YOLOv4.py

import cv2
import numpy as np
from ultralytics import YOLO

# Load YOLOv8 model
model = YOLO('yolov8n.pt')  # You can use other versions like 'yolov8s.pt' or 'yolov8m.pt'

# Initialize webcam (change to video file path if needed)
video_source = 0  # Use 0 for the default webcam
cap = cv2.VideoCapture(video_source)

# Function to display results
def draw_detections(frame, results):
    for result in results:
        for box in result.boxes:
            x1, y1, x2, y2 = map(int, box.xyxy[0])  # Bounding box coordinates
            conf = box.conf[0]  # Confidence score
            cls = int(box.cls[0])  # Class ID
            label = f"{model.names[cls]} {conf:.2f}"

            # Draw bounding box and label
            cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 255, 0), 2)
            cv2.putText(frame, label, (x1, y1 - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)
    return frame

print("Starting object detection... Press 'q' to quit.")
while cap.isOpened():
    ret, frame = cap.read()
    if not ret:
        print("Failed to grab frame. Exiting...")
        break

    # Run YOLO detection
    results = model(frame)

    # Draw detections on the frame
    frame = draw_detections(frame, results)

    # Display the frame
    cv2.imshow("Object Detection", frame)

    # Exit on 'q' key press
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

# Release resources
cap.release()
cv2.destroyAllWindows()