Naga Sandeep Ramachandruni

You need to add the cuda path to bashrc. export CUDA_HOME=/usr/local/cuda-8.0 export LD_LIBRARY_PATH=${CUDA_HOME}/lib64 PATH=${CUDA_HOME}/bin:${PATH} export PATH

You can look at this thread. https://github.com/rbgirshick/py-faster-rcnn/issues/123

For working with gpu you need to install nvidia driver and cuda properly. and then do make. Please let me know which gpu you are using and linux environment so...

You can reduce the memory usage of the model by reducing the size of some parameters. I will mention you some parameters try changing one at a time or combinations....

Obviously, it will be when loading of weights. Try with res50. The gpu you were using doesn't have enough memory to train these networks. What is the memory of your...

check on the number of anchors you have used during train and test. Both should match.

Yes by default pascal-voc has 21 classes. so 21x4. you could have changed it to 6 so 6x4.

You can download from here. https://github.com/tensorflow/models/tree/master/research/slim

please check the variable self.classes if it contains any mistake.

You need to also change lib/layer_utils/snippets.py which has functions generate_anchors_pre_tf and generate_anchors_pre which calls the function generate_anchors without the feat_stride argument. Please change that and add feat_stride[0] as the first...