test1 with media pipe

Dockerfile

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+# Read the doc: https://huggingface.co/docs/hub/spaces-sdks-docker
+# you will also find guides on how best to write your Dockerfile
+
+FROM python:3.9
+
+RUN useradd -m -u 1000 user
+USER user
+ENV PATH="/home/user/.local/bin:$PATH"
+
+WORKDIR /app
+
+COPY --chown=user ./requirements.txt requirements.txt
+RUN pip install --no-cache-dir --upgrade -r requirements.txt
+
+COPY --chown=user . /app
+CMD ["gunicorn", "-b", "0.0.0.0:7860","app:app"]

app.py

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+from flask import Flask, render_template, request, Response
+import cv2
+import mediapipe as mp
+import numpy as np
+import os
+
+app = Flask(__name__)
+
+# Initialize Mediapipe Pose
+mp_pose = mp.solutions.pose
+mp_drawing = mp.solutions.drawing_utils
+
+# Function to calculate the angle between three points
+def calculate_angle(a, b, c):
+    a = np.array(a)  # First point
+    b = np.array(b)  # Middle point
+    c = np.array(c)  # Last point
+
+    radians = np.arctan2(c[1] - b[1], c[0] - b[0]) - np.arctan2(a[1] - b[1], a[0] - b[0])
+    angle = np.abs(radians * 180.0 / np.pi)
+
+    if angle > 180.0:
+        angle = 360 - angle
+
+    return angle
+
+# Function to check shoulder press posture
+def is_shoulder_press_correct(landmarks, mp_pose):
+    # Get coordinates of shoulder, elbow, and wrist (left arm as example)
+    shoulder = [landmarks[mp_pose.PoseLandmark.LEFT_SHOULDER.value].x,
+                landmarks[mp_pose.PoseLandmark.LEFT_SHOULDER.value].y]
+    elbow = [landmarks[mp_pose.PoseLandmark.LEFT_ELBOW.value].x,
+             landmarks[mp_pose.PoseLandmark.LEFT_ELBOW.value].y]
+    wrist = [landmarks[mp_pose.PoseLandmark.LEFT_WRIST.value].x,
+             landmarks[mp_pose.PoseLandmark.LEFT_WRIST.value].y]
+
+    # Calculate angle at the elbow (shoulder, elbow, wrist)
+    elbow_angle = calculate_angle(shoulder, elbow, wrist)
+
+    # Check if the motion is vertical (wrist higher than elbow)
+    if wrist[1] < elbow[1] and elbow[1] < shoulder[1]:
+        # Ensure proper angle range for a shoulder press
+        if 160 <= elbow_angle <= 180:
+            return "Shoulder Press: Correct", True
+        else:
+            return "Shoulder Press: Incorrect - Elbow angle", False
+    else:
+        return "Shoulder Press: Incorrect - Alignment", False
+
+# Video processing function
+def process_video(video_path):
+    cap = cv2.VideoCapture(video_path)
+    count = 0
+    rep_started = False
+
+    with mp_pose.Pose(min_detection_confidence=0.5, min_tracking_confidence=0.5) as pose:
+        while cap.isOpened():
+            ret, frame = cap.read()
+            if not ret:
+                break
+
+            # Convert the frame to RGB
+            image = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+            image.flags.writeable = False
+
+            # Process the image for pose detection
+            results = pose.process(image)
+
+            # Convert back to BGR for rendering
+            image.flags.writeable = True
+            image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
+
+            # Extract landmarks
+            if results.pose_landmarks:
+                landmarks = results.pose_landmarks.landmark
+
+                # Check shoulder press posture
+                feedback, is_correct = is_shoulder_press_correct(landmarks, mp_pose)
+
+                # Count reps
+                if is_correct and not rep_started:
+                    rep_started = True
+                elif not is_correct and rep_started:
+                    rep_started = False
+                    count += 1
+
+                # Display feedback
+                cv2.putText(image, feedback, (50, 50),
+                            cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0) if is_correct else (0, 0, 255), 2, cv2.LINE_AA)
+
+                # Display rep count
+                cv2.putText(image, f'Reps: {count}', (50, 100),
+                            cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255), 2, cv2.LINE_AA)
+
+                # Draw landmarks
+                mp_drawing.draw_landmarks(image, results.pose_landmarks, mp_pose.POSE_CONNECTIONS)
+
+            else:
+                # Warn if no landmarks are detected
+                cv2.putText(image, "No body detected", (50, 50),
+                            cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2, cv2.LINE_AA)
+
+            # Encode frame for streaming
+            ret, buffer = cv2.imencode('.jpg', image)
+            frame = buffer.tobytes()
+            yield (b'--frame\r\n'
+                   b'Content-Type: image/jpeg\r\n\r\n' + frame + b'\r\n')
+
+    cap.release()
+
+@app.route('/')
+def index():
+    return render_template('index.html')
+
+@app.route('/upload', methods=['POST'])
+def upload():
+    if 'video' not in request.files:
+        return "No video file uploaded", 400
+
+    video = request.files['video']
+    video_path = os.path.join('uploads', video.filename)
+    video.save(video_path)
+
+    return Response(process_video(video_path), mimetype='multipart/x-mixed-replace; boundary=frame')
+
+if __name__ == "__main__":
+    app.run(debug=True)

requirements.txt

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+Flask
+opencv-python-headless
+mediapipe
+numpy
+gunicorn

templates/index.html

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+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Shoulder Press Detection</title>
+</head>
+<body>
+    <h1>Upload Your Shoulder Press Video</h1>
+    <form action="/upload" method="post" enctype="multipart/form-data">
+        <input type="file" name="video" accept="video/*" required>
+        <button type="submit">Upload and Analyze</button>
+    </form>
+</body>
+</html>