效果展示：




关键代码：

import numpy as np
import cv2
import os


def crop_face(source_image_path, output_folder_path, tag_width, tag_height):
    face_detector = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')
    #images = os.listdir(input_folder_path)

   # image_path = os.path.join(source_image_path, image)
    img = cv2.imread(source_image_path)

    height, width, channels = img.shape
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    faces = face_detector.detectMultiScale(gray, scaleFactor=1.3, minNeighbors=5, minSize=(30, 30))

    # 无法识别面部的图片
    if len(faces) == 0:
        print(f"No face found in {source_image_path}")
        return

    if len(faces) > 0:
        # 取第一个脸部位置，这里假设一张图片只有一个脸部特征
        x, y, w, h = faces[0]
        expand_w = int(0.5 * w)
        expand_h = int(0.8 * h)
        # 计算扩充后的ROI区域的坐标
        x1 = max(0, x - expand_w)
        y1 = max(0, y - expand_h)
        x2 = min(img.shape[1], x + w + expand_w)
        y2 = min(img.shape[0], y + h + expand_h)


        # 绘制扩充后的ROI区域
        #cv2.rectangle(img, (x1, y1), (x2, y2), (0, 255, 0), 2)

        # 截取扩充后的ROI区域
        roi = img[y1:y2, x1:x2]

        resized = cv2.resize(roi, (tag_width, tag_height), interpolation=cv2.INTER_CUBIC)
        output_path = os.path.join(output_folder_path)
        print(output_path)
        cv2.imwrite(output_path, resized)



if __name__ == "__main__":
    input_folder = r"input/33.jpg"
    output_folder = r"Output"
    # 创建输出目录
    if not os.path.exists(output_folder):
        os.makedirs(output_folder)
    crop_face(input_folder, output_folder+"33.jpg", 295, 413)
    print('Done!')

def resize_image(self, org_img, width, height, color, filename, suffix, config_path):
today = date_util.todaystr()
parent_folder = config_path[‘root_folder’]
static_folder = config_path[‘static’]
temp_folder = config_path[‘temp’]
parent_path = os.path.join(parent_folder, static_folder, today)

    if not os.path.exists(parent_path):
        os.makedirs(parent_path)
    temp_path = os.path.join(parent_folder, temp_folder)
    if not os.path.exists(temp_path):
        os.makedirs(temp_path)

    id_image = os.path.join(parent_path, filename + suffix)

    crop_face(org_img, id_image, int(width), int(height))

    model = onnx_test_image.Matting(model_path='./model/modnet.onnx', input_size=(512, 512))
    model.predict_image(id_image, os.path.join(parent_path, filename + "_cutout.png"),color)



    info = {}
    if width and height:
        width = int(width)
        height = int(height)

        target_image = os.path.join(parent_path, filename + '_finally.jpg')
        resize_image.resize_image(id_image, width, height, target_image)
        target_iamge_cut = os.path.join(static_folder, today, filename + '_finally.jpg')
        info['targetImageCut'] = target_iamge_cut
        print('target_iamge_cut===', target_iamge_cut)

    # 最终图包含背景且切图

    #原图
    source_image = os.path.join(static_folder, today, filename + suffix)
    source_image_not_back = os.path.join(static_folder, today, filename + "_cutout.png")
    print('source_image_not_back===', source_image_not_back)

代码地址：

https://gitee.com/get-help/ai-photo-web