Hi everyone,
I’ve just released on github my take on using object detection to speed up the review of batches of trail camera images. Predator Classifier app I have another project in mind (currently in development) and along the way wanted to speed up the creation of an accurate detection model for classifying predators seen in trail camera images. So I have developed a tool that does an initial scan and files images (as copies) into folders relating to any animal detected. The user can then review these images and make final corrections to end up with a ‘correct’ filing of images and a csv summary (original filename, datetime of image capture if found, initial detection, corrected detection). This then gives some good data showing any weaknesses in the detection model for re-training new versions.
Please feel free to download (Releases v1.0.0 - Initial public release) and have a play. The layout is still a bit rough. I’ll probably have to make this more responsive to smaller screen sizes.
When running this on my pc with 3ghz processor and 32gb ram, it is scanning approx 1000 images in about 8-10 minutes. After this initial detection, it takes me about 15-20 minutes to then manually scan through the images again and make any corrections.
Would be happy for some feedback. And also if anyone is happy to share trail camera images of rare classes (kiwi, ferret) I’d be delighted to include these in future detection models for sharing.
The initial detection model is created on top of approximately 7000 images from about 60 trail cameras so a reasonable diversity of lighting, distance to bait station etc. Your own trail camera images may not be detected quite as well (depending on environment) but I will be releasing in the near future some instructions on how you could build up your own detection model specific to your trapping project and still be able to plug that in to the tool I am sharing now.
Cheers,
Hamish