A reimplementation of relation module for faster rcnn in Tensorflow (refer to paper Relation Network for Object Detection). This repository is based on the multi-image version of Faster RCNN available here. The codes for relation module are based on the original mxnet implementation.
./experiments/scripts/test_faster_rcnn.sh $GPU_ID pascal_voc_0712 res101 RM.ENABLE_INSTANCE True TRAIN.WARMUP True
As above shell shown, we set RM.ENABLE_INSTANCE
as True
to enable relation module
. The learning rate is set according to the original mxnet implementation. More configuration for relation module
can be viewed in lib/model/config.py
Note:
- Only the
relation module
(between fc layers for feature enhance) is implemented for present. The one forduplicate process
(to learn NMS) in not support yet. relation module
is impletemented inlib/nets/network.py
.- The position embedding code are implemented in python, and reside in
lib/layer_utils/rel_module_util.py
.
Update(0717):
- Add
warm up
support, refer tolib/model/config.py
for more details. - Add
ZFnet
for quick iteration, the model is converted fromcaffe
model, and the pool layers are changed fromkernel 3, stride 2
tokernel 2, stride 2