❓ Questions and Help

Hello, I have a problem. I encountered an error while training the data set. Please ask how to solve this problem. Thank you in advance.
Traceback (most recent call last):
File "tools/train_net.py", line 186, in
main()
File "tools/train_net.py", line 179, in main
model = train(cfg, args.local_rank, args.distributed)
File "tools/train_net.py", line 85, in train
arguments,
File "/home/sineva/github/maskrcnn-benchmark/maskrcnn_benchmark/engine/trainer.py", line 57, in do_train
for iteration, (images, targets, _) in enumerate(data_loader, start_iter):
File "/home/sineva/anaconda3/envs/maskrcnn_benchmark/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 582, in next
return self._process_next_batch(batch)
File "/home/sineva/anaconda3/envs/maskrcnn_benchmark/lib/python3.7/site-packages/torch/utils/data/dataloader.py", line 608, in _process_next_batch
raise batch.exc_type(batch.exc_msg)
IndexError: Traceback (most recent call last):
File "/home/sineva/anaconda3/envs/maskrcnn_benchmark/lib/python3.7/site-packages/torch/utils/data/_utils/worker.py", line 99, in _worker_loop
samples = collate_fn([dataset[i] for i in batch_indices])
File "/home/sineva/anaconda3/envs/maskrcnn_benchmark/lib/python3.7/site-packages/torch/utils/data/_utils/worker.py", line 99, in
samples = collate_fn([dataset[i] for i in batch_indices])
File "/home/sineva/anaconda3/envs/maskrcnn_benchmark/lib/python3.7/site-packages/torch/utils/data/dataset.py", line 85, in getitem
return self.datasets[dataset_idx][sample_idx]
File "/home/sineva/github/maskrcnn-benchmark/maskrcnn_benchmark/data/datasets/coco.py", line 83, in getitem
masks = SegmentationMask(masks, img.size, mode='poly')
File "/home/sineva/github/maskrcnn-benchmark/maskrcnn_benchmark/structures/segmentation_mask.py", line 467, in init
self.instances = PolygonList(instances, size)
File "/home/sineva/github/maskrcnn-benchmark/maskrcnn_benchmark/structures/segmentation_mask.py", line 344, in init
assert isinstance(polygons[0][0], (list, tuple)), str(
IndexError: list index out of range

Configuration file:

MODEL:
META_ARCHITECTURE: "GeneralizedRCNN"
WEIGHT: "catalog://ImageNetPretrained/MSRA/R-50"
BACKBONE:
CONV_BODY: "R-50-FPN"
RESNETS:
BACKBONE_OUT_CHANNELS: 256
RPN:
USE_FPN: True
ANCHOR_STRIDE: (4, 8, 16, 32, 64)
PRE_NMS_TOP_N_TRAIN: 2000
PRE_NMS_TOP_N_TEST: 1000
POST_NMS_TOP_N_TEST: 1000
FPN_POST_NMS_TOP_N_TEST: 1000
ROI_HEADS:
USE_FPN: True
ROI_BOX_HEAD:
POOLER_RESOLUTION: 7
POOLER_SCALES: (0.25, 0.125, 0.0625, 0.03125)
POOLER_SAMPLING_RATIO: 2
FEATURE_EXTRACTOR: "FPN2MLPFeatureExtractor"
PREDICTOR: "FPNPredictor"
ROI_MASK_HEAD:
POOLER_SCALES: (0.25, 0.125, 0.0625, 0.03125)
FEATURE_EXTRACTOR: "MaskRCNNFPNFeatureExtractor"
PREDICTOR: "MaskRCNNC4Predictor"
POOLER_RESOLUTION: 14
POOLER_SAMPLING_RATIO: 2
RESOLUTION: 28
SHARE_BOX_FEATURE_EXTRACTOR: False
MASK_ON: False
DATASETS:
TRAIN: ("coco_2014_train", "coco_2014_val")
TEST: ("coco_2014_test",)
DATALOADER:
SIZE_DIVISIBILITY: 32
SOLVER:
BASE_LR: 0.0025
WEIGHT_DECAY: 0.0001
STEPS: (60000, 80000)
MAX_ITER: 90000

Json file:
{
"area": 1320,
"iscrowd": 0,
"image_id": 1211098,
"bbox": [
1160,
21,
33,
40
],
"category_id": 12,
"id": 19781,
"ignore": 0,
"segmentation": []
}