Update app.py

app.py

@@ -1,52 +1,12 @@
 import gradio as gr
-import cv2
-import os
-import tempfile
-from ultralytics import YOLO
+from drs_engine import process_video
 
-# ✅ Load the model
-try:
-    model = YOLO("best.pt")
-except:
-    print("⚠️ Failed to load best.pt, falling back to yolov8n.pt")
-    model = YOLO("yolov8n.pt")
-
-# ✅ Core logic: process video frame-by-frame
-def process_video(video_path):
-    cap = cv2.VideoCapture(video_path)
-    if not cap.isOpened():
-        raise Exception("❌ Failed to open video file")
-
-    width  = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
-    height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
-    fps    = int(cap.get(cv2.CAP_PROP_FPS))
-    fourcc = cv2.VideoWriter_fourcc(*'mp4v')
-
-    # ✅ Output file path
-    out_path = tempfile.NamedTemporaryFile(suffix=".mp4", delete=False).name
-    out = cv2.VideoWriter(out_path, fourcc, fps, (width, height))
-
-    while True:
-        ret, frame = cap.read()
-        if not ret:
-            break
-
-        results = model(frame)
-        annotated = results[0].plot()
-        out.write(annotated)
-
-    cap.release()
-    out.release()
-
-    return out_path
-
-# ✅ Gradio UI
 demo = gr.Interface(
     fn=process_video,
     inputs=gr.Video(label="Upload Cricket Video (.mp4)"),
-    outputs=gr.Video(label="DRS-Processed Output"),
-    title="🏏 GullyDRS - DRS Video Ball Tracker",
-    description="Upload a cricket delivery video. The app will detect and track the ball using YOLOv8, overlay its path, and return a processed video."
+    outputs=gr.Video(label="DRS Result Video"),
+    title="🏏 GullyDRS - Ball Tracking & LBW Decision",
+    description="Upload a delivery video. This system will track the ball, estimate speed, detect bounce, apply simplified DRS rules, and overlay the decision: OUT or NOT OUT."
 )
 
 if __name__ == "__main__":