Camera Configuration

import cv2

def list_cameras():
    """Test camera indices 0-10 to find available cameras"""
    available = []
    for i in range(10):
        cap = cv2.VideoCapture(i)
        if cap.isOpened():
            ret, frame = cap.read()
            if ret:
                available.append(i)
                print(f"Camera {i}: Available")
                print(f"  Resolution: {cap.get(3)}x{cap.get(4)}")
                print(f"  FPS: {cap.get(5)}")
            cap.release()
    return available

if __name__ == "__main__":
    print("Scanning for cameras...")
    cameras = list_cameras()
    print(f"\nFound {len(cameras)} camera(s): {cameras}")

import cv2

def test_camera_config():
    """Test camera settings and display current configuration"""
    cap = cv2.VideoCapture(0)
    
    # Set desired resolution
    cap.set(3, 1280)
    cap.set(4, 720)
    
    # Check actual values
    width = cap.get(cv2.CAP_PROP_FRAME_WIDTH)
    height = cap.get(cv2.CAP_PROP_FRAME_HEIGHT)
    fps = cap.get(cv2.CAP_PROP_FPS)
    
    print("Camera Configuration:")
    print(f"  Resolution: {int(width)}x{int(height)}")
    print(f"  FPS: {fps}")
    print(f"  Backend: {cap.getBackendName()}")
    
    # Test frame capture
    ret, frame = cap.read()
    if ret:
        print(f"  Frame shape: {frame.shape}")
        print("  Status: Camera working correctly!")
        
        # Display test frame
        cv2.imshow("Camera Test", frame)
        print("\nPress any key to close...")
        cv2.waitKey(0)
    else:
        print("  Status: Failed to capture frame")
    
    cap.release()
    cv2.destroyAllWindows()

if __name__ == "__main__":
    test_camera_config()

import cv2
import time
from ultralytics import YOLO

def benchmark_detection():
    """Measure FPS and processing time"""
    cap = cv2.VideoCapture(0)
    cap.set(3, 1280)
    cap.set(4, 720)
    
    model = YOLO('Modelos/best.pt')
    
    frame_count = 0
    start_time = time.time()
    
    print("Benchmarking... (30 seconds)")
    while time.time() - start_time < 30:
        ret, frame = cap.read()
        if ret:
            results = model(frame, stream=True, verbose=False)
            for res in results:
                pass  # Process results
            frame_count += 1
    
    elapsed = time.time() - start_time
    fps = frame_count / elapsed
    
    print(f"\nResults:")
    print(f"  Frames processed: {frame_count}")
    print(f"  Time elapsed: {elapsed:.2f}s")
    print(f"  Average FPS: {fps:.2f}")
    print(f"  Frame time: {1000/fps:.2f}ms")
    
    cap.release()

if __name__ == "__main__":
    benchmark_detection()