first commit

image_qualified.py

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