Problems when I train my dataset with COCO format.

[tangjiaxi98]

Label JPG files with labelme==5.0.1, translated to COCO format, and edit builtin.py and builtin_meta.py already. I think the problem is "[03/15 17:42:59 d2.data.build]: Removed 48 images with no usable annotations. 0 images left." How to fix it?Thanks.

[github-actions[bot]]

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[tangjiaxi98]

Logs: [03/15 17:42:57] detectron2 INFO: Rank of current process: 0. World size: 1 [03/15 17:42:57] detectron2 INFO: Command line arguments: Namespace(config_file='configs/COCO-detection/faster_rcnn_R_101_FPN_base.yaml', dist_url='tcp://127.0.0.1:50152', end_iter=-1, eval_all=False, eval_during_train=False, eval_iter=-1, eval_only=False, machine_rank=0, num_gpus=1, num_machines=1, opts=None, resume=False, start_iter=-1) [03/15 17:42:57] detectron2 INFO: Contents of args.config_file=configs/COCO-detection/faster_rcnn_R_101_FPN_base.yaml: BASE: "../Base-RCNN-FPN.yaml" MODEL: WEIGHTS: "detectron2://ImageNetPretrained/MSRA/R-101.pkl" MASK_ON: False RESNETS: DEPTH: 101 ROI_HEADS: NUM_CLASSES: 3 #60 DATASETS: TRAIN: ('coco_train_base',) #('coco_trainval_base',) TEST: ('coco_test_base',) SOLVER: IMS_PER_BATCH: 2 #16 STEPS: (85,100) #(85000, 100000) MAX_ITER: 110 #110000 OUTPUT_DIR: "checkpoints/coco/faster_rcnn/faster_rcnn_R_101_FPN_base"

[03/15 17:42:57] detectron2 INFO: Full config saved to /media/hp/new/few-shot-object-detection-master/checkpoints/coco/faster_rcnn/faster_rcnn_R_101_FPN_base/config.yaml [03/15 17:42:57] d2.utils.env INFO: Using a generated random seed 57992449 [03/15 17:42:59] d2.data.build INFO: Removed 48 images with no usable annotations. 0 images left.

My Environment: I can run the train code successfully on PASCAL VOC dataset, so I don't think it is the environment that cause this problem.

[DanielWuuuuuu]

Hello! Excuse me, where is this set?

DATASETS: TRAIN: ('coco_train_base',) #('coco_trainval_base',) TEST: ('coco_test_base',)

[ppwwyyxx]

Removed 48 images with no usable annotations. 0 images left."

The logs say that the annotations are not recognized. So your annotations are not in the correct format.