Australian Wildlife Conservancy's Wildlife detection and species classification inference tools
Project description
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 / Windows with 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
)
for result in results:
print(result)
# print example:
# AWCResult(identifier='"path/to/image1.jpg"', bbox=(0.1, 0.2, 0.3, 0.4), bbox_label='animal', bbox_conf=0.95, labels_probs=(('kangaroo', 0.87),))
Documenntation
Refer to this for more details
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.
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