Our lab managed to train DLC 2.26b on a 50 labeled frame dataset (1024 x 1280 images). The frames contain 4 animals of slightly different sizes and each animal was uniquely labeled in each frame with unique identifiers as they had markers on their back. We only trained this NN for 2500 iterations, perhaps more would do better.
The Analyze Video step took about 13 minutes (on a Titan XP 12GB) to process a 15second recording (25FPS). That seemed very slow, and we're wondering if there are any suggestions for speeding this step up. The results for a 15sec video are below. The results shows promise, and we're excited about the possibility of improving this. There are many dropouts (frames without labels) as well as animal ID switching even between 2 sequential frames. If there are any obvious errors we made, we would appreciate any input.
Thanks so much!