import cv2
import cvzone
import numpy as np
import os
import gradio as gr

# Load the YuNet model
model_path = 'face_detection_yunet_2023mar.onnx'
face_detector = cv2.FaceDetectorYN.create(model_path, "", (320, 320))

# Initialize the glass number
num = 1
overlay = cv2.imread(f'glasses/glass{num}.png', cv2.IMREAD_UNCHANGED)

# Count glasses files
def count_files_in_directory(directory):
    file_count = 0
    for root, dirs, files in os.walk(directory):
        file_count += len(files)
    return file_count

directory_path = 'glasses'
total_glass_num = count_files_in_directory(directory_path)

# Change glasses
def change_glasses():
    global num, overlay
    num += 1
    if num > total_glass_num:
        num = 1
    overlay = cv2.imread(f'glasses/glass{num}.png', cv2.IMREAD_UNCHANGED)
    return overlay

# Process frame for overlay
def process_frame(frame):
    global overlay
    height, width = frame.shape[:2]
    face_detector.setInputSize((width, height))
    
    # Detect faces
    _, faces = face_detector.detect(frame)
    if faces is not None:
        for face in faces:
            # Extract bounding box and facial landmarks
            x, y, w, h = face[:4].astype(int)
            face_landmarks = face[4:14].reshape(5, 2).astype(int)  # Adjust if needed

            # Get the nose and eye positions
            nose_x, nose_y = face_landmarks[2]
            left_eye_x, left_eye_y = face_landmarks[0]
            right_eye_x, right_eye_y = face_landmarks[1]

            # Calculate eye center and rotation angle
            eye_center_x = (left_eye_x + right_eye_x) // 2
            eye_center_y = (left_eye_y + right_eye_y) // 2
            delta_x = right_eye_x - left_eye_x
            delta_y = right_eye_y - left_eye_y
            angle = np.degrees(np.arctan2(delta_y, delta_x))

            # Resize and rotate the overlay
            overlay_resize = cv2.resize(overlay, (int(w * 1.15), int(h * 0.8)))
            overlay_center = (overlay_resize.shape[1] // 2, overlay_resize.shape[0] // 2)
            rotation_matrix = cv2.getRotationMatrix2D(overlay_center, angle, 1.0)
            overlay_rotated = cv2.warpAffine(
                overlay_resize, rotation_matrix, 
                (overlay_resize.shape[1], overlay_resize.shape[0]), 
                flags=cv2.INTER_LINEAR, borderMode=cv2.BORDER_CONSTANT, borderValue=(0, 0, 0, 0)
            )

            # Calculate position for overlay
            overlay_x = max(0, eye_center_x - overlay_rotated.shape[1] // 2)
            overlay_y = max(0, eye_center_y - overlay_rotated.shape[0] // 2)

            # Overlay the glasses using cvzone
            try:
                frame = cvzone.overlayPNG(frame, overlay_rotated, [overlay_x, overlay_y])
            except Exception as e:
                print(f"Error overlaying glasses: {e}")

    return frame


# Gradio webcam input
def webcam_input(frame):
    frame = process_frame(frame)
    return frame

# Gradio Interface
with gr.Blocks() as demo:
    with gr.Row():
        with gr.Column():
            input_img = gr.Image(label="Input", sources="webcam", streaming=True)
            next_button = gr.Button("Next Glasses")
    input_img.stream(webcam_input, [input_img], [input_img], stream_every=0.1, concurrency_limit=30)
    next_button.click(change_glasses, [], [])
if __name__ == "__main__":
    demo.launch(share=True)