Help with dataset

[SebastianJanampa]

Hello,
Thanks for your incredible work. I want to replicate your training. I've already downloaded the laval dataset. But when I try to create the openpano dataset I've got messages saying that some images are missing. Could you please guide me on what I am doing wrong?

Regards,
Sebastian

geocalib) sebastian@SebasJR:~/GeoCalib$ python -m siclib.datasets.utils.tonemapping --hdr_dir data/indoorDatasetCalibrated --out_dir data/laval-tonemap
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(geocalib) sebastian@SebasJR:~/GeoCalib$ python -m siclib.datasets.utils.download_openpano --name openpano --laval_dir data/laval-tonemap
[12/10/2024 08:03:57 siclib INFO] Downloading dataset openpano to data/openpano.zip from https://cvg-data.inf.ethz.ch/GeoCalib_ECCV2024/openpano.zip.
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[12/10/2024 08:07:57 siclib INFO] Extracting dataset openpano in data.
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Copying train panoramas:  79%|███████████   | 1795/2262 [00:28<00:10, 46.05it/s][12/10/2024 08:08:45 siclib WARNING] Panorama AG8A7296-2533a0187c.jpg not found in data/laval-tonemap or train split.
Copying train panoramas:  80%|███████████▏  | 1814/2262 [00:28<00:09, 48.03it/s][12/10/2024 08:08:46 siclib WARNING] Panorama AG8A7513-d1348b4f80.jpg not found in data/laval-tonemap or train split.
Copying train panoramas:  81%|███████████▎  | 1834/2262 [00:29<00:10, 42.35it/s][12/10/2024 08:08:46 siclib WARNING] Panorama AG8A7776-627c511f0e.jpg not found in data/laval-tonemap or train split.
Copying train panoramas:  82%|███████████▍  | 1850/2262 [00:29<00:10, 40.05it/s][12/10/2024 08:08:47 siclib WARNING] Panorama AG8A7967-8133e2831c.jpg not found in data/laval-tonemap or train split.
Copying train panoramas:  82%|███████████▌  | 1866/2262 [00:30<00:10, 39.53it/s][12/10/2024 08:08:47 siclib WARNING] Panorama AG8A8112-0c528e8513.jpg not found in data/laval-tonemap or train split.
Copying train panoramas:  85%|███████████▉  | 1923/2262 [00:31<00:13, 25.83it/s][12/10/2024 08:08:49 siclib WARNING] Panorama AG8A8689-c0d7cfb1ba.jpg not found in data/laval-tonemap or train split.
Copying train panoramas:  85%|███████████▉  | 1928/2262 [00:31<00:11, 29.28it/s][12/10/2024 08:08:49 siclib WARNING] Panorama AG8A8731-3b7577627c.jpg not found in data/laval-tonemap or train split.
Copying train panoramas:  85%|███████████▉  | 1932/2262 [00:32<00:10, 30.24it/s][12/10/2024 08:08:49 siclib WARNING] Panorama AG8A8771-5b70b376bb.jpg not found in data/laval-tonemap or train split.
Copying train panoramas:  86%|████████████  | 1940/2262 [00:32<00:10, 31.26it/s][12/10/2024 08:08:50 siclib WARNING] Panorama AG8A8826-ced9970e61.jpg not found in data/laval-tonemap or train split.
Copying train panoramas:  86%|████████████  | 1951/2262 [00:32<00:11, 27.40it/s][12/10/2024 08:08:50 siclib WARNING] Panorama AG8A8890-647a533866.jpg not found in data/laval-tonemap or train split.
Copying train panoramas:  86%|████████████  | 1955/2262 [00:32<00:10, 28.66it/s][12/10/2024 08:08:50 siclib WARNING] Panorama AG8A8932-951d0ce7ed.jpg not found in data/laval-tonemap or train split.
Copying train panoramas:  90%|████████████▌ | 2035/2262 [00:35<00:08, 25.92it/s][12/10/2024 08:08:53 siclib WARNING] Panorama AG8A9675-9c247ed7bf.jpg not found in data/laval-tonemap or train split.
Copying train panoramas:  91%|████████████▋ | 2056/2262 [00:37<00:20,  9.85it/s][12/10/2024 08:08:55 siclib WARNING] Panorama AG8A9906-b8c733941d.jpg not found in data/laval-tonemap or train split.
Copying train panoramas:  91%|████████████▋ | 2060/2262 [00:37<00:14, 14.02it/s][12/10/2024 08:08:55 siclib WARNING] Panorama AG8A9942-4849a42054.jpg not found in data/laval-tonemap or train split.
Copying train panoramas: 100%|██████████████| 2262/2262 [00:38<00:00, 59.39it/s]
Copying test panoramas:   0%|                           | 0/148 [00:00<?, ?it/s][12/10/2024 08:08:55 siclib WARNING] Panorama 9C4A0111-99b1013803.jpg not found in data/laval-tonemap or test split.
Copying test panoramas:   7%|█▏                | 10/148 [00:00<00:02, 65.22it/s][12/10/2024 08:08:55 siclib WARNING] Panorama 9C4A1086-fa0e9c5fbf.jpg not found in data/laval-tonemap or test split.
Copying test panoramas:  14%|██▌               | 21/148 [00:00<00:02, 60.41it/s][12/10/2024 08:08:56 siclib WARNING] Panorama 9C4A1662-83ea2bdfa7.jpg not found in data/laval-tonemap or test split.
Copying test panoramas:  30%|█████▎            | 44/148 [00:03<00:09, 11.23it/s][12/10/2024 08:08:58 siclib WARNING] Panorama 9C4A6597-1e6d8b2f0f.jpg not found in data/laval-tonemap or test split.
Copying test panoramas:  49%|████████▉         | 73/148 [00:06<00:10,  7.41it/s][12/10/2024 08:09:01 siclib WARNING] Panorama AG8A0001-3e70e8fe05.jpg not found in data/laval-tonemap or test split.
Copying test panoramas:  55%|█████████▉        | 82/148 [00:07<00:08,  7.66it/s][12/10/2024 08:09:02 siclib WARNING] Panorama AG8A1369-99c4d08e50.jpg not found in data/laval-tonemap or test split.
Copying test panoramas:  63%|███████████▎      | 93/148 [00:08<00:06,  8.07it/s][12/10/2024 08:09:04 siclib WARNING] Panorama AG8A6635-78aac54b21.jpg not found in data/laval-tonemap or test split.
Copying test panoramas:  68%|███████████▍     | 100/148 [00:09<00:07,  6.51it/s][12/10/2024 08:09:05 siclib WARNING] Panorama AG8A7566-95ae4643ec.jpg not found in data/laval-tonemap or test split.
Copying test panoramas:  70%|███████████▊     | 103/148 [00:09<00:05,  7.91it/s][12/10/2024 08:09:05 siclib WARNING] Panorama AG8A8051-39db7d081a.jpg not found in data/laval-tonemap or test split.
Copying test panoramas: 100%|█████████████████| 148/148 [00:11<00:00, 13.04it/s]
Copying val panoramas:   0%|                            | 0/147 [00:00<?, ?it/s][12/10/2024 08:09:07 siclib WARNING] Panorama 9C4A0001-7c62497929.jpg not found in data/laval-tonemap or val split.
Copying val panoramas:  15%|██▊                | 22/147 [00:00<00:03, 32.20it/s][12/10/2024 08:09:07 siclib WARNING] Panorama 9C4A1788-b3bf34938b.jpg not found in data/laval-tonemap or val split.
Copying val panoramas:  46%|████████▋          | 67/147 [00:04<00:04, 19.73it/s][12/10/2024 08:09:11 siclib WARNING] Panorama AG8A0001-bababfcd36.jpg not found in data/laval-tonemap or val split.
Copying val panoramas:  53%|██████████         | 78/147 [00:05<00:03, 22.78it/s][12/10/2024 08:09:12 siclib WARNING] Panorama AG8A3176-2078222492.jpg not found in data/laval-tonemap or val split.
Copying val panoramas: 100%|██████████████████| 147/147 [00:07<00:00, 20.79it/s]
[12/10/2024 08:09:14 siclib INFO] openpano contains 2150/139/143 train/test/val panoramas.
(geocalib) sebastian@SebasJR:~/GeoCalib$ python -m siclib.datasets.create_dataset_from_pano --config-name openpano n_workers=10 device=cuda
[2024-12-10 08:10:09,964][__main__][INFO] - Config:
name: openpano
base_dir: data/openpano
pano_dir: ${.base_dir}/panoramas
pano_train: ${.pano_dir}/train
pano_val: ${.pano_dir}/val
pano_test: ${.pano_dir}/test
perspective_dir: ${.base_dir}/${.name}
perspective_train: ${.perspective_dir}/train
perspective_val: ${.perspective_dir}/val
perspective_test: ${.perspective_dir}/test
train_csv: ${.perspective_dir}/train.csv
val_csv: ${.perspective_dir}/val.csv
test_csv: ${.perspective_dir}/test.csv
camera_model: pinhole
parameter_dists:
  roll:
    type: uniform
    options:
      loc: -0.7853981633974483
      scale: 1.5707963267948966
  pitch:
    type: uniform
    options:
      loc: -0.7853981633974483
      scale: 1.5707963267948966
  vfov:
    type: uniform
    options:
      loc: 0.3490658503988659
      scale: 1.48352986419518
  resize_factor:
    type: uniform
    options:
      loc: 1.2
      scale: 0.5
  shape:
    type: fix
    value:
    - 640
    - 640
images_per_pano: 16
n_workers: 10
device: cuda
overwrite: true
resize_factor: null

[2024-12-10 08:10:09,985][__main__][INFO] - Writing perspective images to data/openpano/openpano/train
Processing train:   0%|                        | 5/2150 [00:08<39:23,  1.10s/it]Error executing job with overrides: ['n_workers=10', 'device=cuda']
concurrent.futures.process._RemoteTraceback: 
"""
Traceback (most recent call last):
  File "/home/sebastian/anaconda3/envs/geocalib/lib/python3.9/concurrent/futures/process.py", line 246, in _process_worker
    r = call_item.fn(*call_item.args, **call_item.kwargs)
  File "/home/sebastian/GeoCalib/siclib/datasets/create_dataset_from_pano.py", line 279, in generate_images_from_pano
    perspective_images = cam.get_img_from_pano(
  File "/home/sebastian/GeoCalib/siclib/geometry/base_camera.py", line 473, in get_img_from_pano
    resized_pano = F.interpolate(pano_img, size=pano_shape, mode=mode)
  File "/home/sebastian/anaconda3/envs/geocalib/lib/python3.9/site-packages/torch/nn/functional.py", line 4552, in interpolate
    return adaptive_avg_pool2d(input, output_size)
  File "/home/sebastian/anaconda3/envs/geocalib/lib/python3.9/site-packages/torch/nn/functional.py", line 1382, in adaptive_avg_pool2d
    return torch._C._nn.adaptive_avg_pool2d(input, _output_size)
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 94.00 MiB. GPU 0 has a total capacity of 23.57 GiB of which 95.56 MiB is free. Including non-PyTorch memory, this process has 2.41 GiB memory in use. Process 2437650 has 3.29 GiB memory in use. Process 2437654 has 3.32 GiB memory in use. Process 2437649 has 3.97 GiB memory in use. Process 2437655 has 1.34 GiB memory in use. Process 2437652 has 2.23 GiB memory in use. Process 2437656 has 2.00 GiB memory in use. Process 2437651 has 2.26 GiB memory in use. Process 2437653 has 1.41 GiB memory in use. Process 2437660 has 248.00 MiB memory in use. Of the allocated memory 2.12 GiB is allocated by PyTorch, and 13.19 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)
"""

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/home/sebastian/GeoCalib/siclib/datasets/create_dataset_from_pano.py", line 346, in main
    generator.generate_dataset()
  File "/home/sebastian/GeoCalib/siclib/datasets/create_dataset_from_pano.py", line 332, in generate_dataset
    self.generate_split(split=split, parallel_processor=processor)
  File "/home/sebastian/GeoCalib/siclib/datasets/create_dataset_from_pano.py", line 316, in generate_split
    self.infos[split] = parallel_processor.wait_for_completion(futures)
  File "/home/sebastian/GeoCalib/siclib/datasets/create_dataset_from_pano.py", line 84, in wait_for_completion
    results += f.result()
  File "/home/sebastian/anaconda3/envs/geocalib/lib/python3.9/concurrent/futures/_base.py", line 446, in result
    return self.__get_result()
  File "/home/sebastian/anaconda3/envs/geocalib/lib/python3.9/concurrent/futures/_base.py", line 391, in __get_result
    raise self._exception
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 94.00 MiB. GPU 0 has a total capacity of 23.57 GiB of which 95.56 MiB is free. Including non-PyTorch memory, this process has 2.41 GiB memory in use. Process 2437650 has 3.29 GiB memory in use. Process 2437654 has 3.32 GiB memory in use. Process 2437649 has 3.97 GiB memory in use. Process 2437655 has 1.34 GiB memory in use. Process 2437652 has 2.23 GiB memory in use. Process 2437656 has 2.00 GiB memory in use. Process 2437651 has 2.26 GiB memory in use. Process 2437653 has 1.41 GiB memory in use. Process 2437660 has 248.00 MiB memory in use. Of the allocated memory 2.12 GiB is allocated by PyTorch, and 13.19 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation.  See documentation for Memory Management  (https://pytorch.org/docs/stable/notes/cuda.html#environment-variables)

Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.
Processing train: 100%|█████████████████████| 2150/2150 [09:17<00:00,  3.86it/s]
(geocalib) sebastian@SebasJR:~/GeoCalib$ 

[veichta]

Thank you for your kind words and for bringing this to our attention!

It seems that there might be fewer images in the tonemapping step than expected. While we do not use all panoramas from the Laval dataset — since some are not well aligned to gravity — I remember the total count to be closer to 2400 panoramas. It’s possible that the dataset has undergone slight changes since we initially worked with it.

We will investigate this further and provide an update once we have more information. In the meantime, this should not significantly impact your training results, as the majority of the images seem to be available.

[SebastianJanampa]

Hi @veichta ,
Thanks for your quick answer. I tried to train the model; however, I got some error #17 . Could you point out what I am doing wrong? I debugged, but I couldn't solve it.

[sarlinpe]

Thanks for reporting this - we were actually linking to the wrong dataset. Please request to download this one instead: http://hdrdb.com/indoor-hdr-photometric/ The documentation is fixed in fbd383d.