Update app.py

app.py

@@ -4,15 +4,26 @@ import numpy as np
 import os
 import gradio as gr
 
+
+__file__= "HUGGINGFACE _MODELS_AND_SPACES"
+current_dırectory= os.path.dirname(os.path.abspath(__file__))
+folder= os.path.join(current_dırectory,"Cattle_Detection_with_YOLOV8")
+pt= os.path.join(folder, "best.pt")
+py= os.path.join(folder, "Detection_Video.py")
+rqrmt= os.path.join(folder, "requirements.txt")
+example_video= os.path.join(folder, "cows-and-cows-and-cows.mp4")
+output_video= os.path.join(folder, "output_video.mp4")
+
 def fonk(video_path):
   
-  model=YOLO("best.pt")
+  model=YOLO(pt)
   cap=cv2.VideoCapture(video_path)  
 
   frame_width = int(cap.get(3)) 
   frame_height = int(cap.get(4))
   size = (frame_width, frame_height)
-  writer = cv2.VideoWriter("filename.mp4",  
+  output_video= "output_video.mp4"
+  writer = cv2.VideoWriter(output_video,  
                          cv2.VideoWriter_fourcc(*"DIVX"), 
                          10, size) 
 
@@ -25,22 +36,22 @@ def fonk(video_path):
 
     results= model(frame)
     for result in results:
-      box=result.boxes
-
-      x1, y1, x2, y2 = map(int, box.xyxy[0])
-      print(x1, y1, x2, y2)
-      frame= cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 255, 0), 2)
-      output_video= writer.write(frame)
+        if result.boxes is not None and len(result.boxes):
+            box = result.boxes
+            x1, y1, x2, y2 = map(int, box.xyxy[0])
+            print(x1, y1, x2, y2)
+            frame = cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 255, 0), 2)
+            writer.write(frame)
       
       
   writer.release()
   cap.release()
-  return "filename.mp4"
+  return output_video
  
 demo = gr.Interface(fonk,
                     inputs= gr.Video(),
                     outputs=gr.Video(),
-                    examples=["cow-video-cows-mooing-and-grazing-in-a-field.mp4"],
+                    examples=[example_video],
                     title= "cows",
                     cache_examples=True)
 demo.launch()