62 lines
2.7 KiB
Python
62 lines
2.7 KiB
Python
import cv2
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from PIL import Image
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import numpy as np
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import os
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def calculate_clarity_score(image_path,target_size=(512, 512)):
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"""
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计算图片的清晰度评分
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"""
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image = cv2.imread(image_path, cv2.IMREAD_GRAYSCALE)
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image = cv2.resize(image, target_size)
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if image is None:
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raise ValueError(f"无法读取图片：{image_path}")
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return cv2.Laplacian(image, cv2.CV_64F).var()
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def process_images(input_folder, output_folder,clarity_score_threshold):
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if not os.path.exists(input_folder):
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print(f"输入文件夹不存在：{input_folder}")
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return
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for root, dirs, files in os.walk(input_folder):
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print(f'——————正在处理文件夹:{root}, 图片数量:{len(files)}——————')
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i = 0
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for filename in files:
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if not filename.lower().endswith(('.png', '.jpg', '.jpeg', '.bmp', '.gif', '.jfif')):
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continue
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file_path = os.path.join(root, filename)
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# print(f'file_path is {file_path}')
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i+=1
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try:
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# 清晰度检测
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clarity_score = calculate_clarity_score(file_path)
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if clarity_score > clarity_score_threshold:
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# 读取图片
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with Image.open(file_path) as img:
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# resize
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img = img.resize((512, 512))
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# output_subfolder
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relative_path = os.path.relpath(root, input_folder)
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output_subfolder = os.path.join(output_folder, relative_path)
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# print(f'root: {root}, input_folder: {input_folder}, relative_path: {relative_path}, output_subfolder: {output_subfolder}')
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if not os.path.exists(output_subfolder):
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os.makedirs(output_subfolder)
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output_path = os.path.join(output_subfolder, os.path.splitext(filename)[0] + ".png")
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img.save(output_path, format="PNG")
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print(f"处理并保存图片{i}:{file_path} -> {output_path}")
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else:
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print(f"********图片 {file_path} 清晰度评分 {clarity_score} 不满足要求，跳过********")
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except Exception as e:
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print(f"********处理图片 {file_path} 时出错：{e}********")
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if __name__ == "__main__":
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input_folder = 'data_process/datasets/source' # 输入文件夹路径
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output_folder = 'data_process/datasets/target' # 输出文件夹路径
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clarity_score_threshold =50
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process_images(input_folder, output_folder,clarity_score_threshold)
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