Hi community! I have tried to train my first custom object detection model with faster_rcnn_inception_resnet_v2. I have 10 classes, and my dataset consists 50 images for each class. Each image is annotated with LabelImg.
However, I have a few questions here:
The initial total loss is low (starts from 1.1). I eventually stopped the training process at 5000 steps as the total loss has already dropped to below 0.1.
But, a lot of objects are not detected and drawn with bounding boxes as the end result.
And, some detected objects consist of very low confidence score. (Below 50%)
May I ask if there is any ways that I can further improve my model?