CVI-SZU/CLIMS

Undefined Function get_dataset

Spritea opened this issue · 15 comments

Hi,

When I run CUDA_VISIBLE_DEVICES=0 bash run_voc12_coco_pretrained.sh to train DeepLab v2, I met following error.

Traceback (most recent call last):
  File "main.py", line 26, in <module>
    from libs.datasets import get_dataset
ImportError: cannot import name 'get_dataset' from 'libs.datasets' (unknown location)

It looks like the function get_dataset is not defined. Could you check, thanks!

I have copied the file __init__.py from here and put it under the folder segmentation/deeplabv2/libs/datasets/, and the above error is solved. But I met a new error below:

Traceback (most recent call last):
  File "main.py", line 26, in <module>
    from libs.datasets import get_dataset
  File "/home/wensheng/code/for_dev/CLIMS/segmentation/deeplabv2/libs/datasets/__init__.py", line 1, in <module>
    from .voc import VOC, VOCAug
  File "/home/wensheng/code/for_dev/CLIMS/segmentation/deeplabv2/libs/datasets/voc.py", line 19, in <module>
    from .base import _BaseDataset, _BaseDatasetTest, _BaseDatasetCotrain
ImportError: cannot import name '_BaseDatasetCotrain' from 'libs.datasets.base' (/home/wensheng/code/for_dev/CLIMS/segmentation/deeplabv2/libs/datasets/base.py)

Could you check as well?

Try to comment _BaseDatasetCotrain.

Thanks! I have solved the _BaseDatasetCotrain error by removing _BaseDatasetCotrain from this line.

Then I met other import related errors, and I solved them by copying another two __init__.py files. Specifically,

  • copy the __init__.py from here and put it under the folder segmentation/deeplabv2/libs/models. This solves the error below:
Traceback (most recent call last):
  File "main.py", line 27, in <module>
    from libs.models import DeepLabV2_ResNet101_MSC
ImportError: cannot import name 'DeepLabV2_ResNet101_MSC' from 'libs.models' (unknown location)
  • copy the __init__.py from this place and put it under the folder segmentation/deeplabv2/libs/utils. This solves the error below:
Traceback (most recent call last):
  File "main.py", line 28, in <module>
    from libs.utils import DenseCRF, PolynomialLR, scores
ImportError: cannot import name 'DenseCRF' from 'libs.utils' (unknown location)

After these copy things, I think no .py files are missing.

However, I met another error about the dataset:

FileNotFoundError: [Errno 2] No such file or directory: '../../data/VOC2012/ImageSets/Segmentation/train_aug.txt'

I tried to compare the segmentation/deeplabv2/libs/datasets/voc.py with this file, and found the latter uses the path ImageSets/SegmentationAug. So I guess this tutorial for making augmented PASCAL VOC dataset may not be applicable here, and I'm not sure how the augmented PASCAL VOC dataset for CLIMS is formed.

Could you explain how to make the augmented dataset in detail (like this), and how it is organized (including all subdirectories)? This tree structure in the readme does not include subdirectories/specific txt files, and does not specify the way to make the augmented dataset. This would be a key help, thanks!

Sorry for the bugs. I have uploaded the corresponding __init__.py. GT of 'trainaug' data can be downloaded at here. label can be downloaded at here.

Thanks for the update! Could you specify in detail how the augmented PASCAL VOC dataset is organized? This issue seems unresolved.

After these copy things, I think no .py files are missing.

However, I met another error about the dataset:

FileNotFoundError: [Errno 2] No such file or directory: '../../data/VOC2012/ImageSets/Segmentation/train_aug.txt'

I tried to compare the segmentation/deeplabv2/libs/datasets/voc.py with this file, and found the latter uses the path ImageSets/SegmentationAug. So I guess this tutorial for making augmented PASCAL VOC dataset may not be applicable here, and I'm not sure how the augmented PASCAL VOC dataset for CLIMS is formed.

Could you explain how to make the augmented dataset in detail (like this), and how it is organized (including all subdirectories)? This tree structure in the readme does not include subdirectories/specific txt files, and does not specify the way to make the augmented dataset. This would be a key help, thanks!

Hi, just unzip the segmentationaug.rar and put .txt files into your data root ../../data/VOC2012/ImageSets/Segmentation/.

Thanks for the guidance! I have put these txt files into the data root folder, but then I got the following error.

Traceback (most recent call last):
  File "main.py", line 506, in <module>
    main()
  File "/home/wensheng/anaconda3/envs/clims/lib/python3.8/site-packages/click/core.py", line 1130, in __call__
    return self.main(*args, **kwargs)
  File "/home/wensheng/anaconda3/envs/clims/lib/python3.8/site-packages/click/core.py", line 1055, in main
    rv = self.invoke(ctx)
  File "/home/wensheng/anaconda3/envs/clims/lib/python3.8/site-packages/click/core.py", line 1657, in invoke
    return _process_result(sub_ctx.command.invoke(sub_ctx))
  File "/home/wensheng/anaconda3/envs/clims/lib/python3.8/site-packages/click/core.py", line 1404, in invoke
    return ctx.invoke(self.callback, **ctx.params)
  File "/home/wensheng/anaconda3/envs/clims/lib/python3.8/site-packages/click/core.py", line 760, in invoke
    return __callback(*args, **kwargs)
  File "main.py", line 226, in train
    _, images, labels = next(loader_iter)
  File "/home/wensheng/anaconda3/envs/clims/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 517, in __next__
    data = self._next_data()
  File "/home/wensheng/anaconda3/envs/clims/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 557, in _next_data
    data = self._dataset_fetcher.fetch(index)  # may raise StopIteration
  File "/home/wensheng/anaconda3/envs/clims/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch
    data = [self.dataset[idx] for idx in possibly_batched_index]
  File "/home/wensheng/anaconda3/envs/clims/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py", line 44, in <listcomp>
    data = [self.dataset[idx] for idx in possibly_batched_index]
  File "/home/wensheng/code/for_dev/CLIMS/segmentation/deeplabv2/libs/datasets/base.py", line 107, in __getitem__
    image_id, image, label = self._load_data(index)
  File "/home/wensheng/code/for_dev/CLIMS/segmentation/deeplabv2/libs/datasets/voc.py", line 161, in _load_data
    image = cv2.imread(image_path, cv2.IMREAD_COLOR).astype(np.float32)
AttributeError: 'NoneType' object has no attribute 'astype'

I found the problem comes from below function (copied from here)

    def _load_data(self, index):
        # Set paths
        image_id = self.files[index]
        image_path = osp.join(self.image_dir, image_id + ".jpg")
        label_path = osp.join(self.label_dir, image_id + ".png")
        # Load an image
        image = cv2.imread(image_path, cv2.IMREAD_COLOR).astype(np.float32)
        label = np.asarray(Image.open(label_path), dtype=np.int32)
        return image_id, image, label

image_dir has value ../../data/VOC2012/JPEGImages, and image_id has value /JPEGImages/2010_003067.jpg /SegmentationClassAug/2010_003067.png (one line from the train_aug.txt I think). This makes the image_path wrong, and hence cv2.imread cannot work. I guess the _load_data function is not compatible with the train_aug.txt file. It seems that the image_id should be someting like 2007_000032 only. Could you please have a look?

I have downloaded the file list from my personal server. Try this one

I have downloaded the file list from my personal server. Try this one

Eh, it seems that I do not have the access permission.

Try this one

Try this one

Thanks for sharing! Now I can run the training process for DeepLab v2 with the file above.
It looks like the first 2 lines shown below in this shell can run normally,

OMP_NUM_THREADS=32 CUDA_VISIBLE_DEVICES=6 python main.py train --config-path configs/voc12_coco_pretrained.yaml
OMP_NUM_THREADS=32 CUDA_VISIBLE_DEVICES=6 python main.py test --config-path configs/voc12_coco_pretrained.yaml --model-path data/models/voc12_coco_pretrained/deeplabv2_resnet101_msc/train_aug/checkpoint_final.pth

But when it goes to the crf command OMP_NUM_THREADS=32 CUDA_VISIBLE_DEVICES=6 python main.py crf --config-path configs/voc12_coco_pretrained.yaml, I met the following error:

Mode: crf
# jobs: 64
Dataset: VOCAug
    # data: 1449
    Split: val
    Root: ../../data/VOC2012
Logit src: data/features/voc12_coco_pretrained/deeplabv2_resnet101_msc/val/logit
Score dst: data/scores/voc12_coco_pretrained/deeplabv2_resnet101_msc/val/scores_crf.json
[Parallel(n_jobs=64)]: Using backend LokyBackend with 64 concurrent workers.
[Parallel(n_jobs=64)]: Done 145 out of 1449 | elapsed:   22.0s remaining:  3.3min
[Parallel(n_jobs=64)]: Done 290 out of 1449 | elapsed:   39.1s remaining:  2.6min
[Parallel(n_jobs=64)]: Done 435 out of 1449 | elapsed:   57.0s remaining:  2.2min
[Parallel(n_jobs=64)]: Done 580 out of 1449 | elapsed:  1.2min remaining:  1.9min
[Parallel(n_jobs=64)]: Done 725 out of 1449 | elapsed:  1.6min remaining:  1.6min
[Parallel(n_jobs=64)]: Done 870 out of 1449 | elapsed:  1.9min remaining:  1.2min
[Parallel(n_jobs=64)]: Done 1015 out of 1449 | elapsed:  2.2min remaining:   56.1s
[Parallel(n_jobs=64)]: Done 1160 out of 1449 | elapsed:  2.5min remaining:   37.2s
[Parallel(n_jobs=64)]: Done 1305 out of 1449 | elapsed:  2.8min remaining:   18.7s
[Parallel(n_jobs=64)]: Done 1449 out of 1449 | elapsed:  3.1min finished
mIoU: 0.6634496325417438
Device:
    0: NVIDIA RTX A5000
Traceback (most recent call last):
  File "eval.py", line 341, in <module>
    evaluation(config_path=args.config_path, model_path=args.model_path)
  File "eval.py", line 52, in evaluation
    dataset = get_dataset('voc_test')(
  File "/home/wensheng/code/for_dev/CLIMS/segmentation/deeplabv2/libs/datasets/__init__.py", line 6, in get_dataset
    return {
KeyError: 'voc_test'

Could you please have a look?

Hi, as you copy __init__.py from deeplab-pytorch repository, voc_test was not imported. Adding the code below to libs/datasets/__init__.py can work.

from .voc import VOC, VOCAug, VOC_test
from .cocostuff import CocoStuff10k, CocoStuff164k


def get_dataset(name):
    return {
        "cocostuff10k": CocoStuff10k,
        "cocostuff164k": CocoStuff164k,
        "voc": VOC,
        "vocaug": VOCAug,
        "voc_test": VOC_test,  # for test set
    }[name]

Thanks! I have updated the libs/datasets/__init__.py file, and the crf command OMP_NUM_THREADS=32 CUDA_VISIBLE_DEVICES=6 python main.py crf --config-path configs/voc12_coco_pretrained.yaml works.

Then when I run the eval command below:

OMP_NUM_THREADS=32 CUDA_VISIBLE_DEVICES=0 python eval.py --config_path configs/voc12_coco_pretrained.yaml --model_path data/models/voc12_coco_pretrained/deeplabv2_resnet101_msc/train_aug/checkpoint_final.pth

I met the following error:

Device:
    0: NVIDIA RTX A5000
Dataset: VOC_test
    # data: 1456
    Split: test
    Root: ../../data/VOC2012
Logit dst: data/features/voc12_coco_pretrained/deeplabv2_resnet101_msc/test/logit
  0%|                                                     | 0/1456 [00:00<?, ?it/s][ WARN:0@3.541] global loadsave.cpp:244 findDecoder imread_('../../data/VOC
2012/JPEGImages/2008_000006.jpg'): can't open/read file: check file path/integrity
  0%|                                                     | 0/1456 [00:00<?, ?it/s]
Traceback (most recent call last):
  File "eval.py", line 341, in <module>
    evaluation(config_path=args.config_path, model_path=args.model_path)
  File "eval.py", line 102, in evaluation
    for image_ids, images in tqdm(
  File "/home/wensheng/anaconda3/envs/clims/lib/python3.8/site-packages/tqdm/std.py", line 1195, in __iter__
    for obj in iterable:
  File "/home/wensheng/anaconda3/envs/clims/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 517, in __next__
    data = self._next_data()
  File "/home/wensheng/anaconda3/envs/clims/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 557, in _next_data
    data = self._dataset_fetcher.fetch(index)  # may raise StopIteration
  File "/home/wensheng/anaconda3/envs/clims/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py", line 44, in fetch
    data = [self.dataset[idx] for idx in possibly_batched_index]
  File "/home/wensheng/anaconda3/envs/clims/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py", line 44, in <listcomp>
    data = [self.dataset[idx] for idx in possibly_batched_index]
  File "/home/wensheng/code/for_dev/CLIMS/segmentation/deeplabv2/libs/datasets/base.py", line 215, in __getitem__
    image_id, image = self._load_data(index)
  File "/home/wensheng/code/for_dev/CLIMS/segmentation/deeplabv2/libs/datasets/voc.py", line 195, in _load_data
    image = cv2.imread(image_path, cv2.IMREAD_COLOR).astype(np.float32)
AttributeError: 'NoneType' object has no attribute 'astype'

Then I realized I need to copy those .jpg images in test_set of PASCAL VOC 2012 to the VOC2012/JPEGImages. After this copy, then the eval command runs well. Then I zip the results and submit it to the PASCAL VOC server, and get the 71.69720 mIoU (Object Segmentation (comp5))

BTW, there is a typo in this place, where the command should be changed from cd data/features/voc12_imagenet_pretrained/deeplabv2_resnet101_msc/test/ to cd data/features/voc12_coco_pretrained/deeplabv2_resnet101_msc/test/.

Thanks for your all help!

Thanks for helping me to fix the bugs in the code and pointing out the typo.