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caffe fully convolutional cnn - how to use the crop parameters

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问题 I am trying to train a fully convolutional network for my problem. I am using the implementation https://github.com/shelhamer/fcn.berkeleyvision.org . I have different image sizes. I am not sure how to set the 'Offset' param in the 'Crop' layer. What are the default values for the 'Offset' param? How to use this param to crop the images around the center? 回答1: According to the Crop layer documentation, it takes two bottom blobs and outputs one top blob. Let's call the bottom blobs as A and B

number of parameters in Caffe LENET or Imagenet models

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问题 How to calculate number of parameters in a model e.g. LENET for mnist, or ConvNet for imagent model etc. Is there any specific function in caffe that returns or saves number of parameters in a model. regards 回答1: Here is a python snippet to compute the number of parameters in a Caffe model: import caffe caffe.set_mode_cpu() import numpy as np from numpy import prod, sum from pprint import pprint def print_net_parameters (deploy_file): print "Net: " + deploy_file net = caffe.Net(deploy_file,

Multiple category classification in Caffe

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I thought we might be able to compile a Caffeinated description of some methods of performing multiple category classification . By multi category classification I mean: The input data containing representations of multiple model output categories and/or simply being classifiable under multiple model output categories. E.g. An image containing a cat & dog would output (ideally) ~1 for both the cat & dog prediction categories and ~0 for all others. Based on this paper , this stale and closed PR and this open PR , it seems caffe is perfectly capable of accepting labels. Is this correct? Would