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| This directory contains a few example scripts that demonstrate features of detectron2. |
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| * `train_net.py` |
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| An example training script that's made to train builtin models of detectron2. |
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| For usage, see [GETTING_STARTED.md](../GETTING_STARTED.md). |
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| * `plain_train_net.py` |
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| Similar to `train_net.py`, but implements a training loop instead of using `Trainer`. |
| This script includes fewer features but it may be more friendly to hackers. |
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| * `benchmark.py` |
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| Benchmark the training speed, inference speed or data loading speed of a given config. |
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| Usage: |
| ``` |
| python benchmark.py --config-file config.yaml --task train/eval/data [optional DDP flags] |
| ``` |
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| * `analyze_model.py` |
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| Analyze FLOPs, parameters, activations of a detectron2 model. See its `--help` for usage. |
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| * `visualize_json_results.py` |
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| Visualize the json instance detection/segmentation results dumped by `COCOEvalutor` or `LVISEvaluator` |
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| Usage: |
| ``` |
| python visualize_json_results.py --input x.json --output dir/ --dataset coco_2017_val |
| ``` |
| If not using a builtin dataset, you'll need your own script or modify this script. |
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| * `visualize_data.py` |
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| Visualize ground truth raw annotations or training data (after preprocessing/augmentations). |
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| Usage: |
| ``` |
| python visualize_data.py --config-file config.yaml --source annotation/dataloader --output-dir dir/ [--show] |
| ``` |
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| NOTE: the script does not stop by itself when using `--source dataloader` because a training |
| dataloader is usually infinite. |
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