I have trained a model in detectron2. But, it does lot of false prediction if i use it on supermarket as the model was trained on the images taken inside home and arranging products. So, is there any way where i can visualize output of layers of the model, i mean the anchor boxes being generated by the model? Also model predicts properly when i test it on products which are placed on the selves inside my home (similar images) but predict poorly when i take it to any super market. So, is there any proper way to reduce the false predictions.
You could capture more training data from the “supermarket” setup and finetune the model on this data domain, which would most likely reduce the prediction error.
Ok, but is there any way to reduce false prediction on Similar objects, i mean like Pepsi diet can and Coke diet can, they both are in silver colour. We cannot label everything so is there anyway se can do this ? I am reading lot of articles but couldn’t find much of it.