app.py

import cv2
import gradio as gr
import numpy as np
from ultralytics import YOLO

# Load the trained YOLO model
model = YOLO('best.pt')  # Replace with your trained model file

def detect_packages(frame):
    results = model(frame)
    for result in results:
        for box in result.boxes:
            x1, y1, x2, y2 = map(int, box.xyxy[0])
            cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 0, 255), 3)
    return frame

def vid_inf(vid_path, contour_thresh):
    cap = cv2.VideoCapture(vid_path)
    frame_width = int(cap.get(3))
    frame_height = int(cap.get(4))
    fps = int(cap.get(cv2.CAP_PROP_FPS))
    frame_size = (frame_width, frame_height)
    fourcc = cv2.VideoWriter_fourcc(*'mp4v')
    output_video = "output_recorded.mp4"
    out = cv2.VideoWriter(output_video, fourcc, fps, frame_size)
    
    if not cap.isOpened():
        print("Error opening video file")
        return None, None
    
    count = 0
    while cap.isOpened():
        ret, frame = cap.read()
        if ret:
            frame_out = detect_packages(frame.copy())
            frame_out_final = cv2.cvtColor(frame_out, cv2.COLOR_BGR2RGB)
            out.write(frame_out)
            
            if not count % 12:
                yield frame_out_final, None
            count += 1
        else:
            break
    
    cap.release()
    out.release()
    cv2.destroyAllWindows()
    yield None, output_video

# Gradio Interface
input_video = gr.Video(label="Input Video")
contour_thresh = gr.Slider(0, 10000, value=4, label="Contour Threshold", info="Adjust the Contour Threshold according to the object size that you want to detect.")
output_frames = gr.Image(label="Output Frames")
output_video_file = gr.Video(label="Output Video")

app = gr.Interface(
    fn=vid_inf,
    inputs=[input_video, contour_thresh],
    outputs=[output_frames, output_video_file],
    title="Motion Detection using YOLOv8",
    description="A Gradio app for dynamic video analysis using YOLOv8 to track labeled packages while ignoring other moving objects.",
    allow_flagging="never",
    examples=[["./sample/package_test.mp4", "1000"]],
    cache_examples=False,
)

app.queue().launch()