Upload app.py

app.py

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+from flask import Flask, render_template, Response, request, jsonify
+from flask_socketio import SocketIO
+from flask_cors import CORS
+import mediapipe as mp
+import cv2
+import numpy as np
+import time
+import os
+
+app = Flask(__name__)
+socketio = SocketIO(app)
+CORS(app)
+
+mp_pose = mp.solutions.pose
+pose = mp_pose.Pose(static_image_mode=False, min_detection_confidence=0.5, min_tracking_confidence=0.5)
+
+previous_keypoints = None
+previous_velocities = None
+previous_time = time.time()
+
+
+@app.route('/')
+def index():
+    return render_template('index.html')
+
+
+@app.route('/web_app')
+def web_app():
+    return render_template('holistic.html')
+
+
+@app.route('/video_app')
+def video_app():
+    return render_template('video_app.html')
+
+
+def process_frame(frame):
+    global previous_keypoints, previous_time, previous_velocities
+    frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+    results = pose.process(frame_rgb)
+
+    if results.pose_landmarks:
+        landmarks = results.pose_landmarks.landmark
+        keypoints = [(lm.x, lm.y, lm.z) for lm in landmarks]
+        current_time = time.time()
+        delta_time = current_time - previous_time
+
+        velocities = []
+        accelerations = []
+        if previous_keypoints:
+            for i, lm in enumerate(landmarks):
+                dx = lm.x - previous_keypoints[i][0]
+                dy = lm.y - previous_keypoints[i][1]
+                dz = lm.z - previous_keypoints[i][2]
+                speed = np.sqrt(dx ** 2 + dy ** 2 + dz ** 2) / delta_time
+                velocities.append(speed)
+
+                acceleration = (speed - previous_velocities[i]) / delta_time if previous_velocities else 0
+                accelerations.append(acceleration)
+
+        previous_keypoints = keypoints
+        previous_velocities = velocities
+        previous_time = current_time
+
+        return {
+            'landmarks': keypoints,
+            'velocities': velocities,
+            'accelerations': accelerations
+        }
+    return None
+
+
+@socketio.on('process_frame')
+def handle_process_frame(data):
+    frame = cv2.imdecode(np.frombuffer(data['frame'], np.uint8), cv2.IMREAD_COLOR)
+    result = process_frame(frame)
+    if result:
+        socketio.emit('pose_data', result)
+
+
+@app.route('/upload_video', methods=['POST'])
+def upload_video():
+    file = request.files.get('video')
+    if file:
+        upload_folder = os.path.join(app.root_path, 'static', 'uploads')
+        if not os.path.exists(upload_folder):
+            os.makedirs(upload_folder)
+        video_path = os.path.join(upload_folder, 'temp_video.mp4')
+        file.save(video_path)
+        return jsonify(success=True, message='Video uploaded successfully')
+    return jsonify(success=False, message='No video file received'), 400
+
+
+@app.route('/video_feed')
+def video_feed():
+    def generate_frames():
+        video_path = os.path.join(app.root_path, 'static', 'uploads', 'temp_video.mp4')
+        if not os.path.exists(video_path):
+            return
+
+        cap = cv2.VideoCapture(video_path)
+        while True:
+            success, frame = cap.read()
+            if not success:
+                break
+            else:
+                result = process_frame(frame)
+                if result:
+                    socketio.emit('pose_data', result)
+                ret, buffer = cv2.imencode('.jpg', frame)
+                frame = buffer.tobytes()
+                yield (b'--frame\r\n'
+                       b'Content-Type: image/jpeg\r\n\r\n' + frame + b'\r\n')
+        cap.release()
+
+    return Response(generate_frames(), mimetype='multipart/x-mixed-replace; boundary=frame')
+
+
+if __name__ == '__main__':
+    os.makedirs(os.path.join(app.root_path, 'static', 'uploads'), exist_ok=True)
+    socketio.run(app, host='0.0.0.0', port=5000, debug=True, allow_unsafe_werkzeug=True)