Because the structure of the RFCN and light-head rcnn is pretty similar, I just tried to implement the light-head rcnn by modifying the py-R-FCN on caffe.
I only changed the prototxt file for training and testing, the training procedure goes well, but when I do test, I find the mAP is very low.
The attachments are the train and test file I used, I am really eager to know in which step I make mistakes. Could anyone help me to find out it?
Because the structure of the RFCN and light-head rcnn is pretty similar, I just tried to implement the light-head rcnn by modifying the py-R-FCN on caffe.
I only changed the prototxt file for training and testing, the training procedure goes well, but when I do test, I find the mAP is very low.
The attachments are the train and test file I used, I am really eager to know in which step I make mistakes. Could anyone help me to find out it?
resnet50_lhrcnn_test.txt resnet50_lhrcnn_train.txt