🐾 Pytorch-Wildlife and MegaDetector

[!TIP] MegaDetector now resides in Pytorch-Wildlife as part of the model zoo.

At the core of our mission is the desire to create a harmonious space where conservation scientists from all over the globe can unite. Where they're able to share, grow, use datasets and deep learning architectures for wildlife conservation. We've been inspired by the potential and capabilities of Megadetector, and we deeply value its contributions to the community. As we forge ahead with Pytorch-Wildlife, under which Megadetector now resides, please know that we remain committed to supporting, maintaining, and developing Megadetector, ensuring its continued relevance, expansion, and utility.

MegaDetectorV6: SMALLER, FASTER, BETTER!

We have officially released our 6th version of MegaDetector, MegaDetectorV6! In the next generation of MegaDetector, we are focusing on computational efficiency, performance, modernizing of model architectures, and licensing. We have trained multiple new models using different model architectures that are optimized for performance and low-budget devices, including Yolo-v9, Yolo-v10, and RT-Detr for maximum user flexibility. For example, the MegaDetectorV6-Ultralytics-YoloV10-Compact (MDV6-yolov10-c) model only have 2% of the parameters of the previous MegaDetectorV5 and still exhibits comparable performance on our validation datasets.

To test the newest version of MegaDetector with all the existing functionalities, you can use our Hugging Face interface or simply load the model with Pytorch-Wildlife. The weights will be automatically downloaded:

from PytorchWildlife.models import detection as pw_detection
detection_model = pw_detection.MegaDetectorV6()

We will also continuously fine-tune our V6 models on newly collected public and private data to further improve the generalization performance.

[!TIP] All versions of MegaDetector and corresponding performance can be found in the model zoo.

From now on, we encourage our users to use MegaDetectorV6 as their default animal detection model and choose whichever model that fits the project needs. To reduce potential confusion, we have also standardized the model names into MDV6-Compact and MDV6-Extra for two model sizes using the same architecture. Learn how to use MegaDetectorV6 in our image demo and our demo data installtion guideline.

MegaDetectorV5 and Archive Repos

For those interested in accessing the previous MegaDetector repository, which utilizes the same MegaDetectorV5 model weights and was primarily developed by Dan Morris during his time at Microsoft, please visit the archive branch , or you can visit this forked repository that Dan Morris is currently actively maintaining.

[!TIP] If you have any questions regarding MegaDetector and Pytorch-Wildlife, please email us or join us in our discord channel: