Anti spoofing with the Datasouls dataset
Installation
pip install -U datasouls_antispoof
Example inference
Colab notebook with the example:
Dataset
ID & RD anti spoofing challenge
Four types of images:
- real
- replay
- printed
- mask2d
Training
Define the config.
Example at datasoluls_antispoof/configs
Define the environmental variable IMAGE_PATH that points to the folder with the dataset.
Example:
export IMAGE_PATH=<path to the folder with images>
Inference
python -m torch.distributed.launch --nproc_per_node=<num_gpu> datasouls_antispoof/inference.py \
-i <path to images> \
-c <path to config> \
-w <path to weights> \
-o <output-path> \
--fp16
Pre-trained models
| Models | Validation accuracy | Config file | Weights |
|---|---|---|---|
| swsl_resnext50_32x4d | 0.9673 | Link | Link |
| tf_efficientnet_b3_ns | 0.9927 | Link | Link |
1 maintainer
Metadata
1 maintainer
Release files for datasouls-antispoof 0.0.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
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|---|---|---|---|---|
| datasouls_antispoof-0.0.4-py2.py3-none-any.whl | Python 3, Python 2 | none | any | Details |
Total release size: 18.6 kB
Release files / datasouls_antispoof-0.0.4.tar.gz
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