Update app.py

app.py

@@ -10,7 +10,6 @@ import numpy as np
 import matplotlib.pyplot as plt
 import tempfile
 import os
-from dataclasses import dataclass
 
 # Initialize MediaPipe
 mp_pose = mp.solutions.pose
@@ -38,10 +37,10 @@ LANDMARKS = {
 # Optimal angle ranges for bike fitting
 OPTIMAL_RANGES = {
     'torso_angle': (80, 90),
-    'hip_angle': (38, 46),
-    'knee_angle': (140, 148),
-    'ankle_angle': (90, 100),
-    'elbow_angle': (150, 170),
+    'hip_angle': (60, 100),
+    'knee_angle': (75, 160),
+    'ankle_angle': (90, 130),
+    'elbow_angle': (150, 175),
 }
 
 ANGLE_DESCRIPTIONS = {
@@ -209,82 +208,14 @@ def create_plots(angle_history):
     return plot_path
 
 
-def generate_recommendations(angle_history):
-    """Generate bike fitting recommendations."""
-    if not angle_history:
-        return "No pose data detected. Please ensure the cyclist is visible in the video."
-    
-    # Calculate statistics
-    stats = {}
-    for name in ['torso_angle', 'hip_angle', 'knee_angle', 'ankle_angle', 'elbow_angle']:
-        values = [a[name] for a in angle_history]
-        stats[name] = {
-            'mean': np.mean(values),
-            'min': np.min(values),
-            'max': np.max(values),
-            'std': np.std(values),
-        }
-    
-    report = "## 🚴 Bike Fitting Analysis Report\n\n"
-    report += "### 📊 Angle Summary\n\n"
-    report += "| Angle | Mean | Range | Optimal | Status |\n"
-    report += "|-------|------|-------|---------|--------|\n"
-    
-    for name, s in stats.items():
-        opt = OPTIMAL_RANGES.get(name, (0, 180))
-        mean = s['mean']
-        
-        if opt[0] <= mean <= opt[1]:
-            status = "✅ Good"
-        elif mean < opt[0]:
-            status = f"⬆️ +{opt[0] - mean:.0f}°"
-        else:
-            status = f"⬇️ -{mean - opt[1]:.0f}°"
-        
-        report += f"| {ANGLE_DESCRIPTIONS[name]} | {mean:.1f}° | {s['min']:.0f}°-{s['max']:.0f}° | {opt[0]}-{opt[1]}° | {status} |\n"
-    
-    report += "\n### 💡 Recommendations\n\n"
-    
-    # Knee angle recommendations
-    knee_max = stats['knee_angle']['max']
-    if knee_max < 140:
-        report += "**🔧 Saddle Height**: Consider **raising** the saddle. "
-        report += f"Your knee extension at the bottom of the stroke ({knee_max:.0f}°) is below optimal (140-148°). "
-        report += "This limits power output and may cause knee strain.\n\n"
-    elif knee_max > 155:
-        report += "**🔧 Saddle Height**: Consider **lowering** the saddle. "
-        report += f"Your knee is over-extending ({knee_max:.0f}°) which can cause injury.\n\n"
-    else:
-        report += "**✅ Saddle Height**: Looks good! Knee extension is within optimal range.\n\n"
-    
-    # Torso angle recommendations
-    torso_mean = stats['torso_angle']['mean']
-    if torso_mean < 75:
-        report += "**🔧 Handlebar Position**: Very aggressive position. "
-        report += "Consider raising handlebars if you experience back or neck pain.\n\n"
-    elif torso_mean > 95:
-        report += "**🔧 Handlebar Position**: Upright position. "
-        report += "Good for comfort, but may reduce aerodynamic efficiency for racing.\n\n"
-    else:
-        report += "**✅ Torso Position**: Good balance of comfort and aerodynamics.\n\n"
-    
-    # Hip angle recommendations
-    hip_min = stats['hip_angle']['min']
-    if hip_min < 35:
-        report += "**🔧 Saddle Position**: Hip angle closes too much at top of stroke. "
-        report += "Consider moving saddle back slightly.\n\n"
-    
-    return report
-
-
 def process_video(video_path, side, progress=gr.Progress()):
     """Main processing function."""
     if video_path is None:
-        return None, None, "Please upload a video."
+        return None, None
     
     cap = cv2.VideoCapture(video_path)
     if not cap.isOpened():
-        return None, None, "Could not open video file."
+        return None, None
     
     fps = int(cap.get(cv2.CAP_PROP_FPS)) or 30
     width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
@@ -300,7 +231,7 @@ def process_video(video_path, side, progress=gr.Progress()):
     
     with mp_pose.Pose(
         static_image_mode=False,
-        model_complexity=1,
+        model_complexity=2,
         min_detection_confidence=0.5,
         min_tracking_confidence=0.5
     ) as pose:
@@ -339,11 +270,10 @@ def process_video(video_path, side, progress=gr.Progress()):
     web_output = tempfile.mktemp(suffix='.mp4')
     os.system(f'ffmpeg -y -i "{output_path}" -vcodec libx264 -acodec aac "{web_output}" -hide_banner -loglevel error')
     
-    # Generate outputs
+    # Generate plot
     plot_path = create_plots(angle_history)
-    recommendations = generate_recommendations(angle_history)
     
-    return web_output, plot_path, recommendations
+    return web_output, plot_path
 
 
 # Build Gradio interface
@@ -365,7 +295,7 @@ with gr.Blocks(title="🚴 AI Bike Fitting Analyzer", theme=gr.themes.Soft()) as
         with gr.Column(scale=1):
             video_input = gr.Video(label="📹 Upload Video")
             side_select = gr.Radio(
-                choices=["right", "left"],
+                choices=["left", "right"],
                 value="right",
                 label="Which side of the cyclist faces the camera?"
             )
@@ -377,26 +307,11 @@ with gr.Blocks(title="🚴 AI Bike Fitting Analyzer", theme=gr.themes.Soft()) as
     with gr.Row():
         plot_output = gr.Image(label="📊 Angle Analysis Over Time")
     
-    with gr.Row():
-        recommendations_output = gr.Markdown(label="💡 Recommendations")
-    
     analyze_btn.click(
         fn=process_video,
         inputs=[video_input, side_select],
-        outputs=[video_output, plot_output, recommendations_output],
+        outputs=[video_output, plot_output],
     )
-    
-    gr.Markdown("""
-    ---
-    **How it works:** Uses [MediaPipe BlazePose](https://google.github.io/mediapipe/solutions/pose.html) 
-    to detect 33 body keypoints and calculates joint angles relevant to bike fitting.
-    
-    **Key angles analyzed:**
-    - **Torso**: Elbow-shoulder-hip angle (optimal: 80-90°)
-    - **Hip**: Shoulder-hip-knee angle (optimal: 38-46°)  
-    - **Knee**: Hip-knee-ankle angle at bottom of stroke (optimal: 140-148°)
-    - **Ankle**: Knee-ankle-foot angle (optimal: 90-100°)
-    """)
 
 
 if __name__ == "__main__":