error "No media data found" # cvat/cvat/apps/engine/task.py : line 271 if unique_entries == 0 and multiple_entries == 0: raise ValueError('No media data found') Expected Behavior I haven't seen any opensource annotation tools that support panoptic segmentation, so I'm not sure how it...
Object detection物体检测:具有 80 个不同对象的边界框坐标和完整分割掩模; Stuff image segmentation图像分割:像素图显示 91 个无定形背景区域; Panoptic segmentation全景分割:根据 80 个“事物”和 91 个“东西”类别识别图像中的项目; Dense pose:密集姿势包含超过 39,000 张照片,包含超过 56,000 个标记人物,...
# Keypoint Detection@dataclassclassAnnotation:segmentation:Any# RLE or [polygon]num_keypoints:intarea:floatiscrowd:Any# 0 or 1keypoints:Any# [x1,y1,v1,...]image_id:intbbox:Any# [x, y, width, height]category_id:intid:int@dataclassclassCategory:supercategory:strid:intname:str='person'k...
ImageSets中的文件夹存放了不同任务数据集的划分方法。 例如在Segmentation中的train.txt就包含了所有训练集所需要的图片名称。 在Annotations文件目录下,有着与图片名相同,但xml类型的标注文件,其文件内容如下所示。 <annotation> <folder>VOC2012</folder> <filename>2007_000039.jpg</filename> <database>The V...
3.2.4 Panoptic Segmentation(全景分割) 对于全景分割任务,每个注释结构是每个图像的注释,而不是每个对象的注释,与上面三个有区别。每个图像的注释有两个部分:1)存储与类无关的图像分割的PNG;2)存储每个图像段的语义信息的JSON结构。 要将注释与图像匹配,使用image_id字段(即:annotation.image_id==image.id); ...
visualization.pyprovides an example of generating visually appealing representation of the panoptic segmentation data. Contact If you have any questions regarding this API, please contact us at alexander.n.kirillov-at-gmail.com. Releases No releases published...
Other vision datasets:一些数据集如Middlebury datasets,包含立体相对,多视角立体像对和光流;同时还有Berkeley Segmentation Data Set (BSDS500),可以评价segmentation和edge detection算法。 3. COCO数据集格式 COCO有5种类型的标注,分别是:物体检测、关键点检测、实例分割、全景分割、图片标注,都是对应一个json文件。jso...
2. COCO Panoptic Segmentation Task The goal of the COCO Panoptic Segmentation Task is to advance the state of the art in scene segmentation. Panorama segmentation needs to deal with object classes and event classes, it unifies two typical semantic and instance segmentation tasks. The definition of...
2017未标注数据12.319 COCO数据集十分著名,也和历年的学术会议挑战赛有关。不同年份的数据集也被用来测试不同任务。这些数据支持的任务包括图像检测(Detection)、图像描述(Captioning)、关键点(keypoint)、具有特定尺寸和形状的物体(COCO Stuff )、全景分割(Panoptic Segmentation)等。
Json file panoptic_coco_categories.json contains the list of all categories used in COCO panoptic segmentation challenge 2018. Visualization visualization.py provides an example of generating visually appealing representation of the panoptic segmentation data. Contact If you have any questions regarding this...