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29 changes: 29 additions & 0 deletions .circleci/config.yml
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version: 2.1

jobs:
python_lint:
docker:
- image: circleci/python:3.7
steps:
- checkout
- run:
command: |
pip install --user --progress-bar off flake8 typing
flake8 .
test:
docker:
- image: circleci/python:3.7
steps:
- checkout
- run:
command: |
pip install --user --progress-bar off scipy pytest
pip install --user --progress-bar off --pre torch torchvision -f https://download.pytorch.org/whl/nightly/cpu/torch_nightly.html
pytest .
workflows:
build:
jobs:
- python_lint
- test
5 changes: 5 additions & 0 deletions .github/CODE_OF_CONDUCT.md
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# Code of Conduct

Facebook has adopted a Code of Conduct that we expect project participants to adhere to.
Please read the [full text](https://code.fb.com/codeofconduct/)
so that you can understand what actions will and will not be tolerated.
39 changes: 39 additions & 0 deletions .github/CONTRIBUTING.md
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# Contributing to DETR
We want to make contributing to this project as easy and transparent as
possible.

## Our Development Process
Minor changes and improvements will be released on an ongoing basis. Larger changes (e.g., changesets implementing a new paper) will be released on a more periodic basis.

## Pull Requests
We actively welcome your pull requests.

1. Fork the repo and create your branch from `master`.
2. If you've added code that should be tested, add tests.
3. If you've changed APIs, update the documentation.
4. Ensure the test suite passes.
5. Make sure your code lints.
6. If you haven't already, complete the Contributor License Agreement ("CLA").

## Contributor License Agreement ("CLA")
In order to accept your pull request, we need you to submit a CLA. You only need
to do this once to work on any of Facebook's open source projects.

Complete your CLA here: <https://code.facebook.com/cla>

## Issues
We use GitHub issues to track public bugs. Please ensure your description is
clear and has sufficient instructions to be able to reproduce the issue.

Facebook has a [bounty program](https://www.facebook.com/whitehat/) for the safe
disclosure of security bugs. In those cases, please go through the process
outlined on that page and do not file a public issue.

## Coding Style
* 4 spaces for indentation rather than tabs
* 80 character line length
* PEP8 formatting following [Black](https://black.readthedocs.io/en/stable/)

## License
By contributing to DETR, you agree that your contributions will be licensed
under the LICENSE file in the root directory of this source tree.
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32 changes: 32 additions & 0 deletions .github/ISSUE_TEMPLATE/bugs.md
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---
name: "🐛 Bugs"
about: Report bugs in DETR
title: Please read & provide the following

---

## Instructions To Reproduce the 🐛 Bug:

1. what changes you made (`git diff`) or what code you wrote
```
<put diff or code here>
```
2. what exact command you run:
3. what you observed (including __full logs__):
```
<put logs here>
```
4. please simplify the steps as much as possible so they do not require additional resources to
run, such as a private dataset.

## Expected behavior:

If there are no obvious error in "what you observed" provided above,
please tell us the expected behavior.

## Environment:

Provide your environment information using the following command:
```
python -m torch.utils.collect_env
```
22 changes: 22 additions & 0 deletions .github/ISSUE_TEMPLATE/questions-help-support.md
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---
name: "How to do something❓"
about: How to do something using DETR?

---

## ❓ How to do something using DETR

Describe what you want to do, including:
1. what inputs you will provide, if any:
2. what outputs you are expecting:


NOTE:

1. Only general answers are provided.
If you want to ask about "why X did not work", please use the
[Unexpected behaviors](https://github.com/facebookresearch/detr/issues/new/choose) issue template.

2. About how to implement new models / new dataloader / new training logic, etc., check documentation first.

3. We do not answer general machine learning / computer vision questions that are not specific to DETR, such as how a model works, how to improve your training/make it converge, or what algorithm/methods can be used to achieve X.
41 changes: 41 additions & 0 deletions .github/ISSUE_TEMPLATE/unexpected-problems-bugs.md
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---
name: "Unexpected behaviors"
about: Run into unexpected behaviors when using DETR
title: Please read & provide the following

---

If you do not know the root cause of the problem, and wish someone to help you, please
post according to this template:

## Instructions To Reproduce the Issue:

1. what changes you made (`git diff`) or what code you wrote
```
<put diff or code here>
```
2. what exact command you run:
3. what you observed (including __full logs__):
```
<put logs here>
```
4. please simplify the steps as much as possible so they do not require additional resources to
run, such as a private dataset.

## Expected behavior:

If there are no obvious error in "what you observed" provided above,
please tell us the expected behavior.

If you expect the model to converge / work better, note that we do not give suggestions
on how to train a new model.
Only in one of the two conditions we will help with it:
(1) You're unable to reproduce the results in DETR model zoo.
(2) It indicates a DETR bug.

## Environment:

Provide your environment information using the following command:
```
python -m torch.utils.collect_env
```
23 changes: 23 additions & 0 deletions .gitignore
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.nfs*
*.ipynb
*.pyc
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.DS_Store
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**/__pycache__/**
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datasets/data/
experiment-*
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**/.mypy_cache/*
.mypy_cache/*
not_tracked_dir/
.vscode
.python-version
*.sbatch
*.egg-info
build
dist
.idea
25 changes: 25 additions & 0 deletions .run/STTran_train.run.xml
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25 changes: 25 additions & 0 deletions .run/STTran_train_frcnn.run.xml
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25 changes: 25 additions & 0 deletions .run/STTran_train_frcnn_IOU.run.xml
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25 changes: 25 additions & 0 deletions .run/demo_CP.run.xml
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25 changes: 25 additions & 0 deletions .run/demo_trackformer.run.xml
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24 changes: 24 additions & 0 deletions .run/generate_coco_from_VidHOI.run.xml
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24 changes: 24 additions & 0 deletions .run/generate_coco_from_actiongenome.run.xml
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