eye detection with insightface

main.py

import insightface
from insightface.app import FaceAnalysis
import cv2
import numpy as np
import time

input_images = ["face.jpg", "face2.jpg"]

# Initialize the FaceAnalysis module
app = FaceAnalysis()
app.prepare(ctx_id=0, det_size=(640, 640), det_thresh=0.5)

def resize_image(image, max_size=300):
    h, w = image.shape[:2]
    if max(h, w) > max_size:
        if h > w:
            new_h = max_size
            new_w = int(w * (max_size / h))
        else:
            new_w = max_size
            new_h = int(h * (max_size / w))
        image = cv2.resize(image, (new_w, new_h))
    
    # Pad the image to make it 640x640 with the original image centered
    padded_image = np.zeros((640, 640, 3), dtype=np.uint8)
    h, w = image.shape[:2]
    y_offset = (640 - h) // 2
    x_offset = (640 - w) // 2
    padded_image[y_offset:y_offset+h, x_offset:x_offset+w] = image
    
    return padded_image, (x_offset, y_offset, w, h)

def unresize_image(image, original_size):
    x_offset, y_offset, w, h = original_size
    return image[y_offset:y_offset+h, x_offset:x_offset+w]

for image_path in input_images:
    image = cv2.imread(image_path)
    image, original_size = resize_image(image)
    cv2.imwrite("resized_" + image_path, image)
    start_time = time.time()
    faces = app.get(image)
    end_time = time.time()
    detection_time_ms = (end_time - start_time) * 1000
    print(f"Found {len(faces)} faces in {image_path} in {detection_time_ms:.2f} ms")

    for face in faces:
        left_eye_points = [face.landmark_2d_106[35], face.landmark_2d_106[40], 
                           face.landmark_2d_106[39], face.landmark_2d_106[33]]
        right_eye_points = [face.landmark_2d_106[89], face.landmark_2d_106[87], 
                            face.landmark_2d_106[93], face.landmark_2d_106[94]]
        
        left_eye_rect = cv2.boundingRect(np.array(left_eye_points))
        right_eye_rect = cv2.boundingRect(np.array(right_eye_points))
        
        # Enlarge the rectangles by 3 pixels
        left_eye_rect = (left_eye_rect[0] - 3, left_eye_rect[1] - 3,
                         left_eye_rect[2] + 6, left_eye_rect[3] + 6)
        right_eye_rect = (right_eye_rect[0] - 3, right_eye_rect[1] - 3,
                          right_eye_rect[2] + 6, right_eye_rect[3] + 6)
        
        cv2.rectangle(image, left_eye_rect, (0, 255, 0), 1)
        cv2.rectangle(image, right_eye_rect, (0, 255, 0), 1)
                
        unresized_image = unresize_image(image, original_size)
        cv2.imwrite("output_" + image_path, unresized_image)