The same dataset trained on faster rcnn works really well, and detects dogs properly. I've run 50k iterations, and total loss was spiking from 1.5 to 3 all the time in the end, with random bigger spikes, but overall it went down from 20
There wasn't a smooth and gradual decline, but a really spiky and uneven one with both models
I know it's a fast model with low precision, but it should at least more or less detect the object. How can I increase accuracy so it at least partially detects objects without showing completely false bounding boxes ?