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update docs
Reviewed By: alexander-kirillov Differential Revision: D26627161 fbshipit-source-id: c7be8408351d3fbc5f8e2eaba951f4f5a45a1979
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.github/workflows/check-template.yml

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@@ -31,7 +31,7 @@ jobs:
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}
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const body = issue.data.body.toLowerCase();
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const hasInstructions = body.indexOf("reproduce") != -1;
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const hasEnvironment = (body.indexOf("environment") != -1) || (body.indexOf("colab") != -1);
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const hasEnvironment = (body.indexOf("environment") != -1) || (body.indexOf("colab") != -1) || (body.indexOf("docker") != -1);
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if (hasInstructions && hasEnvironment) {
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core.debug("Issue " + issue.data.title + " follows template.");
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return;

INSTALL.md

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### Build Detectron2 from Source
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gcc & g++ ≥ 5 are required. [ninja](https://ninja-build.org/) is recommended for faster build.
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gcc & g++ ≥ 5.4 are required. [ninja](https://ninja-build.org/) is recommended for faster build.
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After having them, run:
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```
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python -m pip install 'git+https://github.com/facebookresearch/detectron2.git'
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Note that:
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1. The pre-built package has to be used with corresponding version of CUDA and the official package of PyTorch.
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Otherwise, please build detectron2 from source.
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Otherwise, please build detectron2 from source.
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2. New packages are released every few months. Therefore, packages may not contain latest features in the master
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branch and may not be compatible with the master branch of a research project that uses detectron2
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(e.g. those in [projects](projects)).

detectron2/data/datasets/coco_panoptic.py

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e.g. "coco_2017_train_panoptic"
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metadata (dict): extra metadata associated with this dataset.
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image_root (str): directory which contains all the images
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panoptic_root (str): directory which contains panoptic annotation images
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panoptic_json (str): path to the json panoptic annotation file
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panoptic_root (str): directory which contains panoptic annotation images in COCO format
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panoptic_json (str): path to the json panoptic annotation file in COCO format
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sem_seg_root (none): not used, to be consistent with
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`register_coco_panoptic_separated`.
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instances_json (str): path to the json instance annotation file

detectron2/utils/collect_env.py

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cxx = cxx.decode("utf-8").strip().split("\n")[0]
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except subprocess.SubprocessError:
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cxx = "Not found"
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data.append(("Compiler", cxx))
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data.append(("Compiler ($CXX)", cxx))
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if has_cuda and CUDA_HOME is not None:
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try:

docker/README.md

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cd docker/
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# Build:
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docker build --build-arg USER_ID=$UID -t detectron2:v0 .
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# Launch:
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# Launch (require GPUs):
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docker run --gpus all -it \
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--shm-size=8gb --env="DISPLAY" --volume="/tmp/.X11-unix:/tmp/.X11-unix:rw" \
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--name=detectron2 detectron2:v0

docs/tutorials/datasets.md

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to contiguous ids in [0, num_categories). It is useful for evaluation only.
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* `json_file`: The COCO annotation json file. Used by COCO evaluation for COCO-format datasets.
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* `panoptic_root`, `panoptic_json`: Used by panoptic evaluation.
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* `panoptic_root`, `panoptic_json`: Used by COCO-format panoptic evaluation.
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* `evaluator_type`: Used by the builtin main training script to select
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evaluator. Don't use it in a new training script.
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You can just provide the [DatasetEvaluator](../modules/evaluation.html#detectron2.evaluation.DatasetEvaluator)

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