32 lines
1.1 KiB
Python
32 lines
1.1 KiB
Python
import cv2 as cv
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import os
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import tqdm
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# 处理图像
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def pretrain(img_path,output_path):
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img=cv.imread(img_path, cv.IMREAD_GRAYSCALE)
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_,img=cv.threshold(img,127,255,cv.THRESH_BINARY)
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img=cv.blur(img,(3,3))
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os.makedirs(os.path.dirname(output_path), exist_ok=True)
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cv.imwrite(output_path, img)
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# 获取文件路径
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def get_img_name(directory, extensions=None):
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if extensions is None:
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extensions = ['.png', '.jpg','.jpeg']
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files = []
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for root, dirs, file_names in os.walk(directory):
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for file_name in file_names:
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if any(file_name.lower().endswith(ext) for ext in extensions):
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files.append(os.path.join(root, file_name))
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return files
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# 处理人脸数据集
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os.makedirs('cache/pretrained/face/', exist_ok=True)
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face_files=get_img_name('cache/dataset/face/')
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print('预处理人脸数据中：')
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for img_path in tqdm.tqdm(face_files):
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relative_path=os.path.relpath(img_path, 'cache/dataset/face/')
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output_path=os.path.join('cache/pretrained/face', relative_path)
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pretrain(img_path, output_path)
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