标记数据以便在自定义数据集上训练yolov5模型
I used the source code (
问题是，在标记图像后，我尝试在Roboflow中训练模型，但我无法使用图像的注释。
我的注释在txt文件中，以以下格式：
2 0.3107142857142857 0.5509554140127388 0.30714285714285716 0.89171974522293
1 0.9696428571428571 0.39331210191082805 0.060714285714285714 0.7292993630573248
1 0.7241071428571428 0.5047770700636943 0.23035714285714284 0.9713375796178344
1 0.07946428571428571 0.4968152866242038 0.15892857142857142 0.9745222929936306
1 0.4982142857142857 0.5031847133757962 0.17857142857142858 0.9617834394904459
当我尝试在Roboflow上传时，显示了消息： 请添加您的LabelMap文本文件（如果有一个），以将数字类标识符转换为可读的名称。
有人知道什么是最好的转换方法或如何使LabelMap进行标签？
I used the source code (ModifiedOpenLabelling) to label my images for Train YOLOv5 Object Detection.
The problem is that after labeling my images, I tried to train a model in roboflow, but I could not use the annotations of the images.
My annotations are in a txt file, in the following format:
2 0.3107142857142857 0.5509554140127388 0.30714285714285716 0.89171974522293
1 0.9696428571428571 0.39331210191082805 0.060714285714285714 0.7292993630573248
1 0.7241071428571428 0.5047770700636943 0.23035714285714284 0.9713375796178344
1 0.07946428571428571 0.4968152866242038 0.15892857142857142 0.9745222929936306
1 0.4982142857142857 0.5031847133757962 0.17857142857142858 0.9617834394904459
When I tried to upload in roboflow, the message was shown:
Please add your labelmap text file (if you have one) to translate the numeric class identifiers into human-readable names.
Does anyone know what is the best way to do this conversion or how I can make the labelmap?
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本文解释了LabelMaps： https：//blog.roboflow.com/label-map/
我建议创建一个“ data.yaml”文件。确保将“火车”和“验证”设置文件夹的文件夹路径的引用更新；确保“ NC”（类数）字段与数据集中的类匹配；并更新列表中的标签名称。
“ rel =“ nofollow noreferrer”>修改类生成带有您想要的类名称的数据集的版本，然后从那里继续您的项目，或将修改后的类数据集版本导出到新项目，并继续使用那里的永久性“新”标签。
此外，我强烈建议继续在Roboflow上标记新项目，因为我们有能力以26种不同格式的注释摄入和转换数据集： https://roboflow.com/formats
this article explains labelmaps: https://blog.roboflow.com/label-map/
I would suggest creating a "data.yaml" file. Be sure to update the references to the folder paths for your "train" and "validation" set folders; ensure the "nc" (number of classes) field matches the number of classes in your dataset; and update the label names in the list.
Another option is to upload the images to Roboflow, use Modify Classes to generate a version of the dataset with the class names you desire, and continue your project from there, or export the Modified Classes dataset version to a new project and continue with the permanent "new" label names from there.
Additionally, I highly recommend continuing to label new projects on Roboflow, as we have the ability to ingest and convert datasets with annotations in 26 different formats: https://roboflow.com/formats