有没有办法将带有注释的图像（标记图像）上传到自定义视觉？

Question

我有数百个标记图像，不想在自定义视觉标记工具中重做这项工作。有没有办法将标记的图像上传到自定义视觉？还是 Azure ML 或 Azure ML Studio？ Azure 中的任何视觉服务是否提供上传带注释的图像？谢谢

Answer 1

我使用我开发的名为 PyLabel 的包构建了一个概念验证，用于将注释上传到 Azure 自定义视觉。你可以在这里看到它https://github.com/pylabel-project/samples/blob/main/pylabel2azure_custom_vision.ipynb。

PyLabel 可以将 COCO、YOLO 或 VOC 格式的注释读取到数据框中。一旦它们在数据框中，您就可以遍历注释的数据框并使用自定义视觉 API 上传图像和注释。

Custom Vision 使用的注解格式类似于 YOLO 格式，因为它们都使用了 0-1 之间的归一化坐标。

这是上面提到的笔记本中的代码的sn-p：

#Iterate the rows for each image in the dataframe
for img_filename, img_df in dataset.df.groupby('img_filename'):
    img_path = str(PurePath(dataset.path_to_annotations, str(img_df.iloc[0].img_folder), img_filename))
    assert exists(img_path), f"File does not exist: {img_path}"

    #Create a region object for each bounding box in the dataset 
    regions = []
    for index, row in img_df.iterrows():

        #Normalize the boundings box coordinates between 0 and 1
        x = Decimal(row.ann_bbox_xmin / row.img_width).min(1)
        y = Decimal(row.ann_bbox_ymin / row.img_height).min(1)
        w = Decimal(row.ann_bbox_width / row.img_width).min(1-x)
        h = Decimal(row.ann_bbox_height / row.img_height).min(1-y)
        
        regions.append(Region(
                tag_id=tags[row.cat_name].id, 
                left=x,
                top=y,
                width=w,
                height=h
            )
        )

    #Create an object with the image and all of the annotations for that image
    with open(img_path, mode="rb") as image_contents:
        image_and_annotations = [ImageFileCreateEntry(name=img_filename, contents=image_contents.read(), regions=regions)]

    #Upload the image and all annnotations for that image
    upload_result = trainer.create_images_from_files(
            project.id, 
            ImageFileCreateBatch(images=image_and_annotations)
        )
    
    #If upload is not successful, print details about that image for debugging 
    if not upload_result.is_batch_successful:
        print("Image upload failed.")
        for image in upload_result.images:
            print(img_path)
            print("Image status: ", image.status)
            print(regions)

#This will take a few minutes 
print("Upload complete")