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| # Pose-Think: AI-Powered Movement Analysis Suite - Gradio 4.8.0 Compatible | |
| import cv2 | |
| import mediapipe as mp | |
| import gradio as gr | |
| import numpy as np | |
| # MediaPipe initialization | |
| mp_pose = mp.solutions.pose | |
| mp_hands = mp.solutions.hands | |
| mp_drawing = mp.solutions.drawing_utils | |
| def analyze_posture(image, analysis_type="basic", age=None, height=None, weight=None): | |
| """Main analysis function compatible with Gradio 4.8.0""" | |
| if image is None: | |
| return None, "❌ No image / Görüntü yok" | |
| # Convert BGR to RGB | |
| rgb_image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) | |
| output_image = cv2.cvtColor(rgb_image, cv2.COLOR_RGB2BGR) | |
| feedback = [] | |
| # Profile info for enhanced mode | |
| if analysis_type == "enhanced" and (age or height or weight): | |
| profile_info = [] | |
| if age: | |
| profile_info.append(f"Age: {age}") | |
| if height and weight: | |
| bmi = weight / ((height/100) ** 2) | |
| profile_info.append(f"BMI: {bmi:.1f}") | |
| if bmi > 25: | |
| feedback.append("⚠️ BMI high - extra load on posture") | |
| if profile_info: | |
| feedback.append(f"👤 Profile: {' | '.join(profile_info)}") | |
| feedback.append("") | |
| if analysis_type == "hand": | |
| # Hand analysis | |
| with mp_hands.Hands( | |
| static_image_mode=False, | |
| max_num_hands=2, | |
| min_detection_confidence=0.5, | |
| min_tracking_confidence=0.5 | |
| ) as hands: | |
| results = hands.process(rgb_image) | |
| if results.multi_hand_landmarks: | |
| hand_count = len(results.multi_hand_landmarks) | |
| feedback.append(f"✅ {hand_count} hands detected") | |
| for idx, hand_landmarks in enumerate(results.multi_hand_landmarks): | |
| mp_drawing.draw_landmarks(output_image, hand_landmarks, mp_hands.HAND_CONNECTIONS) | |
| # Simple finger counting | |
| landmarks = hand_landmarks.landmark | |
| fingers_up = 0 | |
| tip_ids = [4, 8, 12, 16, 20] | |
| pip_ids = [3, 6, 10, 14, 18] | |
| for i in range(5): | |
| if landmarks[tip_ids[i]].y < landmarks[pip_ids[i]].y: | |
| fingers_up += 1 | |
| feedback.append(f"🖐️ Hand {idx+1}: {fingers_up} fingers up") | |
| else: | |
| feedback.append("❌ No hands detected") | |
| feedback.append("🖐️ Show your hands to the camera") | |
| else: | |
| # Posture analysis | |
| with mp_pose.Pose( | |
| static_image_mode=False, | |
| model_complexity=1, | |
| enable_segmentation=False, | |
| min_detection_confidence=0.5, | |
| min_tracking_confidence=0.5 | |
| ) as pose: | |
| results = pose.process(rgb_image) | |
| if results.pose_landmarks: | |
| mp_drawing.draw_landmarks(output_image, results.pose_landmarks, mp_pose.POSE_CONNECTIONS) | |
| landmarks = results.pose_landmarks.landmark | |
| visible_parts = [] | |
| # Check visible parts | |
| if landmarks[mp_pose.PoseLandmark.NOSE.value].visibility > 0.5: | |
| visible_parts.append("Head") | |
| # Shoulders | |
| left_shoulder = landmarks[mp_pose.PoseLandmark.LEFT_SHOULDER.value] | |
| right_shoulder = landmarks[mp_pose.PoseLandmark.RIGHT_SHOULDER.value] | |
| if left_shoulder.visibility > 0.5 and right_shoulder.visibility > 0.5: | |
| visible_parts.append("Shoulders") | |
| # Shoulder level check | |
| shoulder_diff = abs(left_shoulder.y - right_shoulder.y) | |
| if shoulder_diff > 0.05: | |
| if left_shoulder.y < right_shoulder.y: | |
| feedback.append("⚠️ Left shoulder higher") | |
| else: | |
| feedback.append("⚠️ Right shoulder higher") | |
| else: | |
| feedback.append("✅ Shoulders level") | |
| # Elbows and angles | |
| left_elbow = landmarks[mp_pose.PoseLandmark.LEFT_ELBOW.value] | |
| right_elbow = landmarks[mp_pose.PoseLandmark.RIGHT_ELBOW.value] | |
| if left_elbow.visibility > 0.5 and right_elbow.visibility > 0.5: | |
| visible_parts.append("Elbows") | |
| # Calculate elbow angles | |
| try: | |
| def calculate_angle(a, b, c): | |
| a = np.array(a) | |
| b = np.array(b) | |
| c = np.array(c) | |
| 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 | |
| # Left elbow angle | |
| left_shoulder_pos = [left_shoulder.x, left_shoulder.y] | |
| left_elbow_pos = [left_elbow.x, left_elbow.y] | |
| left_wrist_pos = [landmarks[mp_pose.PoseLandmark.LEFT_WRIST.value].x, | |
| landmarks[mp_pose.PoseLandmark.LEFT_WRIST.value].y] | |
| left_angle = calculate_angle(left_shoulder_pos, left_elbow_pos, left_wrist_pos) | |
| feedback.append(f"📐 Left elbow: {left_angle:.1f}°") | |
| # Right elbow angle | |
| right_shoulder_pos = [right_shoulder.x, right_shoulder.y] | |
| right_elbow_pos = [right_elbow.x, right_elbow.y] | |
| right_wrist_pos = [landmarks[mp_pose.PoseLandmark.RIGHT_WRIST.value].x, | |
| landmarks[mp_pose.PoseLandmark.RIGHT_WRIST.value].y] | |
| right_angle = calculate_angle(right_shoulder_pos, right_elbow_pos, right_wrist_pos) | |
| feedback.append(f"📐 Right elbow: {right_angle:.1f}°") | |
| except: | |
| feedback.append("⚠️ Cannot calculate elbow angles") | |
| # Hips | |
| left_hip = landmarks[mp_pose.PoseLandmark.LEFT_HIP.value] | |
| right_hip = landmarks[mp_pose.PoseLandmark.RIGHT_HIP.value] | |
| if left_hip.visibility > 0.5 and right_hip.visibility > 0.5: | |
| visible_parts.append("Hips") | |
| hip_diff = abs(left_hip.y - right_hip.y) | |
| if hip_diff > 0.03: | |
| if left_hip.y < right_hip.y: | |
| feedback.append("⚠️ Left hip higher") | |
| else: | |
| feedback.append("⚠️ Right hip higher") | |
| else: | |
| feedback.append("✅ Hips level") | |
| # Neck position | |
| nose = landmarks[mp_pose.PoseLandmark.NOSE.value] | |
| if nose.visibility > 0.5: | |
| shoulder_center_x = (left_shoulder.x + right_shoulder.x) / 2 | |
| head_offset = abs(nose.x - shoulder_center_x) | |
| if head_offset > 0.08: | |
| if nose.x < shoulder_center_x: | |
| feedback.append("🔍 Neck tilted left") | |
| else: | |
| feedback.append("🔍 Neck tilted right") | |
| else: | |
| feedback.append("🔍 Neck centered") | |
| # Age-specific recommendations for enhanced mode | |
| if analysis_type == "enhanced" and age: | |
| feedback.append("") | |
| feedback.append("🎯 Age-Specific Recommendations:") | |
| if age < 25: | |
| feedback.append("💡 Young age: Form good posture habits now") | |
| elif age < 45: | |
| feedback.append("💡 Middle age: Regular exercise important") | |
| else: | |
| feedback.append("💡 Mature age: Focus on bone health") | |
| # List visible parts | |
| if visible_parts: | |
| feedback.insert(0, f"✅ Visible: {', '.join(visible_parts)}") | |
| feedback.insert(1, "") | |
| else: | |
| feedback.append("❌ Body not detected") | |
| feedback.append("📍 Stand so full body is visible to camera") | |
| return output_image, "\n".join(feedback) | |
| # Simple Gradio Interface compatible with 4.8.0 | |
| with gr.Blocks(title="🎯 Pose-Think: AI Movement Analysis") as demo: | |
| gr.Markdown(""" | |
| # 🎯 Pose-Think: AI-Powered Movement Analysis Suite | |
| ## Real-time posture and movement analysis with multiple modes | |
| **Choose your analysis type and get instant feedback on what the camera sees!** | |
| """) | |
| with gr.Row(): | |
| with gr.Column(): | |
| # Analysis type selection | |
| analysis_type = gr.Radio( | |
| choices=[ | |
| ("🎯 Basic Posture", "basic"), | |
| ("🎯 Enhanced Posture", "enhanced"), | |
| ("🤚 Hand Tracking", "hand") | |
| ], | |
| value="basic", | |
| label="Analysis Type" | |
| ) | |
| # Profile info (for enhanced mode) | |
| gr.Markdown("### 👤 Optional Profile (for Enhanced mode)") | |
| age_input = gr.Number(label="Age", minimum=10, maximum=100, value=None) | |
| height_input = gr.Number(label="Height (cm)", minimum=100, maximum=250, value=None) | |
| weight_input = gr.Number(label="Weight (kg)", minimum=30, maximum=200, value=None) | |
| # Camera input | |
| input_image = gr.Image(sources=["webcam"], label="📹 Camera") | |
| # Analysis button | |
| analyze_btn = gr.Button("🔍 Analyze", variant="primary", size="lg") | |
| with gr.Column(): | |
| # Outputs | |
| output_image = gr.Image(label="🎯 Analysis Result") | |
| feedback_text = gr.Textbox( | |
| label="📊 Detailed Feedback", | |
| lines=15, | |
| interactive=False | |
| ) | |
| # Analysis function | |
| analyze_btn.click( | |
| fn=analyze_posture, | |
| inputs=[input_image, analysis_type, age_input, height_input, weight_input], | |
| outputs=[output_image, feedback_text] | |
| ) | |
| # Usage instructions | |
| gr.Markdown(""" | |
| ## 📋 How to Use | |
| ### 🎯 **Analysis Types:** | |
| - **Basic Posture**: Body parts, joint angles, alignment | |
| - **Enhanced Posture**: Basic + age/BMI insights + personalized recommendations | |
| - **Hand Tracking**: Hand detection and finger counting | |
| ### 📝 **Instructions:** | |
| 1. **Choose analysis type** from the radio buttons | |
| 2. **Allow camera access** when prompted by your browser | |
| 3. **Position yourself** 2-3 meters from camera (full body visible for posture) | |
| 4. **For Enhanced mode**: Optionally enter age/height/weight for personalized insights | |
| 5. **Click Analyze** to get instant detailed feedback | |
| ### 🎯 **What you'll see:** | |
| - ✅ **Green checkmarks**: Good alignment/posture | |
| - ⚠️ **Warning signs**: Issues detected that need attention | |
| - 📐 **Measurements**: Joint angles in degrees | |
| - 🔍 **Position info**: Head, neck, shoulder positions | |
| - 👤 **Profile insights**: Age-specific recommendations (Enhanced mode) | |
| ### 💡 **Tips for best results:** | |
| - **Good lighting**: Ensure even, bright lighting | |
| - **Plain background**: Use contrasting, simple background | |
| - **Stable position**: Minimize movement during analysis | |
| - **Full visibility**: Keep target body parts clearly visible | |
| """) | |
| if __name__ == "__main__": | |
| demo.launch() | |