awc-helpers 0.1.5

Australian Wildlife Conservancy's Wildlife detection and species classification inference tools

AWC Helpers

Wildlife detection and species classification inference tools combining MegaDetector with custom species classifiers.

Installation

1. Install PyTorch

Windows (with CUDA GPU):

pip install "torch<=2.9.1" "torchvision<=0.24.1" --index-url https://download.pytorch.org/whl/cu128

Linux / Mac / CPU:

pip install "torch<=2.9.1" "torchvision<=0.24.1"

2. Install AWC Helpers

From PyPI:

pip install awc-helpers

Usage

from awc_helpers import DetectAndClassify

# Initialize the pipeline
pipeline = DetectAndClassify(
    detector_path="models/md_v1000.0.0-redwood.pt",
    classifier_path="models/awc-135-v1.pth",
    label_names=["species_a", "species_b", "species_c"],
    detection_threshold=0.1,
    clas_threshold=0.5,
)

# Run inference on image paths
results = pipeline.predict(
    inp=["path/to/image1.jpg", "path/to/image2.jpg"],
    clas_bs=4
)

# Results format: [(image_path, bbox_confidence, bbox, label, label_confidence), ...]
for result in results:
    print(result)
# print example:
# ("path/to/image1.jpg",
#  0.804,
#  (0.2246, 0.5885, 0.0678, 0.1022),
#  'Acanthagenys rufogularis | Spiny-cheeked Honeyeater',
#  0.9948)

License

This project is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0).

Non-commercial use only. Derivative works must use the same license.