|
| 1 | +import cv2 |
| 2 | +import mediapipe as mp |
| 3 | +import numpy as np |
| 4 | +from collections import deque |
| 5 | + |
| 6 | +# Initialize MediaPipe Pose |
| 7 | +mp_pose = mp.solutions.pose |
| 8 | +pose = mp_pose.Pose() |
| 9 | +mp_drawing = mp.solutions.drawing_utils |
| 10 | + |
| 11 | +# Initialize video capture |
| 12 | +cap = cv2.VideoCapture('bowling.mp4') |
| 13 | + |
| 14 | +# Store wrist trajectory and arcs |
| 15 | +wrist_trajectory = deque(maxlen=100) # Main wrist trajectory |
| 16 | +wrist_positions = deque(maxlen=20) # For arcs |
| 17 | +elbow_positions = deque(maxlen=20) |
| 18 | +shoulder_positions = deque(maxlen=20) |
| 19 | + |
| 20 | +# Function to convert normalized coordinates to pixel coordinates |
| 21 | +def to_pixel_coords(landmark, frame): |
| 22 | + return int(landmark.x * frame.shape[1]), int(landmark.y * frame.shape[0]) |
| 23 | + |
| 24 | +# Function to draw a gradient arc between two points |
| 25 | +def draw_gradient_arc(frame, p1, p2, thickness, start_color, end_color): |
| 26 | + num_segments = 50 |
| 27 | + x_diff = (p2[0] - p1[0]) / num_segments |
| 28 | + y_diff = (p2[1] - p1[1]) / num_segments |
| 29 | + |
| 30 | + for i in range(num_segments): |
| 31 | + # Compute start and end points of each segment |
| 32 | + start_point = (int(p1[0] + i * x_diff), int(p1[1] + i * y_diff)) |
| 33 | + end_point = (int(p1[0] + (i + 1) * x_diff), int(p1[1] + (i + 1) * y_diff)) |
| 34 | + |
| 35 | + # Interpolate color between start and end |
| 36 | + alpha = i / num_segments |
| 37 | + color = ( |
| 38 | + int(start_color[0] * (1 - alpha) + end_color[0] * alpha), |
| 39 | + int(start_color[1] * (1 - alpha) + end_color[1] * alpha), |
| 40 | + int(start_color[2] * (1 - alpha) + end_color[2] * alpha), |
| 41 | + ) |
| 42 | + cv2.line(frame, start_point, end_point, color, thickness) |
| 43 | + |
| 44 | +while cap.isOpened(): |
| 45 | + ret, frame = cap.read() |
| 46 | + if not ret: |
| 47 | + break |
| 48 | + frame = cv2.resize(frame, (1000, 600)) |
| 49 | + # Convert the frame to RGB |
| 50 | + rgb_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) |
| 51 | + results = pose.process(rgb_frame) |
| 52 | + |
| 53 | + if results.pose_landmarks: |
| 54 | + landmarks = results.pose_landmarks.landmark |
| 55 | + |
| 56 | + # Extract right-hand keypoints |
| 57 | + right_shoulder = landmarks[mp_pose.PoseLandmark.RIGHT_SHOULDER] |
| 58 | + right_elbow = landmarks[mp_pose.PoseLandmark.RIGHT_ELBOW] |
| 59 | + right_wrist = landmarks[mp_pose.PoseLandmark.RIGHT_WRIST] |
| 60 | + |
| 61 | + # Convert normalized coordinates to pixel coordinates |
| 62 | + shoulder_coords = to_pixel_coords(right_shoulder, frame) |
| 63 | + elbow_coords = to_pixel_coords(right_elbow, frame) |
| 64 | + wrist_coords = to_pixel_coords(right_wrist, frame) |
| 65 | + |
| 66 | + # Add wrist coordinates to the deque for trajectory |
| 67 | + wrist_trajectory.append(wrist_coords) |
| 68 | + |
| 69 | + # Add coordinates for arcs |
| 70 | + shoulder_positions.append(shoulder_coords) |
| 71 | + elbow_positions.append(elbow_coords) |
| 72 | + wrist_positions.append(wrist_coords) |
| 73 | + |
| 74 | + # Draw the wrist trajectory (main line) |
| 75 | + for i in range(1, len(wrist_trajectory)): |
| 76 | + cv2.line(frame, wrist_trajectory[i - 1], wrist_trajectory[i], (0, 255, 255), 3) |
| 77 | + |
| 78 | + # Draw dynamic arcs for the last few positions |
| 79 | + for i in range(1, len(shoulder_positions)): |
| 80 | + # Fade effect using index |
| 81 | + thickness = max(2, 10 - (len(shoulder_positions) - i)) |
| 82 | + |
| 83 | + # Gradient arc for shoulder-to-elbow |
| 84 | + draw_gradient_arc(frame, shoulder_positions[i - 1], elbow_positions[i - 1], thickness, (0, 255, 0), (255, 0, 0)) |
| 85 | + # Gradient arc for elbow-to-wrist |
| 86 | + draw_gradient_arc(frame, elbow_positions[i - 1], wrist_positions[i - 1], thickness, (255, 0, 0), (0, 0, 255)) |
| 87 | + |
| 88 | + # Draw keypoints |
| 89 | + cv2.circle(frame, shoulder_coords, 10, (0, 255, 0), -1) # Shoulder |
| 90 | + cv2.circle(frame, elbow_coords, 10, (255, 0, 0), -1) # Elbow |
| 91 | + cv2.circle(frame, wrist_coords, 10, (0, 0, 255), -1) # Wrist |
| 92 | + |
| 93 | + # Display the frame |
| 94 | + cv2.imshow('Dynamic Bowling Trajectory', frame) |
| 95 | + |
| 96 | + if cv2.waitKey(10) & 0xFF == ord('q'): |
| 97 | + break |
| 98 | + |
| 99 | +cap.release() |
| 100 | +cv2.destroyAllWindows() |
| 101 | + |
| 102 | + |
| 103 | + |
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