Provides precise elapsed-time …

# RAW照片批量压缩脚本

方案说明

RAW文件（.CR2/.NEF/.ARW等）无法直接用Pillow压缩，推荐两条路线：

• 方案A（推荐）：调用系统安装的 dcraw 或 rawpy 库解RAW → 转JPEG并压缩
• 方案B：仅做无损优化/复制，速度更快但压缩率低

以下提供 rawpy + Pillow 方案，兼容性好、纯Python实现。

安装依赖

```bash

pip install rawpy pillow

```

完整脚本

```python

import os

import time

import rawpy

from PIL import Image

from concurrent.futures import ThreadPoolExecutor

SRC = r"D:\Photos" # 源文件夹

DST = r"D:\Photos_jpg" # 输出文件夹

QUALITY = 85 # JPEG质量 1-95

MAX_WORKERS = 4 # 并发线程数

RAW_EXT = ('.cr2', '.cr3', '.nef', '.arw', '.dng', '.raf', '.orf', '.rw2')

os.makedirs(DST, exist_ok=True)

files = [f for f in os.listdir(SRC) if f.lower().endswith(RAW_EXT)]

total = len(files)

done, failed = 0, 0

start = time.time()

def process(fname):

src_path = os.path.join(SRC, fname)

dst_path = os.path.join(DST, os.path.splitext(fname)[0] + '.jpg')

with rawpy.imread(src_path) as raw:

rgb = raw.postprocess(use_camera_wb=True)

img = Image.fromarray(rgb)

img.save(dst_path, 'JPEG', quality=QUALITY, optimize=True)

with ThreadPoolExecutor(max_workers=MAX_WORKERS) as pool:

futures = {pool.submit(process, f): f for f in files}

for fut in futures:

try:

fut.result()

done += 1

except Exception as e:

failed += 1

print(f"失败: {futures[fut]} - {e}")

# 每处理若干张后检查是否满10秒再输出（避免刷屏）

if done and time.time() - start >= 10:

elapsed = time.time() - start

print(f"已处理 {done}/{total} 张，已用时 {elapsed:.1f} 秒，"

f"平均 {done/elapsed:.2f} 张/秒"