Open langjiliang opened 5 years ago
maxuba
commented
5 years ago do you solve this problem? I get this problem too.if you solve it, please tell me .Thank you very much.
my problems are as follow:
Traceback (most recent call last):
File "tools/train_net.py", line 213, in
zimenglan-sysu-512
commented
5 years ago i use pytorch-1.2, it meets this problem. any help is appreciated.
cnavarrete72
commented
5 years ago Did any of you manage to solve the problem? I'm getting exactly the same error as gravitymxb. Are you using your own dataset?
Yanhong-Li
commented
5 years ago I got same error too.
Traceback (most recent call last):
File "tools/train_net.py", line 191, in
Traceback (most recent call last):
File "tools/train_net.py", line 191, in
Traceback (most recent call last):
File "tools/train_net.py", line 191, in
Traceback (most recent call last):
File "tools/train_net.py", line 191, in
Traceback (most recent call last):
File "/home/liyh/anaconda3/envs/maskrcnn_benchmark/lib/python3.7/runpy.py", line 193, in _run_module_as_main
"main", mod_spec)
File "/home/liyh/anaconda3/envs/maskrcnn_benchmark/lib/python3.7/runpy.py", line 85, in _run_code
exec(code, run_globals)
File "/home/liyh/anaconda3/envs/maskrcnn_benchmark/lib/python3.7/site-packages/torch/distributed/launch.py", line 246, in
liyz15
commented
5 years ago 
sarahmass
commented
5 years ago Update: I replaced the one occurrence of torch.uint8 with torch.bool in the segmentation_mask.py file and my code is now running!
I read what little was posted under #1053 and the fix is not quite clear. I think I need the fix spelled out more clearly for me. I am trying to get the model to load and run tools/test_net.py on a Linux virtual machine. I can not seem to find a useable PyTorch version 1.1.0 for lynux for Conda=10.0 (if you have a link to one I would love to try it). The earlier version of pytorch for windows (1.1.0) is working on my desktop. I have been working on this for a couple of weeks now trying to get the VM all set up. This is the closest I have been. I appreciate any help offered. -Thanks, Sarah
zsc1220
commented
5 years ago This problem has been bothering me for a week. The key problem is that the pytorch's version is too high.Before I used version pytorch 1.2 ，it always had this error. When I changed the pytorch version to 1.1,and used this code 'python setup.py build develop' to recompile. Now my code running successfully !
zimenglan-sysu-512
commented
5 years ago hi @zsc1220
if u want to us torch-1.2.0, u should replace torch.unit8 with torch.bool in the code. more details can see here.
zsc1220
commented
5 years ago hello @zimenglan-sysu-512 so in which file i need to replace ? A little more detail，thanks a lot!
zimenglan-sysu-512
commented
5 years ago suggest that u should replace all of them
sarahmass
commented
5 years ago At the very least you should change the segmentation_mask.py file.
TheLostIn
commented
4 years ago Thanks to @zimenglan-sysu-512 , I've replaced torch.unit8 with torch.bool,and it worked.
Zy1013921842
commented
4 years ago @zimenglan-sysu-512 @zsc1220 @liyz15
Hello, friends! I'm using pytorch1.1 but I still meet the same problem and I replaced 2 torch.uint8 with torch.bool in segmatation_mask.py but it doesn't work, any advice? Thanks so much!
AllenYuQ
commented
4 years ago i use pytorch-1.2, it meets this problem. any help is appreciated.
Are u sure? The required pytorch vision for maskrcnn_bench is 1.0 or it will never be installed successfully. My torch is 1.0 and encouter the same errror.
Amir22010
commented
4 years ago I too replaced torch.unit8 with torch.bool in segmentation_mask.py and it worked :) thanks guys for helping me in rotated mask_rcnn
but i am getting warning - /pytorch/aten/src/ATen/native/IndexingUtils.h:20: UserWarning: indexing with dtype torch.uint8 is now deprecated, please use a dtype torch.bool instead.
ersen-zh
commented
4 years ago I too replaced torch.unit8 with torch.bool in segmentationmask.py and it worked ^^
❓ 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 dotrain
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": [] }