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# Initially taken from Github's Python gitignore file | ||
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# Byte-compiled / optimized / DLL files | ||
__pycache__/ | ||
*.py[cod] | ||
*$py.class | ||
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# C extensions | ||
*.so | ||
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# Distribution / packaging | ||
.Python | ||
build/ | ||
develop-eggs/ | ||
dist/ | ||
downloads/ | ||
eggs/ | ||
.eggs/ | ||
lib/ | ||
lib64/ | ||
parts/ | ||
sdist/ | ||
var/ | ||
wheels/ | ||
*.egg-info/ | ||
.installed.cfg | ||
*.egg | ||
MANIFEST | ||
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# PyInstaller | ||
# Usually these files are written by a python script from a template | ||
# before PyInstaller builds the exe, so as to inject date/other infos into it. | ||
*.manifest | ||
*.spec | ||
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# Installer logs | ||
pip-log.txt | ||
pip-delete-this-directory.txt | ||
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# Unit test / coverage reports | ||
htmlcov/ | ||
.tox/ | ||
.nox/ | ||
.coverage | ||
.coverage.* | ||
.cache | ||
nosetests.xml | ||
coverage.xml | ||
*.cover | ||
.hypothesis/ | ||
.pytest_cache/ | ||
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# Translations | ||
*.mo | ||
*.pot | ||
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# Django stuff: | ||
*.log | ||
local_settings.py | ||
db.sqlite3 | ||
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# Flask stuff: | ||
instance/ | ||
.webassets-cache | ||
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# Scrapy stuff: | ||
.scrapy | ||
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# Sphinx documentation | ||
docs/_build/ | ||
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# PyBuilder | ||
target/ | ||
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# Jupyter Notebook | ||
.ipynb_checkpoints | ||
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# IPython | ||
profile_default/ | ||
ipython_config.py | ||
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# pyenv | ||
.python-version | ||
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# celery beat schedule file | ||
celerybeat-schedule | ||
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# SageMath parsed files | ||
*.sage.py | ||
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# Environments | ||
.env | ||
.venv | ||
env/ | ||
venv/ | ||
ENV/ | ||
env.bak/ | ||
venv.bak/ | ||
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# Spyder project settings | ||
.spyderproject | ||
.spyproject | ||
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# Rope project settings | ||
.ropeproject | ||
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# mkdocs documentation | ||
/site | ||
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# mypy | ||
.mypy_cache/ | ||
.dmypy.json | ||
dmypy.json | ||
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# Pyre type checker | ||
.pyre/ | ||
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# vscode | ||
.vscode | ||
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# TF code | ||
tensorflow_code | ||
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# Models | ||
models | ||
proc_data | ||
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# examples | ||
runs | ||
examples/runs | ||
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# pyCharm | ||
.idea/ | ||
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# local folders | ||
data | ||
models | ||
output |
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[submodule "transformers"] | ||
path = transformers | ||
url = [email protected]:huggingface/transformers.git | ||
[submodule "coco_caption"] | ||
path = coco_caption | ||
url = [email protected]:LuoweiZhou/coco-caption.git |
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# Microsoft Open Source Code of Conduct | ||
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This project has adopted the [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/). | ||
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Resources: | ||
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- [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/) | ||
- [Microsoft Code of Conduct FAQ](https://opensource.microsoft.com/codeofconduct/faq/) | ||
- Contact [[email protected]](mailto:[email protected]) with questions or concerns |
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# Download | ||
## Datasets | ||
We provide the extracted image region features, object tags, and the original text annotations for each downstream tasks. | ||
```bash | ||
wget https://biglmdiag.blob.core.windows.net/oscar/datasets/$TASK_NAME.zip | ||
unzip $TASK_NAME.zip -d $DATA_DIR | ||
``` | ||
`TASK_NAME` could be `coco_caption`, `coco_ir`, `vqa`, `GQA`, `nlvr2`. | ||
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## Pre-trained Models | ||
We provide pre-trained *Oscar* models of Bert-base and Bert-large structures, with the name starting with `base` and `large`, respectively. | ||
```bash | ||
wget https://biglmdiag.blob.core.windows.net/oscar/pretrained_models/$MODEL_NAME.zip | ||
unzip $MODEL_NAME.zip -d $MODEL_DIR | ||
``` | ||
`MODEL_NAME` could be `base-vg-labels`, `large-vg-labels`, `base-oid-labels`, `base-no-labels`. | ||
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The models are trained with both image region features and object tags. The image region features are extracted by the Faster R-CNN with | ||
ResNet-101, using object and attribute annotations from [Visual Genome](http://visualgenome.org/). | ||
The object tags are from: | ||
1) the same VisualGenome model, named as `-vg-labels`. Or, | ||
2) the model trained on object annotations from [Open Images V5](https://storage.googleapis.com/openimages/web/index.html). named as `-oid-labels`. Or, | ||
3) no object tags provied, serving as baseline, named as `-no-labels`. |
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## Installation | ||
### Requirements | ||
- Python 3.7 | ||
- Pytorch 1.2 | ||
- torchvision 0.4.0 | ||
- cuda 10.0 | ||
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### Setup with Conda | ||
```bash | ||
# create a new environment | ||
conda create --name oscar python=3.7 | ||
conda activate oscar | ||
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# install pytorch1.2 | ||
conda install pytorch==1.2.0 torchvision==0.4.0 cudatoolkit=10.0 -c pytorch | ||
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export INSTALL_DIR=$PWD | ||
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# install apex | ||
cd $INSTALL_DIR | ||
git clone https://github.com/NVIDIA/apex.git | ||
cd apex | ||
python setup.py install --cuda_ext --cpp_ext | ||
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# install oscar | ||
cd $INSTALL_DIR | ||
git clone --recursive [email protected]:xjli/Oscar.git | ||
cd Oscar/coco_caption | ||
./get_stanford_models.sh | ||
cd .. | ||
python setup.py build develop | ||
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# install requirements | ||
pip install -r requirements.txt | ||
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unset INSTALL_DIR | ||
``` | ||
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MIT License | ||
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Copyright (c) Microsoft Corporation. | ||
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Permission is hereby granted, free of charge, to any person obtaining a copy | ||
of this software and associated documentation files (the "Software"), to deal | ||
in the Software without restriction, including without limitation the rights | ||
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell | ||
copies of the Software, and to permit persons to whom the Software is | ||
furnished to do so, subject to the following conditions: | ||
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The above copyright notice and this permission notice shall be included in all | ||
copies or substantial portions of the Software. | ||
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR | ||
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, | ||
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE | ||
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER | ||
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, | ||
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE | ||
SOFTWARE |
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