脚本如何批量调整图片色阶分布

本文目录导读：

1. 使用Python + Pillow库
2. 使用OpenCV + Python
3. 使用ImageMagick命令行工具
4. 使用Photoshop脚本（JavaScript）
5. 使用GIMP批处理
6. 完整的批处理脚本示例
7. 使用建议

使用Python + Pillow库

from PIL import Image, ImageEnhance, ImageOps
import os
import glob
def batch_adjust_levels(input_dir, output_dir, black_point=0, white_point=255):
    """
    批量调整色阶
    black_point: 黑场 (0-255)
    white_point: 白场 (0-255)
    """
    # 创建输出目录
    if not os.path.exists(output_dir):
        os.makedirs(output_dir)
    # 获取所有图片
    for img_path in glob.glob(os.path.join(input_dir, "*.[jJ][pP][gG]")):
        img = Image.open(img_path)
        # 自动色阶调整
        if black_point != 0 or white_point != 255:
            img = ImageOps.autocontrast(img, cutoff=0)
            img = ImageOps.equalize(img)
        # 手动色阶调整
        if black_point > 0 or white_point < 255:
            img = img.point(lambda x: max(0, min(255, 
                (x - black_point) * 255 / (white_point - black_point))))
        # 保存
        output_path = os.path.join(output_dir, os.path.basename(img_path))
        img.save(output_path)
# 使用示例
batch_adjust_levels("input_folder", "output_folder", black_point=20, white_point=235)

使用OpenCV + Python

import cv2
import numpy as np
import os
def batch_adjust_histogram(input_dir, output_dir):
    """使用直方图均衡化"""
    for filename in os.listdir(input_dir):
        if filename.endswith(('.jpg', '.png', '.jpeg')):
            img_path = os.path.join(input_dir, filename)
            img = cv2.imread(img_path)
            # 转换为YUV色彩空间
            img_yuv = cv2.cvtColor(img, cv2.COLOR_BGR2YUV)
            # 对Y通道进行直方图均衡化
            img_yuv[:,:,0] = cv2.equalizeHist(img_yuv[:,:,0])
            # 转换回BGR
            img_equalized = cv2.cvtColor(img_yuv, cv2.COLOR_YUV2BGR)
            # 保存
            output_path = os.path.join(output_dir, filename)
            cv2.imwrite(output_path, img_equalized)

使用ImageMagick命令行工具

# 批量自动色阶
for file in *.jpg; do
  convert "$file" -auto-level "output/${file}"
done
# 批量手动调整色阶（黑点30，白点225）
for file in *.jpg; do
  convert "$file" -level 10%,90% "output/${file}"
done
# 批量归一化
for file in *.jpg; do
  convert "$file" -normalize "output/${file}"
done

使用Photoshop脚本（JavaScript）

// Photoshop 批量色阶调整脚本
var inputFolder = Folder.selectDialog("选择图片文件夹");
var outputFolder = Folder.selectDialog("选择输出文件夹");
var files = inputFolder.getFiles(/\.(jpg|jpeg|png|tif)$/i);
for (var i = 0; i < files.length; i++) {
    var doc = app.open(files[i]);
    // 创建色阶调整图层
    var levelAdjust = doc.artLayers.add();
    levelAdjust.kind = LayerKind.SOLIDFILL;
    levelAdjust.adjustments.levels([0, 1.0, 255]); // [阴影, 中间调, 高光]
    // 或使用自动色阶
    // doc.autoLevels();
    // 保存为JPEG
    var saveFile = new File(outputFolder + "/" + files[i].name);
    var jpegOptions = new JPEGSaveOptions();
    jpegOptions.quality = 12;
    doc.saveAs(saveFile, jpegOptions, true);
    doc.close(SaveOptions.DONOTSAVECHANGES);
}

使用GIMP批处理

# GIMP Python脚本
from gimpfu import *
import os
def batch_levels_adjust(input_dir, output_dir):
    for filename in os.listdir(input_dir):
        if filename.lower().endswith(('.jpg', '.png')):
            img_path = os.path.join(input_dir, filename)
            image = pdb.gimp_file_load(img_path, filename)
            drawable = pdb.gimp_image_get_active_drawable(image)
            # 自动色阶
            pdb.gimp_levels_stretch(drawable)
            # 或手动调整
            # pdb.gimp_levels(drawable, HISTOGRAM_VALUE, 
            #                 low_input, high_input, gamma, 
            #                 low_output, high_output)
            # 保存
            output_path = os.path.join(output_dir, filename)
            pdb.gimp_file_save(image, drawable, output_path, filename)
            pdb.gimp_image_delete(image)
pdb.register("batch_levels_adjust", ...)

完整的批处理脚本示例

import argparse
import os
from PIL import Image, ImageOps
import concurrent.futures
class BatchLevelAdjuster:
    def __init__(self, input_dir, output_dir):
        self.input_dir = input_dir
        self.output_dir = output_dir
        os.makedirs(output_dir, exist_ok=True)
    def adjust_levels(self, img_path, method='auto', **kwargs):
        """调整单张图片色阶"""
        img = Image.open(img_path)
        if method == 'auto':
            # 自动色阶
            img = ImageOps.autocontrast(img, cutoff=0.5)
        elif method == 'equalize':
            # 直方图均衡化
            img = ImageOps.equalize(img)
        elif method == 'manual':
            # 手动调整
            black = kwargs.get('black', 0)
            white = kwargs.get('white', 255)
            gamma = kwargs.get('gamma', 1.0)
            # 实现色阶映射
            def level_map(x):
                if x <= black:
                    return 0
                elif x >= white:
                    return 255
                else:
                    return int(((x - black) / (white - black)) ** gamma * 255)
            img = img.point(level_map)
        return img
    def process_batch(self, method='auto', **kwargs):
        """批量处理所有图片"""
        files = [f for f in os.listdir(self.input_dir) 
                if f.lower().endswith(('.jpg', '.png', '.jpeg'))]
        with concurrent.futures.ThreadPoolExecutor() as executor:
            futures = []
            for file in files:
                img_path = os.path.join(self.input_dir, file)
                output_path = os.path.join(self.output_dir, file)
                future = executor.submit(
                    self.process_single, 
                    img_path, output_path, method, **kwargs
                )
                futures.append(future)
            for future in concurrent.futures.as_completed(futures):
                try:
                    future.result()
                    print(f"完成: {future}")
                except Exception as e:
                    print(f"错误: {e}")
    def process_single(self, img_path, output_path, method, **kwargs):
        """处理单张图片"""
        img = self.adjust_levels(img_path, method, **kwargs)
        img.save(output_path)
# 使用示例
if __name__ == "__main__":
    adjuster = BatchLevelAdjuster("input", "output")
    # 自动色阶
    adjuster.process_batch(method='auto')
    # 或手动设置
    # adjuster.process_batch(method='manual', black=20, white=235, gamma=1.2)

使用建议

1. 小批量测试：先处理几张图片查看效果
2. 备份原图：始终保留原始文件
3. 调整参数：根据图片类型调整参数：
   • 风景图：色阶调整范围大些
   • 人像图：保持自然柔和
   • 产品图：确保准确还原

这些脚本可以帮你快速批量处理大量图片的色阶问题。