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dp-dpm's Issues

About layers in the DPM-CNN

Hi Ross,
as described in the CVPR paper Deformable Part Models are Convolutional Neural Networks,
there are distance transform pooling layer and object geometry layer in the DPM-CNN.

Are these two layers included in the code?
Thank you.

CPU mode yields AP of 0

(Reported to me by Alan Li.)

Details on the issue are sparse. I'm not sure if the problem occurs in training, testing, or both. This issue is primarily meant to document the problem; I likely will not devote time to fixing.

about the network

At first I meet the same problem: AP=0.00001. So I change the 'cnn_binary_file' from 'CaffeNet.v2.caffemodel' to 'ilsvrc_2012_train_iter_310k', and then I get the right output(AP=53.7). But I can't get the information of parts, so I use the function'pascal_train_parts.m' to train. In this way , the result is wrong. who can tell me, how to get the right result with the use of parts information?

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