Main

Extrating_images_with_labels_from_videos.ipynb

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+{
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "provenance": [],
+      "gpuType": "T4",
+      "authorship_tag": "ABX9TyNZpcELM44Sax8rDaoqF7I0",
+      "include_colab_link": true
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    },
+    "accelerator": "GPU"
+  },
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "view-in-github",
+        "colab_type": "text"
+      },
+      "source": [
+        "<a href=\"https://colab.research.google.com/github/AmirAziz1221/computer-vision-course/blob/main/Extrating_images_with_labels_from_videos.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 2,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "woyyurXohzHE",
+        "outputId": "062f9497-41b0-4d7c-f849-88cc2ffecf4c"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
+          ]
+        }
+      ],
+      "source": [
+        "from google.colab import drive\n",
+        "drive.mount('/content/drive')"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "import cv2\n",
+        "import os\n",
+        "\n",
+        "# Paths\n",
+        "video_path = '/content/drive/MyDrive/Colab Notebooks/flood shared with Amir/flood videos/Flood In Booni Upper Chitral Pakistan_part_1.avi'\n",
+        "output_images_dir = '/content/drive/MyDrive/Water Segmentation/frames/train/images'\n",
+        "output_labels_dir = '/content/drive/MyDrive/Water Segmentation/frames/train/labels'\n",
+        "\n",
+        "# Create output directories if they don't exist\n",
+        "os.makedirs(output_images_dir, exist_ok=True)  # Create images output directory if it doesn't exist\n",
+        "os.makedirs(output_labels_dir, exist_ok=True)  # Create labels output directory if it doesn't exist\n",
+        "\n",
+        "# Open video\n",
+        "cap = cv2.VideoCapture(video_path)\n",
+        "frame_rate = cap.get(cv2.CAP_PROP_FPS)  # Frames per second\n",
+        "frame_count = 0\n",
+        "save_frequency = int(frame_rate)  # Modify to control frame save interval\n",
+        "\n",
+        "# Example bounding boxes: (x_min, y_min, x_max, y_max, class_id)\n",
+        "# You need to replace this with actual logic to get bounding boxes if necessary\n",
+        "frame_boxes = {\n",
+        "    0: [(10, 10, 50, 50, 1)],  # frame_number: [(x_min, y_min, x_max, y_max, class), ...]\n",
+        "    1: [(20, 20, 60, 60, 1)],\n",
+        "    # Add more frames with their bounding boxes as needed\n",
+        "}\n",
+        "\n",
+        "while cap.isOpened():\n",
+        "    ret, frame = cap.read()\n",
+        "    if not ret:\n",
+        "        break\n",
+        "\n",
+        "    # Check if we should save this frame\n",
+        "    if frame_count % save_frequency == 0:\n",
+        "        frame_filename = os.path.join(output_images_dir, f'frame_{frame_count}.jpg')\n",
+        "\n",
+        "        # Get bounding boxes for the current frame (or set empty if none)\n",
+        "        boxes = frame_boxes.get(frame_count, [])\n",
+        "\n",
+        "        # Draw bounding boxes on the frame\n",
+        "        for (x_min, y_min, x_max, y_max, cls) in boxes:\n",
+        "            cv2.rectangle(frame, (x_min, y_min), (x_max, y_max), (0, 255, 0), 2)  # Draw rectangle\n",
+        "            cv2.putText(frame, str(cls), (x_min, y_min - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 1)  # Class label\n",
+        "\n",
+        "        # Save the labeled frame as an image\n",
+        "        cv2.imwrite(frame_filename, frame)\n",
+        "\n",
+        "        # Save bounding boxes for this frame in a text file\n",
+        "        label_filename = os.path.join(output_labels_dir, f'frame_{frame_count}.txt')\n",
+        "        with open(label_filename, 'w') as label_file:\n",
+        "            for (x_min, y_min, x_max, y_max, cls) in boxes:\n",
+        "                label_file.write(f\"{cls} {x_min} {y_min} {x_max} {y_max}\\n\")\n",
+        "\n",
+        "    frame_count += 1\n",
+        "\n",
+        "cap.release()"
+      ],
+      "metadata": {
+        "id": "TX8NmITCh9e-"
+      },
+      "execution_count": 23,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "import cv2\n",
+        "import os\n",
+        "\n",
+        "# Paths\n",
+        "video_path = '/content/drive/MyDrive/Water Segmentation/combine video.mp4'\n",
+        "output_images_dir = '/content/drive/MyDrive/Water Segmentation/frames/train/images'\n",
+        "output_labels_dir = '/content/drive/MyDrive/Water Segmentation/frames/train/labels'\n",
+        "\n",
+        "# Create output directories if they don't exist\n",
+        "os.makedirs(output_images_dir, exist_ok=True)  # Create images output directory if it doesn't exist\n",
+        "os.makedirs(output_labels_dir, exist_ok=True)  # Create labels output directory if it doesn't exist\n",
+        "\n",
+        "# Open video\n",
+        "cap = cv2.VideoCapture(video_path)\n",
+        "frame_rate = cap.get(cv2.CAP_PROP_FPS)  # Frames per second\n",
+        "frame_count = 0\n",
+        "save_frequency = int(frame_rate)  # Modify to control frame save interval\n",
+        "\n",
+        "# Example bounding boxes: (x_min, y_min, x_max, y_max, class_id)\n",
+        "# You need to replace this with actual logic to get bounding boxes if necessary\n",
+        "frame_boxes = {\n",
+        "    0: [(10, 10, 50, 50, 1)],  # frame_number: [(x_min, y_min, x_max, y_max, class), ...]\n",
+        "    1: [(20, 20, 60, 60, 1)],\n",
+        "    # Add more frames with their bounding boxes as needed\n",
+        "}\n",
+        "\n",
+        "while cap.isOpened():\n",
+        "    ret, frame = cap.read()\n",
+        "    if not ret:\n",
+        "        break\n",
+        "\n",
+        "    # Check if we should save this frame\n",
+        "    if frame_count % save_frequency == 0:\n",
+        "        frame_filename = os.path.join(output_images_dir, f'frame_{frame_count}.jpg')\n",
+        "\n",
+        "        # Get bounding boxes for the current frame (or set empty if none)\n",
+        "        boxes = frame_boxes.get(frame_count, [])\n",
+        "\n",
+        "        # Draw bounding boxes on the frame\n",
+        "        for (x_min, y_min, x_max, y_max, cls) in boxes:\n",
+        "            cv2.rectangle(frame, (x_min, y_min), (x_max, y_max), (0, 255, 0), 2)  # Draw rectangle\n",
+        "            cv2.putText(frame, str(cls), (x_min, y_min - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 1)  # Class label\n",
+        "\n",
+        "        # Save the labeled frame as an image\n",
+        "        cv2.imwrite(frame_filename, frame)\n",
+        "\n",
+        "        # Save bounding boxes for this frame in a text file\n",
+        "        label_filename = os.path.join(output_labels_dir, f'frame_{frame_count}.txt')\n",
+        "        with open(label_filename, 'w') as label_file:\n",
+        "            for (x_min, y_min, x_max, y_max, cls) in boxes:\n",
+        "                label_file.write(f\"{cls} {x_min} {y_min} {x_max} {y_max}\\n\")\n",
+        "\n",
+        "    frame_count += 1\n",
+        "\n",
+        "cap.release()\n"
+      ],
+      "metadata": {
+        "id": "mHBfHpf5lnZI"
+      },
+      "execution_count": 22,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "import cv2\n",
+        "import os\n",
+        "\n",
+        "# Paths\n",
+        "video_path = '/content/drive/MyDrive/Water Segmentation/combine video.mp4'\n",
+        "output_images_dir = '/content/drive/MyDrive/Water Segmentation/frames/train/images'\n",
+        "output_labels_dir = '/content/drive/MyDrive/Water Segmentation/frames/train/labels'\n",
+        "\n",
+        "# Create output directories if they don't exist\n",
+        "os.makedirs(output_images_dir, exist_ok=True)  # Create images output directory if it doesn't exist\n",
+        "os.makedirs(output_labels_dir, exist_ok=True)  # Create labels output directory if it doesn't exist\n",
+        "\n",
+        "# Open video\n",
+        "cap = cv2.VideoCapture(video_path)\n",
+        "frame_rate = cap.get(cv2.CAP_PROP_FPS)  # Frames per second\n",
+        "frame_count = 0\n",
+        "save_frequency = int(frame_rate)  # Modify to control frame save interval\n",
+        "\n",
+        "# Example bounding boxes: (x_min, y_min, x_max, y_max, class_id)\n",
+        "# You need to replace this with actual logic to get bounding boxes if necessary\n",
+        "frame_boxes = {\n",
+        "    0: [(10, 10, 50, 50, 1)],  # frame_number: [(x_min, y_min, x_max, y_max, class), ...]\n",
+        "    1: [(20, 20, 60, 60, 1)],\n",
+        "    # Add more frames with their bounding boxes as needed\n",
+        "}\n",
+        "\n",
+        "while cap.isOpened():\n",
+        "    ret, frame = cap.read()\n",
+        "    if not ret:\n",
+        "        break\n",
+        "\n",
+        "    # Check if we should save this frame\n",
+        "    if frame_count % save_frequency == 0:\n",
+        "        frame_filename = os.path.join(output_images_dir, f'frame_{frame_count}.jpg')\n",
+        "\n",
+        "        # Get bounding boxes for the current frame (or set empty if none)\n",
+        "        boxes = frame_boxes.get(frame_count, [])\n",
+        "\n",
+        "        # Draw bounding boxes on the frame\n",
+        "        for (x_min, y_min, x_max, y_max, cls) in boxes:\n",
+        "            cv2.rectangle(frame, (x_min, y_min), (x_max, y_max), (0, 255, 0), 2)  # Draw rectangle\n",
+        "            cv2.putText(frame, str(cls), (x_min, y_min - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 1)  # Class label\n",
+        "\n",
+        "        # Save the labeled frame as an image\n",
+        "        cv2.imwrite(frame_filename, frame)\n",
+        "\n",
+        "        # Save bounding boxes for this frame in a text file\n",
+        "        label_filename = os.path.join(output_labels_dir, f'frame_{frame_count}.txt')\n",
+        "        with open(label_filename, 'w') as label_file:\n",
+        "            for (x_min, y_min, x_max, y_max, cls) in boxes:\n",
+        "                label_file.write(f\"{cls} {x_min} {y_min} {x_max} {y_max}\\n\")\n",
+        "\n",
+        "    frame_count += 1\n",
+        "\n",
+        "cap.release()\n"
+      ],
+      "metadata": {
+        "id": "7pvM2ZpFkdkU"
+      },
+      "execution_count": 8,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "import cv2\n",
+        "import os\n",
+        "\n",
+        "# Paths\n",
+        "video_path = '/content/drive/MyDrive/Colab Notebooks/flood shared with Amir/flood videos/Floods submerge villages as Typhoon Carina brings heavy rains in Philippines - ABS-CBN News_part_0.avi'\n",
+        "output_images_dir = '/content/drive/MyDrive/Water Segmentation/frames/train/images'\n",
+        "output_labels_dir = '/content/drive/MyDrive/Water Segmentation/frames/train/labels'\n",
+        "\n",
+        "# Create output directories if they don't exist\n",
+        "os.makedirs(output_images_dir, exist_ok=True)  # Create images output directory if it doesn't exist\n",
+        "os.makedirs(output_labels_dir, exist_ok=True)  # Create labels output directory if it doesn't exist\n",
+        "\n",
+        "# Open video\n",
+        "cap = cv2.VideoCapture(video_path)\n",
+        "frame_rate = cap.get(cv2.CAP_PROP_FPS)  # Frames per second\n",
+        "frame_count = 0\n",
+        "save_frequency = int(frame_rate)  # Modify to control frame save interval\n",
+        "\n",
+        "# Example bounding boxes: (x_min, y_min, x_max, y_max, class_id)\n",
+        "# You need to replace this with actual logic to get bounding boxes if necessary\n",
+        "frame_boxes = {\n",
+        "    0: [(10, 10, 50, 50, 1)],  # frame_number: [(x_min, y_min, x_max, y_max, class), ...]\n",
+        "    1: [(20, 20, 60, 60, 1)],\n",
+        "    # Add more frames with their bounding boxes as needed\n",
+        "}\n",
+        "\n",
+        "while cap.isOpened():\n",
+        "    ret, frame = cap.read()\n",
+        "    if not ret:\n",
+        "        break\n",
+        "\n",
+        "    # Check if we should save this frame\n",
+        "    if frame_count % save_frequency == 0:\n",
+        "        frame_filename = os.path.join(output_images_dir, f'frame_{frame_count}.jpg')\n",
+        "\n",
+        "        # Get bounding boxes for the current frame (or set empty if none)\n",
+        "        boxes = frame_boxes.get(frame_count, [])\n",
+        "\n",
+        "        # Draw bounding boxes on the frame\n",
+        "        for (x_min, y_min, x_max, y_max, cls) in boxes:\n",
+        "            cv2.rectangle(frame, (x_min, y_min), (x_max, y_max), (0, 255, 0), 2)  # Draw rectangle\n",
+        "            cv2.putText(frame, str(cls), (x_min, y_min - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 1)  # Class label\n",
+        "\n",
+        "        # Save the labeled frame as an image\n",
+        "        cv2.imwrite(frame_filename, frame)\n",
+        "\n",
+        "        # Save bounding boxes for this frame in a text file\n",
+        "        label_filename = os.path.join(output_labels_dir, f'frame_{frame_count}.txt')\n",
+        "        with open(label_filename, 'w') as label_file:\n",
+        "            for (x_min, y_min, x_max, y_max, cls) in boxes:\n",
+        "                label_file.write(f\"{cls} {x_min} {y_min} {x_max} {y_max}\\n\")\n",
+        "\n",
+        "    frame_count += 1\n",
+        "\n",
+        "cap.release()\n"
+      ],
+      "metadata": {
+        "id": "AyUdW-Oik_vW"
+      },
+      "execution_count": 24,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "import cv2\n",
+        "import os\n",
+        "\n",
+        "# Paths\n",
+        "video_path = '/content/drive/MyDrive/Colab Notebooks/flood shared with Amir/normal flow/Free stock footage_ Wide shallow river in the green forest_part_0.avi'\n",
+        "output_images_dir = '/content/drive/MyDrive/Water Segmentation/frames/train/images'\n",
+        "output_labels_dir = '/content/drive/MyDrive/Water Segmentation/frames/train/labels'\n",
+        "\n",
+        "# Create output directories if they don't exist\n",
+        "os.makedirs(output_images_dir, exist_ok=True)  # Create images output directory if it doesn't exist\n",
+        "os.makedirs(output_labels_dir, exist_ok=True)  # Create labels output directory if it doesn't exist\n",
+        "\n",
+        "# Open video\n",
+        "cap = cv2.VideoCapture(video_path)\n",
+        "frame_rate = cap.get(cv2.CAP_PROP_FPS)  # Frames per second\n",
+        "frame_count = 0\n",
+        "save_frequency = int(frame_rate)  # Modify to control frame save interval\n",
+        "\n",
+        "# Example bounding boxes: (x_min, y_min, x_max, y_max, class_id)\n",
+        "# You need to replace this with actual logic to get bounding boxes if necessary\n",
+        "frame_boxes = {\n",
+        "    0: [(10, 10, 50, 50, 1)],  # frame_number: [(x_min, y_min, x_max, y_max, class), ...]\n",
+        "    1: [(20, 20, 60, 60, 1)],\n",
+        "    # Add more frames with their bounding boxes as needed\n",
+        "}\n",
+        "\n",
+        "while cap.isOpened():\n",
+        "    ret, frame = cap.read()\n",
+        "    if not ret:\n",
+        "        break\n",
+        "\n",
+        "    # Check if we should save this frame\n",
+        "    if frame_count % save_frequency == 0:\n",
+        "        frame_filename = os.path.join(output_images_dir, f'frame_{frame_count}.jpg')\n",
+        "\n",
+        "        # Get bounding boxes for the current frame (or set empty if none)\n",
+        "        boxes = frame_boxes.get(frame_count, [])\n",
+        "\n",
+        "        # Draw bounding boxes on the frame\n",
+        "        for (x_min, y_min, x_max, y_max, cls) in boxes:\n",
+        "            cv2.rectangle(frame, (x_min, y_min), (x_max, y_max), (0, 255, 0), 2)  # Draw rectangle\n",
+        "            cv2.putText(frame, str(cls), (x_min, y_min - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 1)  # Class label\n",
+        "\n",
+        "        # Save the labeled frame as an image\n",
+        "        cv2.imwrite(frame_filename, frame)\n",
+        "\n",
+        "        # Save bounding boxes for this frame in a text file\n",
+        "        label_filename = os.path.join(output_labels_dir, f'frame_{frame_count}.txt')\n",
+        "        with open(label_filename, 'w') as label_file:\n",
+        "            for (x_min, y_min, x_max, y_max, cls) in boxes:\n",
+        "                label_file.write(f\"{cls} {x_min} {y_min} {x_max} {y_max}\\n\")\n",
+        "\n",
+        "    frame_count += 1\n",
+        "\n",
+        "cap.release()\n"
+      ],
+      "metadata": {
+        "id": "mHs1iKoKofb7"
+      },
+      "execution_count": 31,
+      "outputs": []
+    },
+    {
+      "cell_type": "code",
+      "source": [],
+      "metadata": {
+        "id": "kVSPzr_gojTy"
+      },
+      "execution_count": null,
+      "outputs": []
+    }
+  ]
+}