pytorch/vision

Consistent argument names for video datasets and VideoClips class

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#1,227 opened on Aug 10, 2019

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enhancementhelp wantedmodule: iomodule: video

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Description

First of all, the new support for Video data is amazing. Really useful. 😃

Just when I was going through the code of the video datasets and utilities, I found this a bit confusing.

Sample Dataset: https://github.com/pytorch/vision/blob/8635be94d1216f10fb8302da89233bd86445e449/torchvision/datasets/ucf101.py#L27-L36

VideoClips class: https://github.com/pytorch/vision/blob/8635be94d1216f10fb8302da89233bd86445e449/torchvision/datasets/video_utils.py#L43-L49

From what I understand, the argument frames_per_clip from the dataset is the same as clip_length_in_frames from the VideoClips class.

Similarly, step_between_clips <-> frames_between_clips.

Is there a reason for this difference. Or did I understand it wrong?

Would it be better if both, the video datasets and the VideoClips class had consistent arguments?

In my opinion, frames_per_clip looks better than clip_length_in_frames. And frames_between_clips can be favored over step_between_clips since the former feels more intuitive.

Any suggestions? @fmassa

Contributor guide

Research direction
Identify all occurrences of `frames per clip` in video datasets and `clip length in frames` in VideoClips, and replace them with new consistent names. Also update any internal references.
Tech stack
python
Domain
computer vision
Issue type
Refactor
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
2
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
Under 1 hour
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Active
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
Clear
Prerequisites
GitPython
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
80