duankaiwen / cpndet

Corner Proposal Network for Anchor-free, Two-stage Object Detection

cpndet's Issues

huawei cloud :ModuleNotFoundError: No module named 'moxing'how can I solve it?

Will add CPNDet to mmdet ? Thanks

got final box scores >1

i have trained my own dataset on this project, , but got final box scores >1, what's wrong

No module named 'roi_align_cuda'

ModuleNotFoundError: No module named 'roi_align_cuda'

CUDA out of memory.

Hi,

I came here following your suggestion to use this instead of CenterNet. I actually managed to train CenterNet with promising results but decided to try this out since the code base is very similar, and has more promising inference speed.

So the setup is almost exactly the same (compiling custom layers etc) but I'm heaving trouble with CUDA out of memory errors, 12% into the training which seems bizarre to me.

Env setup:
using the same instance as for training Centernet which worked fine.

• 4 x Tesla V100-SXM2 (16GB RAM), CUDA 10.1

I setup the config file of HG52 with various chunk sizes (even batch size 4, 1 image per gpu) and the same error persists.
Attaching the log below.

I will be very grateful for any advice that you might have.

LOG:
iter 1165, all: 4.9353, focal: 3.4306, grouping:0.8367, region: 0.5174, regr: 0.1507
iter 1170, all: 5.6282, focal: 3.9427, grouping:0.9505, region: 0.5869, regr: 0.1482
iter 1175, all: 5.3373, focal: 3.7071, grouping:0.8346, region: 0.6310, regr: 0.1647
iter 1180, all: 5.3797, focal: 3.7966, grouping:0.8720, region: 0.5691, regr: 0.1419
12%|████▎ | 1184/10000 [42:00<5:12:45, 2.13s/it]
Traceback (most recent call last):
File "train.py", line 203, in
train(training_dbs, validation_db, args.start_iter)
File "train.py", line 143, in train
training_loss, focal_loss, grouping_loss, region_loss,regr_loss = nnet.train(**training)
File "/home/ubuntu/CPNDet/code/nnet/py_factory.py", line 97, in train
loss.backward()
File "/home/ubuntu/CenterNet/env/lib/python3.6/site-packages/torch/tensor.py", line 118, in backward
torch.autograd.backward(self, gradient, retain_graph, create_graph)
File "/home/ubuntu/CenterNet/env/lib/python3.6/site-packages/torch/autograd/init.py", line 93, in backward
allow_unreachable=True) # allow_unreachable flag
RuntimeError: CUDA out of memory. Tried to allocate 3.86 GiB (GPU 0; 15.75 GiB total capacity; 10.16 GiB already allocated; 3.86 GiB free; 554.53 MiB cached)

ModuleNotFoundError

ModuleNotFoundError: No module named 'models./home/lenovo/lpf/CPNDet-master/code/config/DLA34-multi_scale'

when?

请教下，有统计过分类分支的acc吗，和单独的分类器模型比效果如何

这种把分类器嵌入进去进行端到端训练，和单独训练一个分类器，他们的分类精度有多大差别呢。
我现在用的是 anchor-free模型+独立分类器模型 来解决误报问题的，想尝试下你这种端到端训练的方法，请多指教

self.regions, self.groupings分别对应着哪个模块啊？

开始train出现的错误

开始训练出现的这个错误，请问这个错误解决的措施是啥哈？

When would you release?It's beyond four months now

有人训练成功了吗，我配置环境各种出错

I‘m very interested in your paper,so I want to ask When its code will be released? I'm waiting for it,online etc. , thank u.

When would you release?? It's beyond two months now

inference speed

I haven't looked at the code yet, but I'm just surprised that this work used CornerNet and added a classifier. Why is the reasoning going to be faster

.local/lib/python3.6/site-packages/roi_align-0.0.0-py3.6-linux-x86_64.egg/roi_align_cuda.cpython-36m-x86_64-linux-gnu.so: undefined symbol: _ZN3c105ErrorC1ENS_14SourceLocationERKNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEE

.local/lib/python3.6/site-packages/roi_align-0.0.0-py3.6-linux-x86_64.egg/roi_align_cuda.cpython-36m-x86_64-linux-gnu.so: undefined symbol: _ZN3c105ErrorC1ENS_14SourceLocationERKNSt7__cxx1112basic_stringIcSt11char_traitsIcESaIcEEE

RuntimeError: cuda runtime error (98) : invalid device function at CPNDet-master/codes/models/py_utils/roi_extractors/ops/roi_align/src/roi_align_kernel.cu:139

Someone encountered such a problem？

One class testing

Hi,

I trained a model on a single class (human heads-for object detection), and now when running the testing script I'm having problems with filtering boxes.

The log attached below narrows down the problem to: this line where the region scores are gathered. However, I think it's because of the way sigmoid is used to obtain them in the first place, which works well for many classes but in my one-class detection, it fails .

Do you have any advice on this matter?

Log below:

Traceback (most recent call last):
File "test.py", line 105, in
test(testing_db, args.cfg_file, args.split, args.testiter, args.debug, args.no_flip, args.suffix)
File "test.py", line 67, in test
testing(db, cfg_file , nnet, result_dir, debug=debug, no_flip = no_flip)
File "/home/ubuntu/CPNDet/code/test/coco.py", line 342, in testing
return globals()[system_configs.sampling_function](db, cfg_file, nnet, result_dir, debug=debug, no_flip=no_flip)
File "/home/ubuntu/CPNDet/code/test/coco.py", line 238, in kp_detection
dets = decode_func(nnet, images, K, no_flip, ae_threshold=ae_threshold, kernel=nms_kernel, image_idx = image_idx)
File "/home/ubuntu/CPNDet/code/test/coco.py", line 62, in kp_decode
detections = nnet.test([images], ae_threshold=ae_threshold, K=K, no_flip = no_flip, kernel=kernel, image_idx = image_idx)
File "/home/ubuntu/CPNDet/code/nnet/py_factory.py", line 115, in test
return self.model(*xs, **kwargs)
File "/home/ubuntu/CPNDet/env/lib/python3.7/site-packages/torch/nn/modules/module.py", line 547, in call
result = self.forward(*input, **kwargs)
File "/home/ubuntu/CPNDet/code/nnet/py_factory.py", line 33, in forward
return self.module(*xs, **kwargs)
File "/home/ubuntu/CPNDet/env/lib/python3.7/site-packages/torch/nn/modules/module.py", line 547, in call
result = self.forward(*input, **kwargs)
File "/home/ubuntu/CPNDet/code/models/py_utils/HG52.py", line 452, in forward
return self._test(*xs, **kwargs)
File "/home/ubuntu/CPNDet/code/models/py_utils/HG52.py", line 433, in _test
_filter_bboxes(ht_boxes, tl_clses, region_scores, grouping_scores, self.gr_threshold)
File "/home/ubuntu/CPNDet/code/models/py_utils/kp_utils.py", line 159, in _filter_bboxes
specific_rscores = region_scores.gather(1, ppos_ht_score_cls[:,1].long()).squeeze()
IndexError: Dimension out of range (expected to be in range of [-1, 0], but got 1)

什么鬼？至少改一下readme吧？

training is slow.

training is slow.

How can I make the input size I'm testing match my actual image size?

The size of my test image is 512512, but when I run the command:python test.py --cfg_file HG52 --testiter 270000 --split testing , the size of the input image is 639639, before the self.pre . I looked through all the files and couldn't find the value 639 set anywhere. (The size of my train image is also 512512, I found the size of the input image is 512512). How can I make the input size I'm testing match my actual image size?

warning:/opt/conda/conda-bld/pytorch_1565272279342/work/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:14: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.

/opt/conda/conda-bld/pytorch_1565272279342/work/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:114: UserWarning: torch.gt received 'out' parameter with dtype torch.uint8, this behavior is now deprecated,please use 'out' parameter with dtype torch.bool instead.
/opt/conda/conda-bld/pytorch_1565272279342/work/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:38: UserWarning: masked_scatter_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.
/opt/conda/conda-bld/pytorch_1565272279342/work/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:114: UserWarning: torch.gt received 'out' parameter with dtype torch.uint8, this behavior is now deprecated,please use 'out' parameter with dtype torch.bool instead.
/opt/conda/conda-bld/pytorch_1565272279342/work/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:14: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.
/opt/conda/conda-bld/pytorch_1565272279342/work/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:38: UserWarning: masked_scatter_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.
/opt/conda/conda-bld/pytorch_1565272279342/work/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:14: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.
/opt/conda/conda-bld/pytorch_1565272279342/work/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:14: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.
/opt/conda/conda-bld/pytorch_1565272279342/work/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:38: UserWarning: masked_scatter_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.
/opt/conda/conda-bld/pytorch_1565272279342/work/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:14: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.
/opt/conda/conda-bld/pytorch_1565272279342/work/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:14: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.
/opt/conda/conda-bld/pytorch_1565272279342/work/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:14: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.
/opt/conda/conda-bld/pytorch_1565272279342/work/aten/src/ATen/native/cuda/LegacyDefinitions.cpp:14: UserWarning: masked_fill_ received a mask with dtype torch.uint8, this behavior is now deprecated,please use a mask with dtype torch.bool instead.
我在训练的时候有这个warning,我该怎么修改它呢?环境都是按照说明搭建的.

How to train on my own dataset?

SO what's the CUDA version?It always goes wrong in CUDA9.0

Could you provide the pre-training model of HG104？Thanks

Could you provide the pre-training model of HG104？Thanks

When would you release?It's beyond three months now