Prune‘s and Bharat‘s answers gives the overall purpose of a “Python” layer: a general purpose layer which is implemented in python rather than c++. I intend this answer to serve as a tutorial for using “Python” layer. A Tutorial for “Python” layer what is a “Python” layer? Please see the excellent answers of Prune and … Read more
I came across this phenomenon several times. Here are my observations: Gradient blow up Reason: large gradients throw the learning process off-track. What you should expect: Looking at the runtime log, you should look at the loss values per-iteration. You’ll notice that the loss starts to grow significantly from iteration to iteration, eventually the loss … Read more
When using the image dataset input layer (with either lmdb or leveldb backend) caffe only supports one integer label per input image. If you want to do regression, and use floating point labels, you should try and use the HDF5 data layer. See for example this question. In python you can use h5py package to … Read more
A quick guide to Caffe’s convert_imageset Build First thing you must do is build caffe and caffe’s tools (convert_imageset is one of these tools). After installing caffe and makeing it make sure you ran make tools as well. Verify that a binary file convert_imageset is created in $CAFFE_ROOT/build/tools. Prepare your data Images: put all images … Read more