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This is a continuation of the PR split (#6311, #6269) which contains the Sintel Stereo training dataset.

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Thanks @TeodorPoncu , Some minor comments but LGTM



class SintelStereo(StereoMatchingDataset):
""" "Sintel `Stereo Dataset <http://sintel.is.tue.mpg.de/stereo>`_.
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Suggested change
""" "Sintel `Stereo Dataset <http://sintel.is.tue.mpg.de/stereo>`_.
"""Sintel `Stereo Dataset <http://sintel.is.tue.mpg.de/stereo>`_.

Args:
root (string): Root directory where Sintel Stereo is located.
pass_name (string): The name of the pass to use, either "final" or "clean".
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pass_name (string): The name of the pass to use, either "final" or "clean".
pass_name (string): The name of the pass to use, either "final", "clean", or "both".

os.makedirs(split_dir, exist_ok=True)

# a single setting, since there are no splits
num_examples = {"final": 2, "clean": 2}
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Just to make sure the logic is picked up on

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num_examples = {"final": 2, "clean": 2}
num_examples = {"final": 2, "clean": 3}

# reshape into (C, H, W) format
disparity_map = np.transpose(disparity_map, (2, 0, 1))
# find the appropiate file paths
occlued_mask_path, out_of_frame_mask_path = self._get_oclussion_mask_paths(file_path)
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Nit, typo

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occlued_mask_path, out_of_frame_mask_path = self._get_oclussion_mask_paths(file_path)
occluded_mask_path, out_of_frame_mask_path = self._get_occlussion_mask_paths(file_path)

@TeodorPoncu TeodorPoncu merged commit db71802 into main Aug 17, 2022
facebook-github-bot pushed a commit that referenced this pull request Aug 24, 2022
Summary:
* added SceneFLow variant datasets

* Changed split name to variant name

* removed trailing commented code line

* Added Sintel Stereo dataset

* small refactor in tests

* Fixed doc formatting.

* candidate fix for FileNotFound on windows test

* Adressing comments

* Added Sintel Stereo dataset

* small refactor in tests

* Fixed doc formatting.

* candidate fix for FileNotFound on windows test

* Adressing comments

* rebased on main

* lint fix

Reviewed By: datumbox

Differential Revision: D38824235

fbshipit-source-id: 957fcfa5182182de47ba9f99b99a1b5712b2c754
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4 participants