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iimmortall
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S2R-HDR

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Cannot get the split names for the config 'default' of the dataset.

Exception:    ReadTimeout
Message:      (ReadTimeoutError("HTTPSConnectionPool(host='huggingface.co', port=443): Read timed out. (read timeout=10)"), '(Request ID: 5da5c7d7-be9b-4629-b337-4568dbb2e132)')
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 65, in compute_split_names_from_streaming_response
                  for split in get_dataset_split_names(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 353, in get_dataset_split_names
                  info = get_dataset_config_info(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 278, in get_dataset_config_info
                  builder = load_dataset_builder(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1782, in load_dataset_builder
                  dataset_module = dataset_module_factory(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1664, in dataset_module_factory
                  raise e1 from None
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1621, in dataset_module_factory
                  return HubDatasetModuleFactoryWithoutScript(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 978, in get_module
                  standalone_yaml_path = cached_path(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/utils/file_utils.py", line 187, in cached_path
                  resolved_path = huggingface_hub.HfFileSystem(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/hf_file_system.py", line 198, in resolve_path
                  repo_and_revision_exist, err = self._repo_and_revision_exist(repo_type, repo_id, revision)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/hf_file_system.py", line 125, in _repo_and_revision_exist
                  self._api.repo_info(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/utils/_validators.py", line 114, in _inner_fn
                  return fn(*args, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/hf_api.py", line 2816, in repo_info
                  return method(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/utils/_validators.py", line 114, in _inner_fn
                  return fn(*args, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/hf_api.py", line 2673, in dataset_info
                  r = get_session().get(path, headers=headers, timeout=timeout, params=params)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/requests/sessions.py", line 602, in get
                  return self.request("GET", url, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/requests/sessions.py", line 589, in request
                  resp = self.send(prep, **send_kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/requests/sessions.py", line 703, in send
                  r = adapter.send(request, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/utils/_http.py", line 96, in send
                  return super().send(request, *args, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/requests/adapters.py", line 635, in send
                  raise ReadTimeout(e, request=request)
              requests.exceptions.ReadTimeout: (ReadTimeoutError("HTTPSConnectionPool(host='huggingface.co', port=443): Read timed out. (read timeout=10)"), '(Request ID: 5da5c7d7-be9b-4629-b337-4568dbb2e132)')

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✨Dataset Summary

S2R-HDR is a large-scale synthetic dataset for high dynamic range (HDR) reconstruction tasks. It contains 1,000 motion sequences, each comprising 24 images at 1920×1080 resolution, with a total of 24,000 images. To support flexible data augmentation, all images are stored in EXR format with linear HDR values. The dataset is rendered using Unreal Engine 5 and our custom pipeline built upon XRFeitoria, encompassing diverse dynamic elements, motion patterns, HDR-compatible scenes, and varied lighting conditions. Beyond the core imagery, we additionally provide per-frame rendered auxiliary data including optical flow, depth maps, surface normals, and diffuse albedo information, significantly expanding S2R-HDR's potential applications across various computer vision tasks.

Note: The other half of the data is stored in a separate repository: https://huggingface.co/datasets/iimmortall/S2R-HDR-2.




HDRs	Optical Flow	Depth	Diffuse	Normal

🔔News

🔥 We are pleased to announce the official release of our S2R-HDR dataset. We welcome the utilization of this resource and the provision of valuable feedback for continuous improvement.

🏭Dataset Structure

# S2R-HDR
./
├── scene_0_FM
│   ├── camera_params
│   ├── img
│   │   ├── 0000.exr
│   │   ├── [...]
│   │   ├── 0023.exr
│   ├── diffuse
│   │   ├── [...]
│   ├── flow
│   │   ├── [...]
│   ├── depth
│   │   ├── [...]
│   ├── normal
│   │   ├── [...]
├── scene_1_LM_shake
├── [...]

⚠ Note: In the suffix of the sequence name, LM/FM means that the motion mode of this sequence is Local Motion/Full Motion. Shake/No Shake means whether there is simulated camera shake in this sequence.

🏆Dataset Details

Dataset Construction

We implemented three targeted technical enhancements to enhance our synthetic dataset's photorealistic quality, content diversity, and scale.

A custom UE5 rendering pipeline was designed to preserve radiometrically linear data by disabling built-in tone mapping and gamma correction operations throughout the rendering process.
We incorporated Perlin noise-based camera shake simulation to replicate the vibrations and instabilities inherent in physical camera systems during real-world capture scenarios.
A comprehensive asset library was developed containing: 1) animated foreground elements (animals, pedestrians, vehicles); 2) environment sets covering both interior and exterior spaces; 3) distinct HDR lighting configurations simulating daylight, twilight, and nighttime conditions with detailed quantitative breakdowns provided as follows.

Motion Type	Environment	Time
Motion Type	Environment	Daylight	Twilight	Night
Local Motion	Indoor	2016	1152	432
Local Motion	Outdoor	2160	1440	1104
Full Motion	Indoor	3360	1920	720
Full Motion	Outdoor	4272	3024	2400

✏️Citation

@article{wang2025s2r,
  title={S2R-HDR: A Large-Scale Rendered Dataset for HDR Fusion},
  author={Wang, Yujin and Wu, Jiarui and Bian, Yichen and Zhang, Fan and Xue, Tianfan},
  journal={arXiv preprint arXiv:2504.07667},
  year={2025}
}

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