46 lines
1.3 KiB
Markdown
46 lines
1.3 KiB
Markdown
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This directory contains a few scripts that use 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`.
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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:
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```
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python benchmark.py --config-file config.yaml --task train/eval/data [optional DDP flags]
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```
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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:
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```
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python visualize_json_results.py --input x.json --output dir/ --dataset coco_2017_val
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```
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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:
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```
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python visualize_data.py --config-file config.yaml --source annotation/dataloader --output-dir dir/ [--show]
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```
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NOTE: the script does not stop by itself when using `--source dataloader` because a training
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dataloader is usually infinite.
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