added media pipe folder and uploads

workouts/bicepCurls.py

@@ -0,0 +1,103 @@
+import cv2
+import numpy as np
+import  BasicPoseModule as pm_modified
+import time
+import mediapipe as mp
+import os
+from app import session
+
+
+
+# Initialize Mediapipe Pose
+mp_pose = mp.solutions.pose
+mp_drawing = mp.solutions.drawing_utils
+
+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
+
+
+def bicepcurls(video_path):
+    cap = cv2.VideoCapture(video_path)
+    count = 0
+    movement_dir = 0
+
+    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
+
+            frame = cv2.resize(frame, (1280, 720))
+
+            # 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)
+
+            if results.pose_landmarks:
+                landmarks = results.pose_landmarks.landmark
+
+                # Extract relevant joints
+                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 elbow angle
+                elbow_angle = calculate_angle(shoulder, elbow, wrist)
+
+                # Determine movement direction and count reps
+                progress_percentage = np.interp(elbow_angle, (50, 160), (0, 100))
+                progress_bar = np.interp(elbow_angle, (50, 160), (650, 100))
+
+                color = (255, 0, 255)
+                if progress_percentage == 100:
+                    color = (0, 255, 0)
+                    if movement_dir == 0:
+                        count += 0.5
+                        movement_dir = 1
+                if progress_percentage == 0:
+                    color = (0, 0, 255)
+                    if movement_dir == 1:
+                        count += 0.5
+                        movement_dir = 0
+
+                # Draw Progress Bar
+                cv2.rectangle(frame, (1100, 100), (1175, 650), color, 3)
+                cv2.rectangle(frame, (1100, int(progress_bar)), (1175, 650), color, cv2.FILLED)
+                cv2.putText(frame, f'{int(progress_percentage)}%', (1100, 75), cv2.FONT_HERSHEY_PLAIN, 4, color, 4)
+
+                # Draw Counter
+                cv2.rectangle(frame, (0, 450), (250, 720), (0, 255, 0), cv2.FILLED)
+                cv2.putText(frame, str(int(count)), (45, 670), cv2.FONT_HERSHEY_PLAIN, 15, (255, 0, 0), 30)
+
+                # Draw landmarks
+                mp_drawing.draw_landmarks(frame, results.pose_landmarks, mp_pose.POSE_CONNECTIONS)
+
+            # Encode frame for streaming
+            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()
+    today_date = time.strftime("%Y-%m-%d")
+    session[today_date]['bicepscurls'] = count