Update app.py

app.py

@@ -4,7 +4,6 @@ import torch
 from ultralytics import YOLO
 import gradio as gr
 from scipy.interpolate import interp1d
-import plotly.graph_objects as go
 import uuid
 import os
 
@@ -45,8 +44,8 @@ def process_video(video_path):
             break
         frame_count += 1
         frames.append(frame.copy())
-        # Use native resolution for inference
-        results = model.predict(frame, conf=CONF_THRESHOLD, imgsz=(frame_height, frame_width), iou=0.5, max_det=1)
+        # Use smaller image size to speed up detection
+        results = model.predict(frame, conf=CONF_THRESHOLD, imgsz=(384, 640), iou=0.5, max_det=1)
         detections = 0
         for detection in results[0].boxes:
             if detection.cls == 0:  # Class 0 is the ball
@@ -146,7 +145,7 @@ def estimate_trajectory(ball_positions, frames, detection_frames):
 
     trajectory_3d = [pixel_to_3d(x, y, frame_height, frame_width) for x, y in trajectory_2d]
     detections_3d = [pixel_to_3d(x, y, frame_height, frame_width) for x, y in filtered_positions]
-    
+
     # Handle missing pitch and impact points gracefully
     pitch_point_3d = pixel_to_3d(pitch_point[0], pitch_point[1], frame_height, frame_width) if pitch_point else None
     impact_point_3d = pixel_to_3d(impact_point[0], impact_point[1], frame_height, frame_width) if impact_point else None
@@ -249,17 +248,9 @@ def drs_review(video):
     output_path = f"output_{uuid.uuid4()}.mp4"
     slow_motion_path = generate_slow_motion(frames, trajectory_2d, pitch_point, impact_point, detection_frames, pitch_frame, impact_frame, output_path)
 
-    detections_fig = None
-    trajectory_fig = None
-    if detections_3d:
-        detections_fig = create_3d_plot(detections_3d, trajectory_3d, pitch_point_3d, impact_point_3d, "detections")
-        trajectory_fig = create_3d_plot(detections_3d, trajectory_3d, pitch_point_3d, impact_point_3d, "trajectory")
-
     debug_output = f"{debug_log}\n{trajectory_log}"
     return (f"DRS Decision: {decision}\nDebug Log:\n{debug_output}", 
-            slow_motion_path, 
-            detections_fig, 
-            trajectory_fig)
+            slow_motion_path)
 
 # Gradio interface
 iface = gr.Interface(
@@ -268,11 +259,9 @@ iface = gr.Interface(
     outputs=[
         gr.Textbox(label="DRS Decision and Debug Log"),
         gr.Video(label="Very Slow-Motion Replay with Ball Detection (Green), Trajectory (Blue Line), Pitch Point (Red), Impact Point (Yellow)"),
-        gr.Plot(label="3D Single Ball Detections Plot"),
-        gr.Plot(label="3D Ball Trajectory Plot (Single Detections)")
     ],
     title="AI-Powered DRS for LBW in Local Cricket",
-    description="Upload a video clip of a cricket delivery to get an LBW decision, a slow-motion replay, and 3D visualizations. The replay shows ball detection (green boxes), trajectory (blue line), pitch point (red circle), and impact point (yellow circle). The 3D plots show single-detection frames (green markers) and trajectory (blue line) with wicket lines (black), pitch point (red), and impact point (yellow)."
+    description="Upload a video clip of a cricket delivery to get an LBW decision, a slow-motion replay, and 3D visualizations. The replay shows ball detection (green boxes), trajectory (blue line), pitch point (red circle), and impact point (yellow circle)."
 )
 
 if __name__ == "__main__":