# Face detection on image or webcam
# Usage: python run_detection.py --image path/to/image.jpg
#        python run_detection.py --webcam

import argparse
import os

import cv2

from uniface.detection import SCRFD, RetinaFace
from uniface.visualization import draw_detections


def process_image(detector, image_path: str, threshold: float = 0.6, save_dir: str = "outputs"):
    image = cv2.imread(image_path)
    if image is None:
        print(f"Error: Failed to load image from '{image_path}'")
        return

    faces = detector.detect(image)

    if faces:
        bboxes = [face["bbox"] for face in faces]
        scores = [face["confidence"] for face in faces]
        landmarks = [face["landmarks"] for face in faces]
        draw_detections(image, bboxes, scores, landmarks, vis_threshold=threshold)

    os.makedirs(save_dir, exist_ok=True)
    output_path = os.path.join(save_dir, f"{os.path.splitext(os.path.basename(image_path))[0]}_out.jpg")
    cv2.imwrite(output_path, image)
    print(f"Output saved: {output_path}")


def run_webcam(detector, threshold: float = 0.6):
    cap = cv2.VideoCapture(0)  # 0 = default webcam
    if not cap.isOpened():
        print("Cannot open webcam")
        return

    print("Press 'q' to quit")

    while True:
        ret, frame = cap.read()
        frame = cv2.flip(frame, 1)  # mirror for natural interaction
        if not ret:
            break

        faces = detector.detect(frame)

        # unpack face data for visualization
        bboxes = [f["bbox"] for f in faces]
        scores = [f["confidence"] for f in faces]
        landmarks = [f["landmarks"] for f in faces]
        draw_detections(frame, bboxes, scores, landmarks, vis_threshold=threshold)

        cv2.putText(frame, f"Faces: {len(faces)}", (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
        cv2.imshow("Face Detection", frame)

        if cv2.waitKey(1) & 0xFF == ord("q"):
            break

    cap.release()
    cv2.destroyAllWindows()


def main():
    parser = argparse.ArgumentParser(description="Run face detection")
    parser.add_argument("--image", type=str, help="Path to input image")
    parser.add_argument("--webcam", action="store_true", help="Use webcam")
    parser.add_argument("--method", type=str, default="retinaface", choices=["retinaface", "scrfd"])
    parser.add_argument("--threshold", type=float, default=0.6, help="Visualization threshold")
    parser.add_argument("--save_dir", type=str, default="outputs")
    args = parser.parse_args()

    if not args.image and not args.webcam:
        parser.error("Either --image or --webcam must be specified")

    detector = RetinaFace() if args.method == "retinaface" else SCRFD()

    if args.webcam:
        run_webcam(detector, args.threshold)
    else:
        process_image(detector, args.image, args.threshold, args.save_dir)


if __name__ == "__main__":
    main()