Add video classification pipeline
Author: nateraw
Pull request: yes

# What does this PR do?

<!--
Congratulations! You've made it this far! You're not quite done yet though.

Once merged, your PR is going to appear in the release notes with the title you set, so make sure it's a great title that fully reflects the extent of your awesome contribution.

Then, please replace this with a description of the change and which issue is fixed (if applicable). Please also include relevant motivation and context. List any dependencies (if any) that are required for this change.

Once you're done, someone will review your PR shortly (see the section "Who can review?" below to tag some potential reviewers). They may suggest changes to make the code even better. If no one reviewed your PR after a week has passed, don't hesitate to post a new comment @-mentioning the same persons---sometimes notifications get lost.
-->

<!-- Remove if not applicable -->

Adds a video classification pipeline using VideoMAE.

Fixes # (issue)


## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case).
- [x] Did you read the [contributor guideline](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md#start-contributing-pull-requests),
      Pull Request section?
- [ ] Was this discussed/approved via a Github issue or the [forum](https://discuss.huggingface.co/)? Please add a link
      to it if that's the case.
- [x] Did you make sure to update the documentation with your changes? Here are the
      [documentation guidelines](https://github.com/huggingface/transformers/tree/main/docs), and
      [here are tips on formatting docstrings](https://github.com/huggingface/transformers/tree/main/docs#writing-source-documentation).
- [x] Did you write any new necessary tests?


## Who can review?

Anyone in the community is free to review the PR once the tests have passed. Feel free to tag
members/contributors who may be interested in your PR.

<!-- Your PR will be replied to more quickly if you can figure out the right person to tag with @

 If you know how to use git blame, that is the easiest way, otherwise, here is a rough guide of **who to tag**.
 Please tag fewer than 3 people.

Models:

- albert, bert, xlm: @LysandreJik
- blenderbot, bart, marian, pegasus, encoderdecoder,  t5: @patrickvonplaten, @patil-suraj
- longformer, reformer, transfoxl, xlnet: @patrickvonplaten
- fsmt: @stas00
- funnel: @sgugger
- gpt2: @patrickvonplaten, @LysandreJik
- rag: @patrickvonplaten, @lhoestq
- tensorflow: @LysandreJik

Library:

- benchmarks: @patrickvonplaten
- deepspeed: @stas00
- ray/raytune: @richardliaw, @amogkam
- text generation: @patrickvonplaten
- tokenizers: @n1t0, @LysandreJik
- trainer: @sgugger
- pipelines: @LysandreJik

Documentation: @sgugger

HF projects:

- datasets: [different repo](https://github.com/huggingface/datasets)
- rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)

Examples:

- maintained examples (not research project or legacy): @sgugger, @patil-suraj
- research_projects/bert-loses-patience: @JetRunner
- research_projects/distillation: @VictorSanh

 -->


Comments:
_The documentation is not available anymore as the PR was closed or merged._

The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_20151). All of your documentation changes will be reflected on that endpoint.

The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_20151). All of your documentation changes will be reflected on that endpoint.

The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_20151). All of your documentation changes will be reflected on that endpoint.

The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_20151). All of your documentation changes will be reflected on that endpoint.

The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_20151). All of your documentation changes will be reflected on that endpoint.

The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_20151). All of your documentation changes will be reflected on that endpoint.

The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_20151). All of your documentation changes will be reflected on that endpoint.

The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_20151). All of your documentation changes will be reflected on that endpoint.

The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_20151). All of your documentation changes will be reflected on that endpoint.

Holding off on this PR as we discuss https://github.com/huggingface/datasets/issues/5225 - I think I will update the PR here to use `av` instead of `decord` because of it. Feel free to join the conversation there.

---

edit: wrong issue link

> Holding off on this PR as we discuss #5225 - I think I will update the PR here to use `av` instead of `decord` because of it. Feel free to join the conversation there.

Your link is wrong I think, you meant https://github.com/huggingface/datasets/issues/5225 (Tip: GH will shorten the URL on its own so you don't have to care, just copy&paste raw URLs :) )

Maybe a core maintainer could jump in, but I feel like "blocking" PRs like this is not desirable, we should merge whatever is ready first, and hardmonize later. if this PRs code isolate the dependency enough, it should be  a breeze to update.
And if it's not it could be an argument in favor/defavor of some library. Real code always trumps whatever feelings about library X.

I agree the PR should not be held off until a feature is merged in Datasets. We can adapt to it later on when Datasets has the features.

Ok thanks for the advice @Narsil and @sgugger - in that case I'll just resolve all PR comments here and finish this out this week.

@Narsil is it ok to leave decord for now? I think its fine for this use case, and is just constrained to this pipeline. Later, we'll probably want to add some `video_utils.py` file, just as we do with image utils, where we can keep some more permanent video utilities.

Based on the convo in the datasets repo, I think we'll end up using PyAV.

To try this feature:

```python
from transformers import pipeline

pipe = pipeline('video-classification')
pipe('https://huggingface.co/datasets/nateraw/video-demo/resolve/main/archery.mp4')

# Result
"""
[{'score': 0.6418354511260986, 'label': 'archery'}, {'score': 0.0026529659517109394, 'label': 'riding unicycle'}, {'score': 0.00258301617577672, 'label': 'golf driving'}, {'score': 0.002545431721955538, 'label': 'throwing ball'}, {'score': 0.0023797585163265467, 'label': 'tobogganing'}]
"""
```