pip install pillow

from PIL import Image

def resize_image(input_path, output_path, size):
    """
    調(diào)整圖片大小并保存
    
    參數(shù):
        input_path: 輸入圖片路徑
        output_path: 輸出圖片路徑
        size: 目標尺寸，格式為(寬度, 高度)
    """
    with Image.open(input_path) as img:
        # 使用LANCZOS重采樣濾波器(高質(zhì)量)
        resized_img = img.resize(size, Image.LANCZOS)
        resized_img.save(output_path)

# 使用示例
resize_image("input.jpg", "output.jpg", (800, 600))

def resize_with_aspect_ratio(input_path, output_path, max_size):
    """
    按比例調(diào)整圖片大小，保持寬高比
    
    參數(shù):
        input_path: 輸入圖片路徑
        output_path: 輸出圖片路徑
        max_size: 最大寬度或高度
    """
    with Image.open(input_path) as img:
        width, height = img.size
        
        # 計算縮放比例
        if width > height:
            new_width = max_size
            new_height = int(height * (max_size / width))
        else:
            new_height = max_size
            new_width = int(width * (max_size / height))
            
        resized_img = img.resize((new_width, new_height), Image.LANCZOS)
        resized_img.save(output_path)

# 使用示例：將圖片最大邊調(diào)整為500像素
resize_with_aspect_ratio("input.jpg", "output_scaled.jpg", 500)

# 使用不同濾波器比較
with Image.open("input.jpg") as img:
    # 低質(zhì)量快速縮放
    fast_resize = img.resize((200, 200), Image.NEAREST)
    fast_resize.save("fast_resize.jpg")
    
    # 高質(zhì)量縮放
    high_quality = img.resize((200, 200), Image.LANCZOS)
    high_quality.save("high_quality.jpg")

import os
from PIL import Image

def batch_resize_images(input_folder, output_folder, size):
    """
    批量縮放文件夾中的所有圖片
    
    參數(shù):
        input_folder: 輸入文件夾路徑
        output_folder: 輸出文件夾路徑
        size: 目標尺寸，格式為(寬度, 高度)
    """
    if not os.path.exists(output_folder):
        os.makedirs(output_folder)
    
    for filename in os.listdir(input_folder):
        if filename.lower().endswith(('.png', '.jpg', '.jpeg', '.bmp', '.gif')):
            input_path = os.path.join(input_folder, filename)
            output_path = os.path.join(output_folder, filename)
            
            try:
                with Image.open(input_path) as img:
                    resized_img = img.resize(size, Image.LANCZOS)
                    resized_img.save(output_path)
                print(f"成功處理: {filename}")
            except Exception as e:
                print(f"處理 {filename} 時出錯: {e}")

# 使用示例
batch_resize_images("input_images", "output_images", (800, 600))

def create_thumbnail(input_path, output_path, thumbnail_size=128):
    """
    創(chuàng)建方形縮略圖
    
    參數(shù):
        input_path: 輸入圖片路徑
        output_path: 輸出縮略圖路徑
        thumbnail_size: 縮略圖邊長(像素)
    """
    with Image.open(input_path) as img:
        # 先按比例縮放，使較小邊等于縮略圖大小
        img.thumbnail((thumbnail_size, thumbnail_size), Image.LANCZOS)
        
        # 創(chuàng)建方形畫布
        background = Image.new('RGBA', (thumbnail_size, thumbnail_size), (255, 255, 255, 0))
        
        # 計算居中位置
        offset = ((thumbnail_size - img.size[0]) // 2, 
                 (thumbnail_size - img.size[1]) // 2)
        
        background.paste(img, offset)
        background.save(output_path)

# 使用示例
create_thumbnail("product.jpg", "product_thumbnail.png")

from PIL import Image, ExifTags

def resize_with_exif(input_path, output_path, size):
    """
    調(diào)整圖片大小并保留EXIF信息
    
    參數(shù):
        input_path: 輸入圖片路徑
        output_path: 輸出圖片路徑
        size: 目標尺寸，格式為(寬度, 高度)
    """
    with Image.open(input_path) as img:
        # 獲取EXIF數(shù)據(jù)
        exif_data = {}
        if hasattr(img, '_getexif'):
            exif = img._getexif()
            if exif is not None:
                for tag, value in exif.items():
                    decoded = ExifTags.TAGS.get(tag, tag)
                    exif_data[decoded] = value
        
        # 調(diào)整大小
        resized_img = img.resize(size, Image.LANCZOS)
        
        # 保存圖片并寫入EXIF數(shù)據(jù)(僅JPEG支持)
        resized_img.save(output_path, exif=exif_data if 'JPEG' in img.format.upper() else None)

# 使用示例
resize_with_exif("photo.jpg", "photo_resized.jpg", (1024, 768))