Open chunhui999 opened 5 years ago
It should not come as a surprise to you that the model trained on the FSNS dataset does not work well on other data. This is a common problem in Deep Learning...
How do your images lokk like? Are they quite similar to the original FSNS images? If not, you can not expect the pre-trained model to work well! The prcess you describe seems to be correct.
It looks like this,these two pictures are just for a small test, I have not prepared a real dataset yet. the blue bounding box is the ditection result, you can ignore them.
@Bartzi I understand what you mean,if I wonder it works well, I must fine-tuning and retrain the pre-trained model using my own dataset, right?
Hi,
the first picture should not work, but the second should actually... did you have a look at the some feature visualization? YOu can do this with Visual Backprop. IN order to enable this, youll have to add the lines before the call to render_rois
from this file to this file and then it should work (hopefully) and you can see a feature visualization of what regions of the image excite the localization network the most. Maybe that helps to debug why the secodn image does not work.
@Bartzi Hi, I ran the fsns_demo.py using my pictures,but it doesn't work well.The result identified the wrong word and the incorrect bboxs. The process I made my pictures as follows: 1) I choose some goods have english words,and then take photos from 4 views(focus on the words); 2) resize the 4 pictures to 150150,then combine them horizontally,create a new picture img(600150); 3) the new picture img will be the input for running fsns_demo.py I wanna to know whether my idea of processing pictures is wrong?Please give me some advice.