AI智能人脸识别，抠图

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AI智能人脸识别，抠图

2023-06-26 07:58| 来源: 网络整理| 查看: 265

效果展示：在这里插入图片描述关键代码：

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

【本文地址】

AI智能人脸识别，抠图

AI智能人脸识别，抠图

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