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import cv2
import mediapipe as mp
import numpy as np
import gradio as gr
import tempfile
import os
mp_pose = mp.solutions.pose
mp_drawing = mp.solutions.drawing_utils
pose = mp_pose.Pose(static_image_mode=False, min_detection_confidence=0.5, min_tracking_confidence=0.5)
def calculate_angle(a, b, c):
a = np.array(a)
b = np.array(b)
c = np.array(c)
ba = a - b
bc = c - b
cosine_angle = np.dot(ba, bc) / (np.linalg.norm(ba) * np.linalg.norm(bc))
angle = np.arccos(np.clip(cosine_angle, -1.0, 1.0))
return np.degrees(angle)
def detect_pose_video(video_path, max_duration=20):
try:
if not os.path.exists(video_path):
return None, "Error: Video file does not exist."
cap = cv2.VideoCapture(video_path)
if not cap.isOpened():
return None, "Error: Cannot open video file."
fps = cap.get(cv2.CAP_PROP_FPS) or 20.0
width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH) or 640)
height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT) or 480)
max_frames = int(fps * max_duration)
# Use tempfile for a safe path Hugging Face can access
tmp_file = tempfile.NamedTemporaryFile(delete=False, suffix=".mp4")
out_path = tmp_file.name
tmp_file.close()
fourcc = cv2.VideoWriter_fourcc(*'mp4v')
out = cv2.VideoWriter(out_path, fourcc, fps, (width, height))
frame_count = 0
while frame_count < max_frames:
ret, frame = cap.read()
if not ret:
break
# Resize if too big
max_dim = 640
h, w, _ = frame.shape
if max(h, w) > max_dim:
scale = max_dim / max(h, w)
frame = cv2.resize(frame, (int(w*scale), int(h*scale)))
frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
results = pose.process(frame_rgb)
if results.pose_landmarks:
mp_drawing.draw_landmarks(
frame,
results.pose_landmarks,
mp_pose.POSE_CONNECTIONS,
mp_drawing.DrawingSpec(color=(0,255,0), thickness=2, circle_radius=2),
mp_drawing.DrawingSpec(color=(0,0,255), thickness=2)
)
landmarks = results.pose_landmarks.landmark
shoulder = [landmarks[mp_pose.PoseLandmark.LEFT_SHOULDER.value].x * frame.shape[1],
landmarks[mp_pose.PoseLandmark.LEFT_SHOULDER.value].y * frame.shape[0]]
elbow = [landmarks[mp_pose.PoseLandmark.LEFT_ELBOW.value].x * frame.shape[1],
landmarks[mp_pose.PoseLandmark.LEFT_ELBOW.value].y * frame.shape[0]]
wrist = [landmarks[mp_pose.PoseLandmark.LEFT_WRIST.value].x * frame.shape[1],
landmarks[mp_pose.PoseLandmark.LEFT_WRIST.value].y * frame.shape[0]]
angle = calculate_angle(shoulder, elbow, wrist)
cv2.putText(frame, f"Left Elbow: {int(angle)} deg", (20,40),
cv2.FONT_HERSHEY_SIMPLEX, 1, (255,255,0), 2)
out.write(frame)
frame_count += 1
cap.release()
out.release()
return out_path, "Video processed successfully."
except Exception as e:
return None, f"Error: {str(e)}"
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