Open xiaozhuang1010 opened 7 years ago
I'm not sure I understand. Are you saying you fed each image into the model individually, then recorded the class prediction, then divided the number of correct predictions by the number of images you fed in and got 0.0098?
I means enter a single image to the trained model(oxford102_VGG_S_iter_20000.caffemodel) and obtained equal probability of classification.just like: sweet pea:0.0098 english marigold:0.0098 pink primross:0.0098....and so on.
hi, I got exactly the same problem, have you figured it out?
I solved it. Just need to edit the deploy file properly
I use the same way as you and obtained a good performance,but when I use a single picture to test the model it only obtained 0.0098 accuracy.....please tell me why?