Labelme加载AI（Segment-Anything）模型进行图像标注

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  labelme是使用python写的基于QT的跨平台图像标注工具，可用来标注分类、检测、分割、关键点等常见的视觉任务，支持VOC格式和COCO等的导出，代码简单易读，是非常利用上手的良心工具。

第一步：
  下载源码进行安装。

git clone https://github.com/wkentaro/labelme.gitcd labelmepip install -e .

第二步：
   找到源码所在路径进行修改。
  （1）打开labelme/labelme/ai/init.py，源码如下：

MODELS = [    Model(        name="Segment-Anything (speed)",        encoder_weight=Weight(            url="https://github.com/wkentaro/labelme/releases/download/sam-20230416/sam_vit_b_01ec64.quantized.encoder.onnx",  # NOQA            md5="80fd8d0ab6c6ae8cb7b3bd5f368a752c",        ),        decoder_weight=Weight(            url="https://github.com/wkentaro/labelme/releases/download/sam-20230416/sam_vit_b_01ec64.quantized.decoder.onnx",  # NOQA            md5="4253558be238c15fc265a7a876aaec82",        ),    ),    Model(        name="Segment-Anything (balanced)",        encoder_weight=Weight(            url="https://github.com/wkentaro/labelme/releases/download/sam-20230416/sam_vit_l_0b3195.quantized.encoder.onnx",  # NOQA            md5="080004dc9992724d360a49399d1ee24b",        ),        decoder_weight=Weight(            url="https://github.com/wkentaro/labelme/releases/download/sam-20230416/sam_vit_l_0b3195.quantized.decoder.onnx",  # NOQA            md5="851b7faac91e8e23940ee1294231d5c7",        ),    ),    Model(        name="Segment-Anything (accuracy)",        encoder_weight=Weight(            url="https://github.com/wkentaro/labelme/releases/download/sam-20230416/sam_vit_h_4b8939.quantized.encoder.onnx",  # NOQA            md5="958b5710d25b198d765fb6b94798f49e",        ),        decoder_weight=Weight(            url="https://github.com/wkentaro/labelme/releases/download/sam-20230416/sam_vit_h_4b8939.quantized.decoder.onnx",  # NOQA            md5="a997a408347aa081b17a3ffff9f42a80",        ),    ),]

  （2）在labelme/labelme/文件夹下自建一个文件夹model_file。
  （3）依次输入以下几个网址下载onnx到model_file文件目录。

https://github.com/wkentaro/labelme/releases/download/sam-20230416/sam_vit_b_01ec64.quantized.encoder.onnxhttps://github.com/wkentaro/labelme/releases/download/sam-20230416/sam_vit_b_01ec64.quantized.decoder.onnxhttps://github.com/wkentaro/labelme/releases/download/sam-20230416/sam_vit_l_0b3195.quantized.encoder.onnxhttps://github.com/wkentaro/labelme/releases/download/sam-20230416/sam_vit_l_0b3195.quantized.decoder.onnxhttps://github.com/wkentaro/labelme/releases/download/sam-20230416/sam_vit_h_4b8939.quantized.encoder.onnxhttps://github.com/wkentaro/labelme/releases/download/sam-20230416/sam_vit_h_4b8939.quantized.decoder.onnx

  （4）修改labelme/labelme/ai/init.py，代码如下：

import collectionsfrom .models.segment_anything import SegmentAnythingModel  # NOQAModel = collections.namedtuple(    "Model", ["name", "encoder_weight", "decoder_weight"])Weight = collections.namedtuple("Weight", ["url", "md5"])# MODELS = [#     Model(#         name="Segment-Anything (speed)",#         encoder_weight=Weight(#             url="https://github.com/wkentaro/labelme/releases/download/sam-20230416/sam_vit_b_01ec64.quantized.encoder.onnx",  # NOQA#             md5="80fd8d0ab6c6ae8cb7b3bd5f368a752c",#         ),#         decoder_weight=Weight(#             url="https://github.com/wkentaro/labelme/releases/download/sam-20230416/sam_vit_b_01ec64.quantized.decoder.onnx",  # NOQA#             md5="4253558be238c15fc265a7a876aaec82",#         ),#     ),#     Model(#         name="Segment-Anything (balanced)",#         encoder_weight=Weight(#             url="https://github.com/wkentaro/labelme/releases/download/sam-20230416/sam_vit_l_0b3195.quantized.encoder.onnx",  # NOQA#             md5="080004dc9992724d360a49399d1ee24b",#         ),#         decoder_weight=Weight(#             url="https://github.com/wkentaro/labelme/releases/download/sam-20230416/sam_vit_l_0b3195.quantized.decoder.onnx",  # NOQA#             md5="851b7faac91e8e23940ee1294231d5c7",#         ),#     ),#     Model(#         name="Segment-Anything (accuracy)",#         encoder_weight=Weight(#             url="https://github.com/wkentaro/labelme/releases/download/sam-20230416/sam_vit_h_4b8939.quantized.encoder.onnx",  # NOQA#             md5="958b5710d25b198d765fb6b94798f49e",#         ),#         decoder_weight=Weight(#             url="https://github.com/wkentaro/labelme/releases/download/sam-20230416/sam_vit_h_4b8939.quantized.decoder.onnx",  # NOQA#             md5="a997a408347aa081b17a3ffff9f42a80",#         ),#     ),# ]MODELS = [    Model(        name="Segment-Anything (speed)",        encoder_weight=Weight(            url="E:\labelme\labelme\model_file\sam_vit_b_01ec64.quantized.encoder.onnx",  # NOQA            md5="80fd8d0ab6c6ae8cb7b3bd5f368a752c",        ),        decoder_weight=Weight(            url="E:\labelme\labelme\model_file\sam_vit_b_01ec64.quantized.decoder.onnx",  # NOQA            md5="4253558be238c15fc265a7a876aaec82",        ),    ),    Model(        name="Segment-Anything (balanced)",        encoder_weight=Weight(            url="E:\labelme\labelme\model_file\sam_vit_l_0b3195.quantized.encoder.onnx",  # NOQA            md5="080004dc9992724d360a49399d1ee24b",        ),        decoder_weight=Weight(            url="E:\labelme\labelme\model_file\sam_vit_l_0b3195.quantized.decoder.onnx",  # NOQA            md5="851b7faac91e8e23940ee1294231d5c7",        ),    ),    Model(        name="Segment-Anything (accuracy)",        encoder_weight=Weight(            url="E:\labelme\labelme\model_file\sam_vit_h_4b8939.quantized.encoder.onnx",  # NOQA            md5="958b5710d25b198d765fb6b94798f49e",        ),        decoder_weight=Weight(            url="E:\labelme\labelme\model_file\sam_vit_h_4b8939.quantized.decoder.onnx",  # NOQA            md5="a997a408347aa081b17a3ffff9f42a80",        ),    ),]

  （5）修改labelme/labelme/widgets/canvas.py，代码如下：

    def initializeAiModel(self, name):        if name not in [model.name for model in labelme.ai.MODELS]:            raise ValueError("Unsupported ai model: %s" % name)        model = [model for model in labelme.ai.MODELS if model.name == name][0]        if self._ai_model is not None and self._ai_model.name == model.name:            logger.debug("AI model is already initialized: %r" % model.name)        else:            logger.debug("Initializing AI model: %r" % model.name)            self._ai_model = labelme.ai.SegmentAnythingModel(                name=model.name,                # encoder_path=gdown.cached_download(                #     url=model.encoder_weight.url,                #     md5=model.encoder_weight.md5,                # ),                # decoder_path=gdown.cached_download(                #     url=model.decoder_weight.url,                #     md5=model.decoder_weight.md5,                # ),                encoder_path=model.encoder_weight.url,                decoder_path=model.decoder_weight.url,            )        self._ai_model.set_image(            image=labelme.utils.img_qt_to_arr(self.pixmap.toImage())        )

第三步：
  启动labelme

cd labelmelabelme

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本文链接：https://www.kjpai.cn/gushi/2024-04-13/158272.html，文章来源：网络cs，作者：言安琪，版权归作者所有，如需转载请注明来源和作者，否则将追究法律责任！