Alloy Wrench

一些 研究 折腾机器视觉框架时候用到的 工具 轮子代码.

代码基于 Java 17 Java 21, 依赖 Topaz 库, 以木兰宽松许可证 (第二版) 协议开源.

为什么用 Java?
因为主业是写 Java 的, 写着习惯

_{为什么不用 Java 8?!} 为什么是 Java 17? 为什么是 Java 21?
_{因为相信的心就是你的魔法哟~} 因为乐意

这一切值得吗?
能用就行, 哪来那么多毛病

图标?
原图为 工业时代 - 扳手 的材质 _{吱嘎吱嘎吱嘎 🔈}

用法

<!-- if u want Maven -->
<!-- then u'll have to take pom -->
<repositories>
    <repository>
        <id>github-alloy-wrench</id>
        <url>https://maven.pkg.github.com/FirokOtaku/AlloyWrench</url>
    </repository>
</repositories>
<dependencies>
  <dependency>
    <groupId>firok.tool</groupId>
    <artifactId>alloy-wrench</artifactId>
    <version>0.35.0</version>

    <exclusions>
      <!-- if u only want use Alloy Wrench as code lib, -->
      <!-- most of dependencies of Alloy Wrench can be excluded -->
      ...
    </exclusions>
  </dependency>
</dependencies>

# 神说 要有 jar
# 出于未知且知道也懒得修复的问题 现在打包出来的玩意不能用
# 反正在 IDE 里直接用也不是不能用
# 建议你也装一套开发环境
mvn package

# 帮助信息
# 下面所有的例子都是以前写的 参数列表的顺序可能发生过变化
# 建议有问题之前先不带参数直接执行一下 打印出来的帮助信息应该够详细了
java -jar alloy-wrench-jar-with-dependencies.jar

# 收集 DOTA 数据标签文件里面的标签目标类型
# 整理成一个 json
java -jar alloy-wrench-jar-with-dependencies.jar ^
 collect dota ^
 "./playground/mapping.json" ^
 "./dota-1.0/train/labelTxt" ^
 "./dota-1.0/val/labelTxt"

# 将 DOTA 数据标签文件转换成 YOLO 格式的
# 需要用到上面读取创建的映射 json
java -jar alloy-wrench-jar-with-dependencies.jar ^
 convert dota yolo ^ 
 "./dota-1.0/val/labelTxt" ^
 "./dota-1.0/val/images" ^
 "./playground/mapping.json" ^
 "./playground/val-labels"

java -jar alloy-wrench-jar-with-dependencies.jar ^
 convert dota yolo ^
 "./dota-1.0/train/labelTxt" ^
 "./dota-1.0/train/images" ^
 "./playground/mapping.json" ^
 "./playground/train-labels"

# 将 COCO 数据集转换为 DOTA 格式
java -jar alloy-wrench-jar-with-dependencies.jar ^
 convert coco dota ^
 "./coco-label.json" ^
 "./coco-2-dota-label/"

# 将 COCO 数据集转换为 MVTec 格式
java -jar alloy-wrench-jar-with-dependencies.jar ^
 convert coco mvtec ^
 "./coco-dataset/images" ^
 "./coco-dataset/coco-label.json" ^
 "./playground/mapping.json" ^
 "./playground/output-dataset"

# 将 COCO 数据集转换为旧版 COCO 数据集
java -jar alloy-wrench-jar-with-dependencies.jar ^
 convert coco coco-split ^
 "./coco.json" ^
 "./images/" ^
 "./output"

# 将 labelme 创建的 JSON 数据文件转换为 COCO 格式的
java -jar alloy-wrench-jar-with-dependencies.jar ^
 convert labelme coco ^
 "./labelme-labels.json" ^
 "./output-coco-labels.json"

# 将 labelme 创建的 JSON 数据文件转换为 YOLO 格式的
java -jar alloy-wrench-jar-with-dependencies.jar ^
 convert labelme yolo ^
 "./labelme-labels.json" ^
 "./yolo-labels.txt" ^
 "./mapping.json"

# 将 labelme 创建的 JSON 数据文件转换为 DOTA 格式的
java -jar alloy-wrench-jar-with-dependencies.jar ^
 convert labelme dota ^
 "./labelme-labels.json" ^
 "./dota-labels.txt"

# 直接以矩形切割图片
java -jar alloy-wrench-jar-with-dependencies.jar ^
 cut block direct ^
 "./input-image.png" ^
 "./output-images/" ^
 1600 1600 0 0

# 切分图片和相关 DOTA 标签数据
# 如果只希望输出切片图片或切片标签
# 需要手动修改代码里的 CutImageTask.OUTPUT_CUT_IMAGE 和 CutImageTask.OUTPUT_CUT_LABEL 值
# 如果需要调整输出图片的大小等参数
# 需要手动修改代码里的 CutImageTask.OVERLYING_X 和 CutImageTask.PIECE_X 等参数
# 为什么用这种方式 因为懒得从代码接收参数了
java -jar alloy-wrench-jar-with-dependencies.jar ^
 cut block dota ^
 "./raw.png" ^
 "./raw.txt" ^
 "./sub-images" ^
 "./sub-labels"

# 把单一的 COCO 标签图按照矩形范围切割成小图 COCO 数据集
java -jar alloy-wrench-jar-with-dependencies.jar ^
 cut block coco ^
 "./coco-label.json" ^
 "./coco-images/" ^
 "./coco-label-cut.json" ^
 "./coco-images-cut/" ^
 "coco-image-cut-"

# 切分图片和相关 COCO 标签数据
# 会把图片里的每个实例单独切分成一张图片
java -jar alloy-wrench-jar-with-dependencie.jar ^
 cut block coco ^
 "./super-big/images/" ^
 "./super-big.json" ^
 "./super-big-pieces/" ^
 "./super-big-pieces.json"

# 合并两个 COCO 标签文件
java -jar alloy-wrench-jar-with-dependencies.jar ^
 merge coco multi ^
 "./coco-label-output.json"
 "./coco-label-1.json" ^
 "./coco-label-2.json" ^

# 合并 COCO 标签文件中的种类
# 比如把 "板房" "砖房" 统一合并成 "房屋"
java -jar alloy-wrench-jar-with-dependencies.jar ^
 merge coco category
 "./label-input.json" ^
 "./label-output.json" ^
 "./mapping.json"

# 过滤 COCO 标签文件的内容
java -jar alloy-wrench-jar-with-dependencies.jar ^
 filter coco ^
 "./coco-label-input.json" "./coco-label-output.json" ^
 --filter-anno-id 1 2 3 ^
 --filter-image-id 1 2 3 ^
 --filter-category-id 1 2 3
 
# 修复 coco 数据集标签文件
java -jar alloy-wrench-jar-with-dependencies.jar ^
 coco fix ^
 "./images" ^
 "./coco.json"

# 启动数据标签可视化工具
java -jar alloy-wrench-jar-with-dependencies.jar ^
 renderer dota

# 启动数据标记工具
java -jar alloy-wrench-jar-with-dependencies.jar ^
 marker

• convert coco mvtec COCO 数据集转换 MVTec 数据集 - 映射文件格式

相关链接

• DOTA 数据集
• YOLO 框架
• labelme 工具
• MMDetection 框架
• MMDetection 框架官网
• JTS 库
• MVTec 数据集

changelog

• 0.37.0
  • add convert from coco dataset to old version coco dataset
• 0.36.0
  • add fixing tool for COCO dataset annotations file
• 0.35.0
  • upgrade dependencies versions
  • license change to MulanPSL2 from MIT
• 0.34.0
  • fix a logic error when converting coco dataset to mvtec dataset
• 0.33.0
  • add convert from coco dataset to mvtec dataset
  • JDK dependency upgrade to 21 from 17
• 0.32.0
  • fix an inference result conversion error
• 0.31.0
  • add imantics dependency for converting inference results
• 0.30.0
  • add more params to convert_result script
• 0.29.0
  • update convert_result script for MMDetection3 compatibility
• 0.28.0
  • adjust location of Python script and maven compiling config
• 0.27.0
  • update dependency
• 0.26.0
  • fix a coor calculation error
  • fix coco json read error
• 0.25.0
  • fix a coor calculation error
  • provide CutImageDirectTask api
• 0.24.0
  • fix border coor calculation error
• 0.23.0
  • coco label merging tool now can deal with multiple files at once
• 0.22.0
  • add tool for merging categories in coco label
• 0.21.0
  • add http server for converting script json to geojson (internal usage)
• 0.20.0
  • add convert from geojson to coco label (internal usage)
  • filtering coco label tool now can be used for remove unused images from label file
• 0.19.0
  • add tool for filtering coco label content
• 0.18.0
  • add tool for merging two coco label files
• 0.17.0
  • add convert from labelme label to coco label
• 0.16.0
  • add image cutter tool (cut into rectangle shape directly)
• 0.15.0
  • add a python script to convert results of mmdetection and get coordinates from it
  • now renderer tool could read json data converted from script mentioned above
• 0.14.0
  • add image cutter tool (cut by coco format dataset)
• 0.13.0
  • add convert from coco label to dota label
• 0.12.0
  • add image cutter tool
• 0.11.0
  • update label marker (unfinished)
• 0.10.0
  • update label marker (unfinished)
• 0.9.0
  • DOTA label renderer now will add points to indicate where the polygon starts
  • minor code improvement
  • add label marker (unfinished)
• 0.8.0
  • now we could calculate overlaps between labels and cutting area when cutting images
• 0.7.0
  • add image-and-labels cutter
• 0.6.0
  • add convert from labelme json to yolo text
  • minor code improvement
  • add Java module support
• 0.5.0
  • reformat help information
• 0.4.0
  • add label viewer GUI
  • minor code improvement
• 0.3.0
  • print more log information
  • update readme
• 0.2.0
  • error fixes
• 0.1.0
  • init commit

gossip

• DOTA 集里有些打点在图片外, 非常真实
• DOTA 集的标签文件换行符是 /r/n 哟
• 突然发现 JavaFX 当 Swing 写也可以嘛
• native-image + JavaFX + --no-fallback = BOOM
• native-image + Swing + --no-fallback = BOOM
• 要是某些项目的文档全一点, 这里的轮子至少少一半
• 自己写的 库 肯定是要狠狠地用; 建议你们也用
• 这玩意真的有别的人会用吗? 也许吧
• 查看 COCO 数据集的功能在 这里