metrics import accuracy_score, classification_report","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-05-02T15:06:28.737006Z","iopub.execute_input":"2025-05-02T15:06:28.737316Z","iopub.status.idle":"2025-05-02T15:06:29.186791Z","shell.execute_reply.started":"2025-05-02T15:06:28.737295Z","shell.execute_reply":"2025-05-02T15:06:29.185861Z"}},"outputs":[],"execution_count":19},{"cell_type":"code","source":"train_label = pd.read_csv('/kaggle/input/rsna-pneumonia-detection-challenge/stage_2_train_labels.csv')\ntrain_label.shape","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-05-02T15:31:54.433133Z","iopub.execute_input":"2025-05-02T15:31:54.433459Z","iopub.status.idle":"2025-05-02T15:31:54.467291Z","shell.execute_reply.started":"2025-05-02T15:31:54.433433Z","shell.execute_reply":"2025-05-02T15:31:54.466458Z"}},"outputs":[{"execution_count":22,"output_type":"execute_result","data":{"text/plain":"(30227, 6)"},"metadata":{}}],"execution_count":22},{"cell_type":"code","source":"train_label","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-05-02T15:32:31.933513Z","iopub.execute_input":"2025-05-02T15:32:31.933826Z","iopub.status.idle":"2025-05-02T15:32:31.94938Z","shell.execute_reply.started":"2025-05-02T15:32:31.9338Z","shell.execute_reply":"2025-05-02T15:32:31.948613Z"}},"outputs":[{"execution_count":24,"output_type":"execute_result","data":{"text/plain":"                                  patientId      x      y  width  height  \\\n0      0004cfab-14fd-4e49-80ba-63a80b6bddd6    NaN    NaN    NaN     NaN   \n1      00313ee0-9eaa-42f4-b0ab-c148ed3241cd    NaN    NaN    NaN     NaN   \n2      00322d4d-1c29-4943-afc9-b6754be640eb    NaN    NaN    NaN     NaN   \n3      003d8fa0-6bf1-40ed-b54c-ac657f8495c5    NaN    NaN    NaN     NaN   \n4      00436515-870c-4b36-a041-de91049b9ab4  264.0  152.0  213.0   379.0   \n...                                     ...    ...    ...    ...     ...   \n30222  c1ec14ff-f6d7-4b38-b0cb-fe07041cbdc8  185.0  298.0  228.0   379.0   \n30223  c1edf42b-5958-47ff-a1e7-4f23d99583ba    NaN    NaN    NaN     NaN   \n30224  c1f6b555-2eb1-4231-98f6-50a963976431    NaN    NaN    NaN     NaN   \n30225  c1f7889a-9ea9-4acb-b64c-b737c929599a  570.0  393.0  261.0   345.0   \n30226  c1f7889a-9ea9-4acb-b64c-b737c929599a  233.0  424.0  201.0   356.0   \n\n       Target  \n0           0  \n1           0  \n2           0  \n3           0  \n4           1  \n...       ...  \n30222       1  \n30223       0  \n30224       0  \n30225       1  \n30226       1  \n\n[30227 rows x 6 columns]","text/html":"<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>patientId</th>\n      <th>x</th>\n      <th>y</th>\n      <th>width</th>\n      <th>height</th>\n      <th>Target</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>0004cfab-14fd-4e49-80ba-63a80b6bddd6</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>00313ee0-9eaa-42f4-b0ab-c148ed3241cd</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>00322d4d-1c29-4943-afc9-b6754be640eb</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>003d8fa0-6bf1-40ed-b54c-ac657f8495c5</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>00436515-870c-4b36-a041-de91049b9ab4</td>\n      <td>264.0</td>\n      <td>152.0</td>\n      <td>213.0</td>\n      <td>379.0</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>30222</th>\n      <td>c1ec14ff-f6d7-4b38-b0cb-fe07041cbdc8</td>\n      <td>185.0</td>\n      <td>298.0</td>\n      <td>228.0</td>\n      <td>379.0</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>30223</th>\n      <td>c1edf42b-5958-47ff-a1e7-4f23d99583ba</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>30224</th>\n      <td>c1f6b555-2eb1-4231-98f6-50a963976431</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>NaN</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>30225</th>\n      <td>c1f7889a-9ea9-4acb-b64c-b737c929599a</td>\n      <td>570.0</td>\n      <td>393.0</td>\n      <td>261.0</td>\n      <td>345.0</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>30226</th>\n      <td>c1f7889a-9ea9-4acb-b64c-b737c929599a</td>\n      <td>233.0</td>\n      <td>424.0</td>\n      <td>201.0</td>\n      <td>356.0</td>\n      <td>1</td>\n    </tr>\n  </tbody>\n</table>\n<p>30227 rows × 6 columns</p>\n</div>"},"metadata":{}}],"execution_count":24},{"cell_type":"markdown","source":"# Formatting Data","metadata":{}},{"cell_type":"code","source":"# input_size = 244\n\n# def format_image(img, box):\n#     height, width = img.shape \n#     max_size = max(height, width)\n#     r = max_size / input_size\n#     new_width = int(width / r)\n#     new_height = int(height / r)\n#     new_size = (new_width, new_height)\n#     resized = cv.resize(img, new_size, interpolation= cv.INTER_LINEAR)\n#     new_image = np.zeros((input_size, input_size), dtype=np.uint8)\n#     new_image[0:new_height, 0:new_width] = resized\n\n#     x, y, w, h = (box[0], box[1], box[2], box[3]) if box[0] else (0.0,0.0,0.0,0.0)\n#     new_box = [int((x)/ r), int((y)/ r), int(w/ r), int(h/ r)] if box[0] else [0.0,0.0,0.0,0.0]\n\n#     return new_image, new_box","metadata":{"trusted":true,"jupyter":{"source_hidden":true}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"**Original image**","metadata":{}},{"cell_type":"code","source":"dcm_path = '/kaggle/input/rsna-pneumonia-detection-challenge/stage_2_train_images/00436515-870c-4b36-a041-de91049b9ab4.dcm'\n\nimage_array = pydicom.dcmread(dcm_path).pixel_array\n\nprint(image_array.shape)\n\nfig, ax = plt.subplots(1, 1, figsize=(6, 6))\nax.imshow(image_array, cmap='bone')         \n\n\nrect = patches.Rectangle((264.0, 152.0), 213.0, 379.0, \n                         edgecolor='r', facecolor='none', linewidth=2)\nax.add_patch(rect)                        \n\nplt.show()    ","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-05-02T15:37:42.998766Z","iopub.execute_input":"2025-05-02T15:37:42.99914Z","iopub.status.idle":"2025-05-02T15:37:43.346452Z","shell.execute_reply.started":"2025-05-02T15:37:42.999111Z","shell.execute_reply":"2025-05-02T15:37:43.345615Z"}},"outputs":[{"name":"stdout","text":"(1024, 1024)\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"<Figure size 600x600 with 1 Axes>","image/png":"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\n"},"metadata":{}}],"execution_count":26},{"cell_type":"code","source":"def preprocess_image(img, box=None):\n    # Convert to grayscale if not already\n    if len(img.shape) == 3:\n        img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)\n    \n    height, width = img.shape \n    input_size = 244\n    max_size = max(height, width)\n    r = max_size / input_size\n    new_width = int(width / r)\n    new_height = int(height / r)\n    new_size = (new_width, new_height)\n    resized = cv2.resize(img, new_size, interpolation=cv2.INTER_LINEAR)\n    new_image = np.zeros((input_size, input_size), dtype=np.uint8)\n    new_image[0:new_height, 0:new_width] = resized\n\n    # Handle bounding box if provided\n    new_box = [0, 0, 0, 0]\n    if box is not None and len(box) == 4:\n        x, y, w, h = box\n        new_box = [int(x/r), int(y/r), int(w/r), int(h/r)]\n\n    # Denoising\n    img = cv2.GaussianBlur(new_image, (3, 3), 0)\n\n    # Contrast enhancement\n    clahe = cv2.createCLAHE(clipLimit=2.0)\n    img = clahe.apply(img)\n\n    # Thresholding\n    _, thresh = cv2.threshold(img, 0, 255, cv2.THRESH_OTSU)\n\n    # Morphological operations\n    kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (5, 5))\n    morphed = cv2.morphologyEx(thresh, cv2.MORPH_CLOSE, kernel)\n\n    return morphed, new_box","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-05-02T14:57:03.68219Z","iopub.execute_input":"2025-05-02T14:57:03.682476Z","iopub.status.idle":"2025-05-02T14:57:03.689116Z","shell.execute_reply.started":"2025-05-02T14:57:03.682445Z","shell.execute_reply":"2025-05-02T14:57:03.688281Z"}},"outputs":[],"execution_count":5},{"cell_type":"markdown","source":"**Image after preprocessing**","metadata":{}},{"cell_type":"code","source":"\nmorphed , new_box =preprocess_image(image_array,[264.0, 152.0, 213.0, 379.0])\nprint(image_array.shape)\n\nfig, ax = plt.subplots(1, 1, figsize=(6, 6))\nax.imshow(morphed, cmap='bone')         \n\n\nrect = patches.Rectangle((new_box[0], new_box[1]),new_box[2], new_box[3], \n                         edgecolor='r', facecolor='none', linewidth=2)\nax.add_patch(rect)                        \n\nplt.show()    ","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-05-02T15:42:58.49563Z","iopub.execute_input":"2025-05-02T15:42:58.495975Z","iopub.status.idle":"2025-05-02T15:42:58.735069Z","shell.execute_reply.started":"2025-05-02T15:42:58.495949Z","shell.execute_reply":"2025-05-02T15:42:58.734189Z"}},"outputs":[{"name":"stdout","text":"(1024, 1024)\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"<Figure size 600x600 with 1 Axes>","image/png":"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\n"},"metadata":{}}],"execution_count":28},{"cell_type":"code","source":"","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"def segment_rois(img):\n    edges = cv2.Canny(img, 20, 50)\n    contours, _ = cv2.findContours(edges, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)\n\n    masks = np.zeros_like(img)\n    for cnt in contours:\n        area = cv2.contourArea(cnt)\n        if area > 100:  # ignore small noise\n            cv2.drawContours(masks, [cnt], -1, 255, -1)\n    return masks","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-05-02T15:53:44.525101Z","iopub.execute_input":"2025-05-02T15:53:44.525422Z","iopub.status.idle":"2025-05-02T15:53:44.530137Z","shell.execute_reply.started":"2025-05-02T15:53:44.52539Z","shell.execute_reply":"2025-05-02T15:53:44.529233Z"}},"outputs":[],"execution_count":52},{"cell_type":"code","source":"roi_masks = segment_rois(image_array)\n\n# Display original and result\nplt.figure(figsize=(10,5))\nplt.subplot(121), plt.imshow(image_array, cmap='gray'), plt.title('Original Image')\nplt.subplot(122), plt.imshow(roi_masks, cmap='gray'), plt.title('ROI Masks')\nplt.show()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-05-02T15:53:47.225355Z","iopub.execute_input":"2025-05-02T15:53:47.225635Z","iopub.status.idle":"2025-05-02T15:53:47.704034Z","shell.execute_reply.started":"2025-05-02T15:53:47.225615Z","shell.execute_reply":"2025-05-02T15:53:47.70324Z"}},"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1000x500 with 2 Axes>","image/png":"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\n"},"metadata":{}}],"execution_count":53},{"cell_type":"markdown","source":"**output of segmentation**","metadata":{}},{"cell_type":"code","source":"","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"def extract_features(img, mask=None):\n    if mask is not None:\n        img = cv2.bitwise_and(img, img, mask=mask)\n\n    hog_feat = hog(img, pixels_per_cell=(16, 16), cells_per_block=(2, 2))\n    hist = cv2.calcHist([img], [0], None, [32], [0, 256]).flatten()\n    edged = cv2.Canny(img, 100, 200)\n    edge_density = np.sum(edged) / np.prod(edged.shape)\n\n    return np.concatenate([hog_feat, hist, [edge_density]])","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-05-02T14:57:08.610905Z","iopub.execute_input":"2025-05-02T14:57:08.61133Z","iopub.status.idle":"2025-05-02T14:57:08.616926Z","shell.execute_reply.started":"2025-05-02T14:57:08.611294Z","shell.execute_reply":"2025-05-02T14:57:08.615771Z"}},"outputs":[],"execution_count":7},{"cell_type":"code","source":"def create_tf_dataset(dicom_dir, label_csv, batch_size=32):\n    # Read label CSV\n    labels_df = pd.read_csv(label_csv)\n    \n    # Prepare lists for images, labels, and boxes\n    image_paths = []\n    labels = []\n    boxes = []\n    \n    for _, row in labels_df.iterrows():\n        patient_id = row['patientId']\n        target = row['Target']\n        dicom_path = os.path.join(dicom_dir, f\"{patient_id}.dcm\")\n        \n        if os.path.exists(dicom_path):\n            image_paths.append(dicom_path)\n            labels.append(target)\n            box = [row['x'], row['y'], row['width'], row['height']]\n            if target == 0 or not all(np.isfinite(box)):\n                box = [0.0, 0.0, 0.0, 0.0]  # Use dummy box for negative/NaN cases\n            boxes.append(box)\n    \n    # Convert to tensors\n    image_paths = tf.constant(image_paths)\n    labels = tf.constant(labels, dtype=tf.float32)\n    boxes = tf.constant(boxes, dtype=tf.float32)\n    \n    # Create dataset\n    dataset = tf.data.Dataset.from_tensor_slices((image_paths, labels, boxes))\n    \n    # Split dataset (60% train, 20% val, 20% test)\n    dataset_size = len(image_paths)\n    train_size = int(0.6 * dataset_size)\n    val_size = int(0.2 * dataset_size)\n    test_size = dataset_size - train_size - val_size\n    \n    # Shuffle dataset\n    dataset = dataset.shuffle(buffer_size=dataset_size, seed=42)\n    \n    # Split into train, val, test\n    train_dataset = dataset.take(train_size)\n    val_dataset = dataset.skip(train_size).take(val_size)\n    test_dataset = dataset.skip(train_size + val_size)\n    \n    # Define processing function\n    def process_data(image_path, label, box):\n        # Read DICOM file\n        dicom = pydicom.dcmread(image_path.numpy().decode('utf-8'))\n        img = dicom.pixel_array\n        # Normalize to 8-bit\n        if img.dtype != np.uint8:\n            img = cv2.normalize(img, None, 0, 255, cv2.NORM_MINMAX).astype(np.uint8)\n        \n        # Preprocess and extract features\n        preprocessed_img, _ = preprocess_image(img, box.numpy())\n        mask = segment_rois(preprocessed_img)\n        features = extract_features(preprocessed_img, mask)\n        \n        return features, label\n    \n    # Wrapper for tf.py_function\n    def tf_process_data(image_path, label, box):\n        features, label = tf.py_function(\n            func=process_data,\n            inp=[image_path, label, box],\n            Tout=[tf.float32, tf.float32]\n        )\n        features.set_shape([None])  # Set shape for features (dynamic size)\n        label.set_shape([])  # Scalar label\n        return features, label\n    \n    # Map processing function and configure datasets\n    train_dataset = train_dataset.map(tf_process_data, num_parallel_calls=tf.data.AUTOTUNE)\n    val_dataset = val_dataset.map(tf_process_data, num_parallel_calls=tf.data.AUTOTUNE)\n    test_dataset = test_dataset.map(tf_process_data, num_parallel_calls=tf.data.AUTOTUNE)\n    \n    # Batch and prefetch\n    train_dataset = train_dataset.batch(batch_size).prefetch(tf.data.AUTOTUNE)\n    val_dataset = val_dataset.batch(batch_size).prefetch(tf.data.AUTOTUNE)\n    test_dataset = test_dataset.batch(batch_size).prefetch(tf.data.AUTOTUNE)\n    \n    return train_dataset, val_dataset, test_dataset, test_size","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-05-02T14:57:29.526512Z","iopub.execute_input":"2025-05-02T14:57:29.526836Z","iopub.status.idle":"2025-05-02T14:57:29.536843Z","shell.execute_reply.started":"2025-05-02T14:57:29.526812Z","shell.execute_reply":"2025-05-02T14:57:29.535793Z"}},"outputs":[],"execution_count":9},{"cell_type":"code","source":"class ImageProcessingPipeline:\n    def __init__(self, input_dim):\n        self.model = self._build_nn_model(input_dim)\n        \n    def _build_nn_model(self, input_dim):\n        model = Sequential([\n            Dense(512, activation='relu', input_dim=input_dim),\n            Dropout(0.3),\n            Dense(256, activation='relu'),\n            Dropout(0.3),\n            Dense(128, activation='relu'),\n            Dropout(0.3),\n            Dense(1, activation='sigmoid')\n        ])\n        model.compile(optimizer=Adam(learning_rate=0.001), \n                     loss='binary_crossentropy', \n                     metrics=['accuracy'])\n        return model\n    def build_classifier_head(inputs):\n        return tf.keras.layers.Dense(CLASSES, activation='softmax', name = 'classifier_head')(inputs)\n\n    def build_regressor_head(inputs):\n        return tf.keras.layers.Dense(units = 4, name = 'regressor_head')(inputs)\n    \n    def process_image(self, img, box=None):\n        # Preprocess\n        preprocessed_img, new_box = preprocess_image(img, box)\n        \n        # Segment\n        mask = segment_rois(preprocessed_img)\n        \n        # Extract features\n        features = extract_features(preprocessed_img, mask)\n        \n        return features\n    \n    def fit(self, train_dataset, val_dataset, epochs=50):\n        # Train model\n        self.model.fit(\n            train_dataset,\n            validation_data=val_dataset,\n            epochs=epochs,\n            verbose=1\n        )\n        \n        return self\n    \n    def evaluate(self, test_dataset):\n        # Evaluate\n        loss, accuracy = self.model.evaluate(test_dataset, verbose=0)\n        print(f\"Test Accuracy: {accuracy:.4f}\")\n        \n        # Detailed classification report\n        y_true = []\n        y_pred = []\n        for features, labels in test_dataset:\n            preds = (self.model.predict(features, verbose=0) > 0.5).astype(int)\n            y_true.extend(labels.numpy())\n            y_pred.extend(preds.flatten())\n        \n        print(\"\\nClassification Report:\\n\", classification_report(y_true, y_pred))\n        \n        return accuracy\n\n\n    def predict(self, images, boxes=None):\n        if boxes is None:\n            boxes = [None] * len(images)\n            \n        features_list = []\n        for img, box in zip(images, boxes):\n            features = self.process_image(img, box)\n            features_list.append(features)\n        \n        X = np.array(features_list)\n        return (self.model.predict(X) > 0.5).astype(int)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-05-02T14:59:23.975158Z","iopub.execute_input":"2025-05-02T14:59:23.975445Z","iopub.status.idle":"2025-05-02T14:59:23.983597Z","shell.execute_reply.started":"2025-05-02T14:59:23.975424Z","shell.execute_reply":"2025-05-02T14:59:23.982653Z"}},"outputs":[],"execution_count":13},{"cell_type":"code","source":"dicom_dir = '/kaggle/input/rsna-pneumonia-detection-challenge/stage_2_train_images/'\nlabel_csv = '/kaggle/input/rsna-pneumonia-detection-challenge/stage_2_train_labels.csv'\n\nbatch_size = 32\ntrain_dataset, val_dataset, test_dataset, test_size = create_tf_dataset(dicom_dir, label_csv, batch_size)\n\n# Determine input dimension\nsample_img = pydicom.dcmread(os.path.join(dicom_dir, f\"{pd.read_csv(label_csv)['patientId'][0]}.dcm\")).pixel_array\nif sample_img.dtype != np.uint8:\n    sample_img = cv2.normalize(sample_img, None, 0, 255, cv2.NORM_MINMAX).astype(np.uint8)\nsample_features = preprocess_image(sample_img)[0]\nsample_mask = segment_rois(sample_features)\ninput_dim = len(extract_features(sample_features, sample_mask))\n# Initialize and run pipeline\npipeline = ImageProcessingPipeline(input_dim=input_dim)\npipeline.fit(train_dataset, val_dataset, epochs=20)\n\n   ","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-05-02T15:12:01.156253Z","iopub.execute_input":"2025-05-02T15:12:01.156617Z","iopub.status.idle":"2025-05-02T15:30:26.465236Z","shell.execute_reply.started":"2025-05-02T15:12:01.156587Z","shell.execute_reply":"2025-05-02T15:30:26.445361Z"}},"outputs":[{"name":"stdout","text":"Epoch 1/20\n","output_type":"stream"},{"name":"stderr","text":"/usr/local/lib/python3.10/dist-packages/keras/src/layers/core/dense.py:87: UserWarning: Do not pass an `input_shape`/`input_dim` argument to a layer. When using Sequential models, prefer using an `Input(shape)` object as the first layer in the model instead.\n  super().__init__(activity_regularizer=activity_regularizer, **kwargs)\n","output_type":"stream"},{"name":"stdout","text":"\u001b[1m567/567\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m373s\u001b[0m 651ms/step - accuracy: 0.5812 - loss: 80.4069 - val_accuracy: 0.6834 - val_loss: 0.6931\nEpoch 2/20\n\u001b[1m567/567\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m361s\u001b[0m 637ms/step - accuracy: 0.6747 - loss: 0.7289 - val_accuracy: 0.6951 - val_loss: 0.6148\nEpoch 3/20\n\u001b[1m567/567\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 478ms/step - accuracy: 0.6790 - loss: 0.7425","output_type":"stream"},{"traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)","\u001b[0;32m<ipython-input-21-f0462b0754bf>\u001b[0m in \u001b[0;36m<cell line: 16>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     14\u001b[0m \u001b[0;31m# Initialize and run pipeline\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     15\u001b[0m \u001b[0mpipeline\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mImageProcessingPipeline\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minput_dim\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0minput_dim\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 16\u001b[0;31m \u001b[0mpipeline\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtrain_dataset\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mval_dataset\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mepochs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m20\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     17\u001b[0m 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So we can\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    877\u001b[0m       \u001b[0;31m# run the first trace but we should fail if variables are created.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 878\u001b[0;31m       results = tracing_compilation.call_function(\n\u001b[0m\u001b[1;32m    879\u001b[0m           \u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_variable_creation_config\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    880\u001b[0m       )\n","\u001b[0;32m/usr/local/lib/python3.10/dist-packages/tensorflow/python/eager/polymorphic_function/tracing_compilation.py\u001b[0m in \u001b[0;36mcall_function\u001b[0;34m(args, kwargs, tracing_options)\u001b[0m\n\u001b[1;32m    137\u001b[0m   \u001b[0mbound_args\u001b[0m \u001b[0;34m=\u001b[0m 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\u001b[0mcancellation_context\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcancellation\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcontext\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   1551\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mcancellation_context\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1552\u001b[0;31m       outputs = execute.execute(\n\u001b[0m\u001b[1;32m   1553\u001b[0m           \u001b[0mname\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdecode\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"utf-8\"\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   1554\u001b[0m           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\u001b[0mcore\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_NotOkStatusException\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mKeyboardInterrupt\u001b[0m: "],"ename":"KeyboardInterrupt","evalue":"","output_type":"error"}],"execution_count":21},{"cell_type":"code","source":"pipeline.evaluate(test_dataset)\n\n# Example prediction (using a small subset of raw images)\nlabels_df = pd.read_csv(label_csv)\ntest_images = []\ntest_boxes = []\nfor _, row in labels_df.head(5).iterrows():\n    dicom_path = os.path.join(dicom_dir, f\"{row['patientId']}.dcm\")\n    if os.path.exists(dicom_path):\n        img = pydicom.dcmread(dicom_path).pixel_array\n        if img.dtype != np.uint8:\n            img = cv2.normalize(img, None, 0, 255, cv2.NORM_MINMAX).astype(np.uint8)\n        test_images.append(img)\n        box = [row['x'], row['y'], row['width'], row['height']]\n        if row['Target'] == 0 or not all(np.isfinite(box)):\n            box = None\n        test_boxes.append(box)\n\npredictions = pipeline.predict(test_images, test_boxes)\nprint(\"Sample Predictions:\", predictions)","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"# dcm_path = '/kaggle/input/rsna-pneumonia-detection-challenge/stage_2_train_images/00436515-870c-4b36-a041-de91049b9ab4.dcm'\n# # \n# image_array = pydicom.dcmread(dcm_path).pixel_array\n# # image_array = cv.resize(image_array, (224, 224))\n\n# print(image_array.shape)\n\n# # 繪圖\n# fig, ax = plt.subplots(1, 1, figsize=(6, 6))  # 建立圖表與子圖\n# ax.imshow(image_array, cmap='bone')          # 顯示影像\n\n# # 繪製標註框\n# rect = patches.Rectangle((264.0, 152.0), 213.0, 379.0, \n#                          edgecolor='r', facecolor='none', linewidth=2)\n# ax.add_patch(rect)                           # 在軸上新增標註框\n\n# plt.show()    ","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"\n# datapath = '/kaggle/input/rsna-pneumonia-detection-challenge/stage_2_train_images/008c19e8-a820-403a-930a-bc74a4053664.dcm'\n# temp_img = pydicom.dcmread(datapath).pixel_array\n# temp_box = [264.0, 152.0, 213.0, 379.0]\n\n# temp_img_formated, box = format_image(temp_img, temp_box)\n# print(box)\n# temp_color_img = cv.cvtColor(temp_img_formated, cv.COLOR_GRAY2RGB)\n\n# cv.rectangle(temp_color_img, box, (0, 255, 0), 1)\n\n# plt.imshow(temp_color_img)\n# # plt.axis(\"off\")\n# plt.show()","metadata":{"trusted":true,"jupyter":{"source_hidden":true}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"import os\n\nos.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' # disabling verbose tf logging\n\n# uncomment the following line if you want to force CPU\n# os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"-1\"\n\nimport tensorflow as tf\nprint(tf.__version__)","metadata":{"trusted":true,"jupyter":{"source_hidden":true}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"train_labels = pd.read_csv('/kaggle/input/rsna-pneumonia-detection-challenge/stage_2_train_labels.csv')\ntrain_labels","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"# from tqdm import tqdm  # 引入 tqdm\n# import os\n# import pydicom\n# import numpy as np\n# import tensorflow as tf\n# import math\n\n# def data_load(dataset, batch_size=3, full_data_path=\"/kaggle/input/rsna-pneumonia-detection-challenge/stage_2_train_images/\", image_ext=\".dcm\",ds_type='not_trian'):\n#     X = []\n#     Y = []\n\n#     # 使用 tqdm 包裝迭代器，顯示進度條\n#     for index, row in tqdm(dataset.iterrows(), total=len(dataset), desc=\"Loading data\"):\n#         filename = row['patientId']  # 根據欄位名稱取值\n\n#         # 讀取 DICOM 影像\n#         temp_img = pydicom.dcmread(os.path.join(full_data_path, filename + image_ext)).pixel_array\n        \n#         # 確認標註框是否有效\n#         temp_box = [row['x'], row['y'], row['width'], row['height']] if not math.isnan(row['x']) else [0.0, 0.0, 0.0, 0.0]\n\n#         # 格式化影像與標註框\n#         img, box = format_image(temp_img, temp_box)\n\n#         # 正規化影像與標註框\n#         img = img.astype(float) / 255.\n#         box = np.asarray(box, dtype=float) / input_size\n        \n#         # 合併標註與目標標籤\n#         label = np.append(box, row['Target'])\n\n#         # 將資料加入 X 和 Y\n#         X.append(img)\n#         Y.append(label)\n#     # print(len(X))\n#     # print(len(Y))\n    \n#     # 將資料轉換為 TensorFlow 格式\n#     X = np.array(X)\n#     # if ds_type==\"train\":\n#     #     X = np.tile(X, (3, 1, 1))  # 重複 3 次，沿第 0 軸 (樣本數量) 增加\n#     #     Y = np.array(Y)  \n#     #     Y = np.tile(Y,(3 ,1))\n#     #     np.random.shuffle(X)\n#     #     print(len(X))\n#     data_X_len = len(X)\n#     X = np.expand_dims(X, axis=3)\n#     X = tf.convert_to_tensor(X, dtype=tf.float32)\n#     Y = tf.convert_to_tensor(Y, dtype=tf.float32)\n    \n#     # 建立 TensorFlow 資料集\n#     result = tf.data.Dataset.from_tensor_slices((X, Y))\n\n#     return result,data_X_len\n# raw_train_ds,train_len = data_load(train_labels[:6001],ds_type=\"train\")\n# print(train_len)\n# raw_valid_ds,valid_len = data_load(train_labels[6001:6301],ds_type=\"not train\")\n# raw_test_ds, test_len = data_load(train_labels[6301:6501],ds_type=\"not train\")","metadata":{"trusted":true,"jupyter":{"source_hidden":true}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"plt.figure(figsize=(20, 10))\nBATCH_SIZE = 32\ni = 0\nfor images, labels in raw_train_ds:\n        \n        print(labels)\n        ax = plt.subplot(4, BATCH_SIZE//4, i + 1)\n        label = labels[4]\n        box = (labels[:4] * input_size)\n        box = tf.cast(box, tf.int32)\n\n        image = images.numpy().astype(\"float\") * 255.0\n        image = image.astype(np.uint8)\n        image_color = cv.cvtColor(image, cv.COLOR_GRAY2RGB)\n\n        color = (0, 0, 255)\n        if label > 0:\n            color = (0, 255, 0)\n\n        cv.rectangle(image_color, box.numpy(), color, 2)\n\n        plt.imshow(image_color)\n        plt.axis(\"off\")\n        i += 1","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"import os\ncpu_count = os.cpu_count()\nprint(f\"Available CPU cores: {cpu_count}\")\n","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"CLASSES = 2\n\ndef format_instance(image, label):\n    return image, (tf.one_hot(int(label[4]), CLASSES), [label[0], label[1], label[2], label[3]])","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"BATCH_SIZE = 32\n\n# see https://www.tensorflow.org/guide/data_performance\n\ndef tune_training_ds(dataset):\n    dataset = dataset.map(format_instance, num_parallel_calls=tf.data.AUTOTUNE)\n    dataset = dataset.shuffle(1024, reshuffle_each_iteration=True)\n    dataset = dataset.repeat() # The dataset be repeated indefinitely.\n    dataset = dataset.batch(BATCH_SIZE)\n    dataset = dataset.prefetch(tf.data.AUTOTUNE)\n    return dataset","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"labels\n","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"def tune_validation_ds(dataset):\n    dataset = dataset.map(format_instance, num_parallel_calls=tf.data.AUTOTUNE)\n    dataset = dataset.batch(len(dataset) // 4)\n    dataset = dataset.repeat()\n    return dataset","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"train_ds = tune_training_ds(raw_train_ds)\nvalidation_ds = tune_validation_ds(raw_valid_ds)\n","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"plt.figure(figsize=(20, 10))\nfor images, labels in train_ds.take(1):\n    for i in range(BATCH_SIZE):\n        # print(labels.shape)\n        ax = plt.subplot(4, BATCH_SIZE//4, i + 1)\n        label = labels[0][i]\n        box = (labels[1][i] * input_size)\n        box = tf.cast(box, tf.int32)\n\n        image = images[i].numpy().astype(\"float\") * 255.0\n        image = image.astype(np.uint8)\n        image_color = cv.cvtColor(image, cv.COLOR_GRAY2RGB)\n\n        color = (0, 0, 255)\n        if label[0] > 0:\n            color = (0, 255, 0)\n\n        cv.rectangle(image_color, box.numpy(), color, 2)\n\n        plt.imshow(image_color)\n        plt.axis(\"off\")","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"DROPOUT_FACTOR = 0.5\n\ndef build_feature_extractor(inputs):\n\n    x = tf.keras.layers.Conv2D(16, kernel_size=3, activation='relu', input_shape=(input_size, input_size, 1))(inputs)\n    x = tf.keras.layers.AveragePooling2D(2,2)(x)\n\n    x = tf.keras.layers.Conv2D(32, kernel_size=3, activation = 'relu')(x)\n    x = tf.keras.layers.AveragePooling2D(2,2)(x)\n\n    x = tf.keras.layers.Conv2D(64, kernel_size=3, activation = 'relu')(x)\n    x = tf.keras.layers.Dropout(DROPOUT_FACTOR)(x)\n    x = tf.keras.layers.AveragePooling2D(2,2)(x)\n\n    return x\n\ndef build_model_adaptor(inputs):\n    x = tf.keras.layers.Flatten()(inputs)\n    x = tf.keras.layers.Dense(64, activation='relu')(x)\n    return x\n\ndef build_classifier_head(inputs):\n    return tf.keras.layers.Dense(CLASSES, activation='softmax', name = 'classifier_head')(inputs)\n\ndef build_regressor_head(inputs):\n    return tf.keras.layers.Dense(units = 4, name = 'regressor_head')(inputs)\n\ndef build_model(inputs):\n    \n    feature_extractor = build_feature_extractor(inputs)\n\n    model_adaptor = build_model_adaptor(feature_extractor)\n\n    classification_head = build_classifier_head(model_adaptor)\n\n    regressor_head = build_regressor_head(model_adaptor)\n\n    model = tf.keras.Model(inputs = inputs, outputs = [classification_head, regressor_head])\n\n    model.compile(optimizer=tf.keras.optimizers.Adam(), \n              loss = {'classifier_head' : 'categorical_crossentropy', 'regressor_head' : 'mse' }, \n              metrics = {'classifier_head' : 'accuracy', 'regressor_head' : 'mse' })\n\n    return model","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"model = build_model(tf.keras.layers.Input(shape=(input_size, input_size, 1,)))\n\nmodel.summary()","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"# plot_model requires graphviz & pydot\n# see https://github.com/XifengGuo/CapsNet-Keras/issues/7#issuecomment-370745440\nfrom tensorflow.keras.utils import plot_model\n\nplot_model(model, show_shapes=True, show_layer_names=True)","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"EPOCHS = 100\n\nhistory = model.fit(train_ds,\n                    steps_per_epoch=(6000 // BATCH_SIZE),\n                    validation_data=validation_ds, validation_steps=1, \n                    epochs=EPOCHS)","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"plt.plot(history.history['classifier_head_accuracy'])\nplt.plot(history.history['val_classifier_head_accuracy'])\nplt.title('Model Accuracy')\nplt.ylabel('accuracy')\nplt.xlabel('epoch')\nplt.legend(['train', 'validation'], loc='upper left')\nplt.show()","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"# Evaluation","metadata":{}},{"cell_type":"code","source":"# # adapted from: https://pyimagesearch.com/2016/11/07/intersection-over-union-iou-for-object-detection/\n# def intersection_over_union(boxA, boxB):\n# \txA = max(boxA[0], boxB[0])\n# \tyA = max(boxA[1], boxB[1])\n# \txB = min(boxA[0] + boxA[2], boxB[0] + boxB[2])\n# \tyB = min(boxA[1] + boxA[3], boxB[1] + boxB[3])\n# \tinterArea = max(0, xB - xA + 1) * max(0, yB - yA + 1)\n# \tboxAArea = (boxA[2] + 1) * (boxA[3] + 1)\n# \tboxBArea = (boxB[2] + 1) * (boxB[3] + 1)\n# \tiou = interArea / float(boxAArea + boxBArea - interArea)\n# \treturn iou\ndef intersection_over_union(boxA, boxB):\n    # 提取座標\n    xA = max(boxA[0], boxB[0])\n    yA = max(boxA[1], boxB[1])\n    xB = min(boxA[0] + boxA[2], boxB[0] + boxB[2])\n    yB = min(boxA[1] + boxA[3], boxB[1] + boxB[3])\n\n    # 計算交集區域\n    interWidth = max(0, xB - xA)\n    interHeight = max(0, yB - yA)\n    interArea = interWidth * interHeight\n\n    # 計算各框面積\n    boxAArea = boxA[2] * boxA[3]  # 預測框面積\n    boxBArea = boxB[2] * boxB[3]  # 實際框面積\n\n    # 若有任何框面積為 0，直接返回 IoU = 0\n    if boxAArea == 0 or boxBArea == 0:\n        return 0.0  # 空框情況\n\n    # 計算 IoU\n    iou = interArea / float(boxAArea + boxBArea - interArea)\n    return iou\n","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"def tune_test_ds(dataset):\n    dataset = dataset.map(format_instance, num_parallel_calls=tf.data.AUTOTUNE)\n    dataset = dataset.batch(1) \n    dataset = dataset.repeat()\n    return dataset\n\ntest_ds = tune_test_ds(raw_test_ds)","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"plt.figure(figsize=(12, 10))\n\ntest_list = list(test_ds.take(20).as_numpy_iterator())\n\nprint(len(test_list))\n\nimage, labels = test_list[0]\n\nfor i in range(len(test_list)):\n\n    ax = plt.subplot(4, 5, i + 1)\n    image, labels = test_list[i]\n\n    predictions = model(image)\n\n    predicted_box = predictions[1][0] * input_size\n    predicted_box = tf.cast(predicted_box, tf.int32)\n\n    predicted_label = predictions[0][0]\n\n    image = image[0]\n\n    actual_label = labels[0][0]\n    actual_box = labels[1][0] * input_size\n    actual_box = tf.cast(actual_box, tf.int32)\n\n    image = image.astype(\"float\") * 255.0\n    image = image.astype(np.uint8)\n    image_color = cv.cvtColor(image, cv.COLOR_GRAY2RGB)\n\n    color = (255, 0, 0)\n    # print box red if predicted and actual label do not match\n    if (predicted_label[0] > 0.5 and actual_label[0] > 0) or (predicted_label[0] < 0.5 and actual_label[0] == 0):\n        color = (0, 255, 0)\n\n    img_label = \"unmasked\"\n    if predicted_label[0] > 0.5:\n        img_label = \"masked\"\n\n    predicted_box_n = predicted_box.numpy()\n    cv.rectangle(image_color, predicted_box_n, color, 2)\n    cv.rectangle(image_color, actual_box.numpy(), (0, 0, 255), 2)\n    cv.rectangle(image_color, (predicted_box_n[0], predicted_box_n[1] + predicted_box_n[3] - 20), (predicted_box_n[0] + predicted_box_n[2], predicted_box_n[1] + predicted_box_n[3]), color, -1)\n    cv.putText(image_color, img_label, (predicted_box_n[0] + 5, predicted_box_n[1] + predicted_box_n[3] - 5), cv.FONT_HERSHEY_SIMPLEX, 0.6, (0, 0, 0))\n\n    IoU = intersection_over_union(predicted_box.numpy(), actual_box.numpy())\n\n    plt.title(\"IoU:\" + format(IoU, '.4f'))\n    plt.imshow(image_color)\n    plt.axis(\"off\")\n","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"\n\n# 建立儲存比較圖的資料夾\noutput_dir = \"output_predictions\"\nos.makedirs(output_dir, exist_ok=True)\n\nplt.figure(figsize=(12, 10))\n\n# 將 test_ds 資料轉換為可迭代的列表\ntest_list = list(test_ds.take(200).as_numpy_iterator())\nprint(f\"Test Data Size: {len(test_list)}\")\n\n# 初始化計算變數\ncorrect_count = 0\ntotal_count = 0\niou_list = []\n\n# 開始處理每張圖片\nfor i in range(len(test_list)):\n\n    # ax = plt.subplot(4, 5, i + 1)\n\n    # 取得影像與標籤\n    image, labels = test_list[i]\n    predictions = model(image)\n\n    # 預測標籤與框\n    predicted_box = predictions[1][0] * input_size\n    predicted_box = tf.cast(predicted_box, tf.int32)\n    predicted_label = predictions[0][0]\n\n    # 取得實際標籤與框\n    image = image[0]\n    actual_label = labels[0][0]\n    actual_box = labels[1][0] * input_size\n    actual_box = tf.cast(actual_box, tf.int32)\n\n    # 預處理影像\n    image = image.astype(\"float\") * 255.0\n    image = image.astype(np.uint8)\n    image_color = cv.cvtColor(image, cv.COLOR_GRAY2RGB)\n\n    # 比較預測標籤與實際標籤\n    color = (255, 0, 0)  # 預設紅色\n    if (predicted_label[0] > 0.5 and actual_label[0] > 0) or (predicted_label[0] < 0.5 and actual_label[0] == 0):\n        color = (0, 255, 0)  # 預測正確顯示綠色\n        correct_count += 1\n\n    total_count += 1\n\n    # 繪製預測標籤\n    img_label = \"unmasked\"\n    if predicted_label[0] > 0.5:\n        img_label = \"masked\"\n\n    # 繪製預測框\n    predicted_box_n = predicted_box.numpy()\n    cv.rectangle(image_color, predicted_box_n, color, 2)\n    cv.rectangle(image_color, actual_box.numpy(), (0, 0, 255), 2)  # 實際標籤框紅色\n    cv.rectangle(image_color, (predicted_box_n[0], predicted_box_n[1] + predicted_box_n[3] - 20), \n                 (predicted_box_n[0] + predicted_box_n[2], predicted_box_n[1] + predicted_box_n[3]), color, -1)\n    cv.putText(image_color, img_label, (predicted_box_n[0] + 5, predicted_box_n[1] + predicted_box_n[3] - 5), \n               cv.FONT_HERSHEY_SIMPLEX, 0.6, (0, 0, 0))\n\n    # 計算 IoU\n    IoU = intersection_over_union(predicted_box.numpy(), actual_box.numpy())\n    iou_list.append(IoU)\n\n    # 顯示圖片與 IoU 值\n    # plt.title(f\"IoU: {IoU:.4f}\")\n    # plt.imshow(image_color)\n    # plt.axis(\"off\")\n\n    # 儲存圖片到資料夾\n    output_path = os.path.join(output_dir, f\"prediction_{i + 1}.png\")\n    cv.imwrite(output_path, cv.cvtColor(image_color, cv.COLOR_RGB2BGR))  # OpenCV 儲存格式為 BGR\n\n# 計算準確率與 IoU 平均值\naccuracy = correct_count / total_count\naverage_iou = np.mean(iou_list)\n\nprint(f\"準確率 (Accuracy): {accuracy:.4f}\")\nprint(f\"平均 IoU (Mean IoU): {average_iou:.4f}\")\n\n# 儲存圖表\nplt.savefig(os.path.join(output_dir, \"all_predictions.png\"))\nplt.show()\n","metadata":{"trusted":true},"outputs":[],"execution_count":null},{"cell_type":"code","source":"import shutil\n\n# 壓縮 output_predictions 資料夾為 predictions.zip\nshutil.make_archive('predictions', 'zip', output_dir)\n","metadata":{"trusted":true},"outputs":[],"execution_count":null}]}