Update app.py

app.py

@@ -1,4 +1,26 @@
-def count_unique_trucks(video_path, frame_skip_factor=2):
+import cv2
+import numpy as np
+import torch
+from ultralytics import YOLO
+from sort import Sort
+
+# Load YOLOv12x model
+MODEL_PATH = "yolov12x.pt"
+model = YOLO(MODEL_PATH)
+
+# COCO dataset class ID for truck
+TRUCK_CLASS_ID = 7  # "truck"
+
+# Initialize SORT tracker
+tracker = Sort()
+
+# Minimum confidence threshold for detection
+CONFIDENCE_THRESHOLD = 0.5
+
+# Distance threshold to avoid duplicate counts
+DISTANCE_THRESHOLD = 50
+
+def count_unique_trucks(video_path):
     cap = cv2.VideoCapture(video_path)
     if not cap.isOpened():
         return "Error: Unable to open video file."
@@ -8,7 +30,7 @@ def count_unique_trucks(video_path, frame_skip_factor=2):
 
     # Get FPS of the video
     fps = int(cap.get(cv2.CAP_PROP_FPS))
-    frame_skip = fps * frame_skip_factor  # Skip frames based on the dynamic factor
+    frame_skip = fps * 2  # Skip frames every 5 seconds
 
     frame_count = 0
 
@@ -19,7 +41,7 @@ def count_unique_trucks(video_path, frame_skip_factor=2):
 
         frame_count += 1
         if frame_count % frame_skip != 0:
-            continue  # Skip frames dynamically
+            continue  # Skip frames to process only every 5 seconds
 
         # Run YOLOv12x inference
         results = model(frame, verbose=False)
@@ -67,23 +89,21 @@ def count_unique_trucks(video_path, frame_skip_factor=2):
     return {"Total Unique Trucks": len(unique_truck_ids)}
 
 # Gradio UI function
-def analyze_video(video_file, frame_skip_factor):
-    result = count_unique_trucks(video_file, frame_skip_factor)
+def analyze_video(video_file):
+    result = count_unique_trucks(video_file)
     return "\n".join([f"{key}: {value}" for key, value in result.items()])
 
 # Define Gradio interface
 import gradio as gr
 iface = gr.Interface(
     fn=analyze_video,
-    inputs=[
-        gr.Video(label="Upload Video"),
-        gr.Slider(minimum=1, maximum=10, step=1, value=2, label="Frame Skip Factor"),  # Fixed default value
-    ],
+    inputs=gr.Video(label="Upload Video"),
     outputs=gr.Textbox(label="Analysis Result"),
     title="YOLOv12x Unique Truck Counter",
-    description="Upload a video to count unique trucks using YOLOv12x and SORT tracking. Adjust the frame skip factor to control processing speed."
+    description="Upload a video to count unique trucks using YOLOv12x and SORT tracking."
 )
 
 # Launch the Gradio app
 if __name__ == "__main__":
     iface.launch()
+