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A tool for generating random images

Project description

Nazo Image Utils

Nazo Image Utils 是一个高性能的图像处理和随机图像生成 Python 包。它包含两个主要组件:RandImageProcessImage,支持现代图像格式(AVIF、WebP、JPEG)。

🚀 特性

  • 🖼️ 多格式支持: 支持 AVIF、WebP、JPEG 三种图像格式
  • 高性能: 使用 Cython 优化和多进程处理
  • 🎯 智能格式选择: 根据浏览器支持自动选择最佳格式(AVIF > WebP > JPEG)
  • 🔧 渐进式编码: 支持渐进式 JPEG 和 AVIF
  • 📱 响应式: 自动识别横图/竖图适配不同设备
  • 🛠️ 原生工具集成: 支持使用 avifenc 获得最佳 AVIF 质量

📦 安装

您可以使用 pip 安装 Nazo Image Utils:

pip install nazo-image-utils

可选依赖

为了获得最佳的 AVIF 支持,建议安装 avifenc 工具:

Windows:

winget install avif-tools

Ubuntu/Debian:

sudo apt install libavif-bin

macOS:

brew install libavif

🔧 ProcessImage

ProcessImage 是一个高性能的图像批处理类,支持多种现代图像格式。

初始化

from nazo_image_utils import ProcessImage

process_image = ProcessImage(
    flush: bool = False,           # 是否清空缓存
    filter: bool = True,           # 是否过滤不合格图像
    gallery_path: str = "./gallary", # 待处理图像目录
    pc_filter_size: Size = PC_SIZE,     # PC端最小尺寸 (1920x1080)
    mobile_filter_size: Size = MOBILE_SIZE, # 移动端最小尺寸 (1080x1920)
)

配置说明

  • gallery_path: 待处理图像的源目录
  • flush: 当为 True 时,忽略已生成的 manifest 文件,重新处理所有图像
  • filter: 当为 True 时,过滤掉小于指定尺寸的图像
  • pc_filter_size: PC 端图像的最小合格尺寸(默认:1920×1080)
  • mobile_filter_size: 移动端图像的最小合格尺寸(默认:1080×1920)

方法

try_process()

process_image.try_process()

批量处理指定文件夹中的所有图片,生成多种格式和尺寸的图像文件。

处理结果:

  • 创建 avif/webp/jpeg/ 三个目录
  • 每张图片生成三种尺寸:
    • source: 原始尺寸
    • th: 缩略图 (900×600)
    • md: 微型图 (50×30)
  • 生成两个 manifest 文件:
    • manifest.json: PC 端图像索引
    • manifest_mobile.json: 移动端图像索引

格式优化:

  • AVIF: 使用原生 avifenc 工具,启用渐进式编码
  • WebP: 高质量有损压缩,方法级别 6
  • JPEG: 渐进式编码,禁用色度子采样

Manifest 文件格式

{
  "md5_hash": {
    "source": "original_filename.jpg"
  }
}

🎲 RandImage

RandImage 是一个高性能的随机图像 URL 生成器,使用 Cython 优化以获得最佳性能。

初始化

from nazo_image_utils import RandImage

rand_image = RandImage(
    pc_json_path="./manifest.json",
    mobile_json_path="./manifest_mobile.json",
    domain="https://example.com"
)

方法

process()

result = rand_image.process(
    ua: bytes,                          # 用户代理字符串
    number: int,                        # 请求的URL数量 (1-10)
    platform: bytes = b"pc",           # 平台类型
    encode: bytes = b"",                # 编码方式
    size: bytes = b"source",            # 图像尺寸
)

根据用户代理和平台生成优化的图像 URL。

参数详解

  • ua (bytes): 用户浏览器的 User-Agent 字符串,用于检测 AVIF 和 WebP 支持
  • number (int): 请求的图像 URL 数量,范围 1-10
  • platform (bytes): 图像方向
    • b"pc": 横向图像 (宽 > 高)
    • b"mobile": 纵向图像 (高 > 宽)
  • encode (bytes): 返回格式
    • b"": 返回单个 URL (bytes)
    • b"json": 返回 URL 列表 (list[str])
  • size (bytes): 图像尺寸
    • b"source": 原始尺寸
    • b"th": 缩略图尺寸
    • b"md": 微型图尺寸

返回值

  • 单个 URL (当 encode != b"json"): bytes 类型的图像 URL
  • URL 列表 (当 encode == b"json"): list[str] 类型的 URL 列表

智能格式选择

系统会根据用户代理自动选择最佳图像格式:

  1. AVIF - 如果浏览器支持(最新、最高效)
  2. WebP - 如果浏览器支持但不支持 AVIF
  3. JPEG - 后备选项,确保兼容性

URL 格式

生成的 URL 格式为:

{domain}/{format}/{md5_hash}.{size}.{format}

示例:

https://nazo.run/avif/0a4d55a8d778e5022fab701977c5d840.source.avif
https://nazo.run/webp/1b5e66b9d889e6033gbc802088c6e951.th.webp
https://nazo.run/jpeg/2c6f77c0e990f7044hcd913199d7f062.md.jpeg

💡 使用示例

基本图像处理

from nazo_image_utils import ProcessImage

# 创建处理器实例
processor = ProcessImage(
    gallery_path="./my_images",
    filter=True,
    flush=False
)

# 处理所有图像
processor.try_process()

生成随机图像 URL

from nazo_image_utils import RandImage

# 初始化随机图像生成器
rand_img = RandImage(
    pc_json_path="./manifest.json",
    mobile_json_path="./manifest_mobile.json",
    domain="https://cdn.example.com"
)

# 获取单个 PC 图像 URL
url = rand_img.process(
    ua=b"Mozilla/5.0 (compatible; AVIF support)",
    number=1,
    platform=b"pc",
    size=b"source"
)

# 获取多个移动端图像 URL 列表
urls = rand_img.process(
    ua=b"Mozilla/5.0 (Mobile; WebP support)",
    number=5,
    platform=b"mobile",
    encode=b"json",
    size=b"th"
)

在 Web 应用中使用

from flask import Flask, request
from nazo_image_utils import RandImage

app = Flask(__name__)
rand_img = RandImage("./manifest.json", "./manifest_mobile.json", "https://cdn.mysite.com")

@app.route('/api/random-image')
def get_random_image():
    user_agent = request.headers.get('User-Agent', '').encode('utf-8')
    platform = b"mobile" if "Mobile" in request.headers.get('User-Agent', '') else b"pc"

    url = rand_img.process(
        ua=user_agent,
        number=1,
        platform=platform,
        size=b"source"
    )

    return {"image_url": url.decode('utf-8')}

🔧 运行脚本

为了避免多进程相关问题,建议使用提供的 main.py 脚本:

# main.py
from nazo_image_utils import ProcessImage

if __name__ == "__main__":
    processor = ProcessImage(
        flush=False,
        filter=True,
        gallery_path="./gallary"
    )
    processor.try_process()

运行:

python main.py

📋 系统要求

  • Python 3.7+
  • PIL/Pillow
  • Cython (用于编译)
  • tqdm (进度条)
  • ujson (JSON 处理)

可选依赖

  • avifenc (推荐,用于最佳 AVIF 质量)
  • modern-image-support (用于浏览器兼容性检测)

🎯 性能优化

  • 多进程处理: 使用 8 个进程并行处理图像
  • Cython 优化: 核心随机选择逻辑使用 C 扩展
  • 内存管理: 自动内存分配和释放
  • 原生工具: 使用 avifenc 获得最佳 AVIF 压缩
  • 智能缓存: 基于 MD5 的重复检测

📄 许可证

详见 LICENSE 文件。

🤝 贡献

欢迎提交 Issue 和 Pull Request!

许可证

本项目采用 MIT 许可证进行许可 - 请参阅 LICENSE 文件获取更多详细信息。

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