{ "cells": [ { "cell_type": "markdown", "id": "cab2d0f1", "metadata": {}, "source": [ "# **Trajectory** back on original video\n", "\n", "IDEA:\n", "- take the processed positions\n", "- apply the inverse of the homography\n", "- print on the video frame by frame all points before the current frame" ] }, { "cell_type": "code", "execution_count": 31, "id": "4cd7f188", "metadata": {}, "outputs": [], "source": [ "from pathlib import Path\n", "import cv2\n", "import csv\n", "\n", "import numpy as np\n", "import pandas as pd" ] }, { "cell_type": "code", "execution_count": null, "id": "060e2535", "metadata": {}, "outputs": [], "source": [ "VIDEO_NUMBER = \"7\"\n", "PROJECT_ROOT = Path().resolve().parent.parent\n", "INPUT_VIDEO_PATH = str(\n", " PROJECT_ROOT\n", " / \"data\"\n", " / f\"recording_{VIDEO_NUMBER}\"\n", " / f\"Recording_{VIDEO_NUMBER}.mp4\"\n", ")\n", "TRASFORMED_CSV_PATH = str(\n", " PROJECT_ROOT\n", " / \"data\"\n", " / \"auxiliary_data\"\n", " / \"reconstructed_positions\"\n", " / f\"Transformed_positions_processed_{VIDEO_NUMBER}.csv\"\n", ")\n", "LANE_CSV_PATH = str(\n", " PROJECT_ROOT\n", " / \"data\"\n", " / \"auxiliary_data\"\n", " / \"lane_points\"\n", " / f\"Lane_points_{VIDEO_NUMBER}.csv\"\n", ")\n", "OUTPUT_VIDEO_PATH = str(\n", " PROJECT_ROOT\n", " / \"data\"\n", " / f\"recording_{VIDEO_NUMBER}\"\n", " / f\"Tracked_output_{VIDEO_NUMBER}.mp4\"\n", ")" ] }, { "cell_type": "code", "execution_count": 33, "id": "72b93c45", "metadata": {}, "outputs": [], "source": [ "# Load video\n", "cap = cv2.VideoCapture(INPUT_VIDEO_PATH)\n", "if not cap.isOpened():\n", " print(\"Error: Could not open video.\")\n", " exit\n", "\n", "# Get video properties\n", "frame_width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))\n", "frame_height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))\n", "fps = int(cap.get(cv2.CAP_PROP_FPS))\n", "\n", "# Setup video writer\n", "fourcc = cv2.VideoWriter_fourcc(*\"mp4v\")\n", "out = cv2.VideoWriter(OUTPUT_VIDEO_PATH, fourcc, fps, (frame_width, frame_height))" ] }, { "cell_type": "code", "execution_count": 34, "id": "27d15335", "metadata": {}, "outputs": [], "source": [ "# Load lane points and compute homographies\n", "lane_points = pd.read_csv(LANE_CSV_PATH)\n", "homographies = {}\n", "\n", "width = 106 # Approximate pixels for 1.0668m\n", "height = 1829 # Approximate pixels for 18.29m\n", "\n", "for _, row in lane_points.iterrows():\n", " frame = int(row[\"Frame\"])\n", " pts_src = np.array(\n", " [\n", " [row[\"bottom_left_x\"], row[\"bottom_left_y\"]],\n", " [row[\"bottom_right_x\"], row[\"bottom_right_y\"]],\n", " [row[\"up_right_x\"], row[\"up_right_y\"]],\n", " [row[\"up_left_x\"], row[\"up_left_y\"]],\n", " ],\n", " dtype=np.float32,\n", " )\n", "\n", " pts_dst = np.array(\n", " [[0, height], [width, height], [width, 0], [0, 0]], dtype=np.float32\n", " )\n", "\n", " H, _ = cv2.findHomography(pts_dst, pts_src) # Inverse homography\n", " if H is not None:\n", " homographies[frame] = H\n", "\n", "# Load real-world trajectory positions (top-down space)\n", "positions = {}\n", "with open(TRASFORMED_CSV_PATH, mode=\"r\") as file:\n", " reader = csv.reader(file)\n", " next(reader) # Skip header\n", " for coord in reader:\n", " frame_num, x, y = coord\n", " frame_num = int(frame_num)\n", " if x and y:\n", " positions[frame_num] = (float(x), float(y)) # Store in top-down space\n", " else:\n", " positions[frame_num] = None" ] }, { "cell_type": "code", "execution_count": null, "id": "e63549c3", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "End of video or error reading frame.\n", "Tracking video saved to /home/davic/projects/IACV_project/bowling-analysis/data/recording_7/Tracked_output_7.mp4\n" ] } ], "source": [ "# Draw trajectory frame-by-frame\n", "frame_count = 0\n", "trajectory = [] # Store real-world trajectory (top-down)\n", "\n", "while True:\n", " ret, frame = cap.read()\n", " if not ret:\n", " print(\"End of video or error reading frame.\")\n", " break\n", "\n", " # Collect current position if available\n", " if frame_count in positions and positions[frame_count] is not None:\n", " trajectory.append(positions[frame_count])\n", "\n", " # Transform all points in trajectory to current frame using current frame's homography\n", " refreshed_trajectory = []\n", " if frame_count in homographies:\n", " H = homographies[frame_count]\n", " for x, y in trajectory:\n", " transformed = cv2.perspectiveTransform(\n", " np.array([[[x, y]]], dtype=np.float32), H\n", " )[0][0]\n", " refreshed_trajectory.append((int(transformed[0]), int(transformed[1])))\n", "\n", " # Draw trajectory lines\n", " for i in range(1, len(refreshed_trajectory)):\n", " cv2.line(\n", " frame, refreshed_trajectory[i - 1], refreshed_trajectory[i], (0, 0, 255), 2\n", " )\n", "\n", " # Draw current ball position\n", " if refreshed_trajectory:\n", " x, y = refreshed_trajectory[-1]\n", " cv2.circle(frame, (x, y), 4, (0, 0, 255), -1) # Red dot\n", "\n", " out.write(frame)\n", " frame_count += 1\n", "\n", "cap.release()\n", "out.release()\n", "print(f\"Tracking video saved to {OUTPUT_VIDEO_PATH}\")" ] } ], "metadata": { "kernelspec": { "display_name": ".venv", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.12.3" } }, "nbformat": 4, "nbformat_minor": 5 }