import gradio as gr
import cv2
from ultralytics import YOLO

def object_detection():
    
    model=YOLO("/home/kahraman/Masaüstü/HuggingFace_Models_and_Spaces/yolov8_model_on_custom_data/best.pt")
    
    source="/home/kahraman/Masaüstü/HuggingFace_Models_and_Spaces/yolov8_model_on_custom_data/cow-video-cows-mooing-and-grazing-in-a-field.mp4"
    
    cap = cv2.VideoCapture(source)
    
    while True:
        ret, frame = cap.read()
    
        if not ret:
            break
    
        results = model(frame)
        for result in results:
            box=result.boxes
            
            x1, y1, x2, y2 = map(int, box.xyxy[0])
            print(x1, y1, x2, y2)
            cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 255, 0), 2)
    
        cv2.imshow("img", frame)
        
        if cv2.waitKey(1) & 0xFF == ord("q"):
            break
    
    cap.release()
    cv2.destroyAllWindows()


iface = gr.Interface(
    fn=object_detection,
    inputs="text",
    outputs="text",
    layout="vertical",
    title="Sığır Object Detection",
    description="Bir sığır videosu bırakın ve videoda ki sığırların yakalayın."
)

iface.launch(share=True)