# AssertionError: The `num_classes` (3) in Shared2FCBBoxHead of MMDataParallel does not matches the length of `CLASSES` 80) in CocoDataset 你可能已经修改了以下两个文件,但是还是报错: mmdetection-master\mmdet\core\evaluation\class_names.py mmdetection-master\mmdet\datasets\coco.py 意思就是你指定...
CLASSES4) in CocoDataset#114 Notice There are several common situations in the reimplementation issues as below Reimplement a model in the model zoo using the provided configs Reimplement a model in the model zoo on other dataset (e.g., custom datasets) Reimplement a custom model but all the ...
AssertionError: The num_classes (3) in Shared2FCBBoxHead of MMDataParallel does not matches the length of CLASSES 80) in CocoDataset Can you help answer the question ? thanks myfutures changed the title Training Error AssertionError: The num_classes (3) in Shared2FCBBoxHead of MMDataParallel ...
1 shows an example image, its annotations in COCO and COCO-Stuff. The original COCO dataset offers location annotations only for the train, potted plant, bench and person, which are not sufficient to understand what the scene is about. Indeed, the image captions written by hu- mans (also ...
附一个VOC转COCO格式的参考代码 voc_dataset = VOCTrainValDataset(voc_root, class_names, split=train_split, format=img_format, transforms=preview_transform) output_file = f'instances_{train_split[:-4]}.json' for i, sample in enumerate(voc_dataset): ...
use COCO-Stuff to analyze: (a) the importance of stuff and thing classes in terms of their surface cover and how frequently they are mentioned in image captions; (b) the spatial relations between stuff and things, highlighting the rich contextual relations that make our dataset unique; (c) ...
To understand stuff and things in context we introduce COCO-Stuff, which augments all 164K images of the COCO 2017 dataset with pixel-wise annotations for 91 stuff classes. We introduce an efficient stuff annotation protocol based on superpixels, which leverages the original thing annotations. We ...
277 (82%) Figure 6: Histogram of similarity between training class groups (base and proxy-novel) and novel classes in OV-COCOdataset. For visualization, we adopt the same setting depicted in Figure 2 of the manuscript. 337 (100%)
use COCO-Stuff to analyze: (a) the importance of stuff and thing classes in terms of their surface cover and how frequently they are mentioned in image captions; (b) the spatial relations between stuff and things, highlighting the rich contextual relations that make our dataset unique; (c)...
AssertionError: Attribute 'thing_classes' in the metadata of 'coco_2017_train' cannot be set to a different value! I have not changed anything in the code, just followed the same procedure mentioned here: create dataset - coco/annotations and coco/image-folders, registered the dataset by call...