pix2pix
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phillipi
Image-to-image translation with conditional adversarial nets
@phillipi, I want to collect remote sensing data from googleMaps, Could you provide any solution to scrape data from googleMaps. Any suggestion would be appreciated.
https://github.com/phillipi/pix2pix/blob/master/scripts/edges/PostprocessHED.m is there python version of this matlab code?
Hello, I am trying to implement your work following the steps you provide in this git but I am having several version conflicts. Would you kindly provide the version of...
@phillipi when Training the model on CityScapes(photo->label), I have a question the how to prepare the pair of data(input,target): {RGB photo，the ont-hot label map},size is {(3,2048,1024),(30,2048,1024)} or {RGB photo，the ont-hot...
How to use the PatchGAN discriminator to judge the true and false of a specific irregular area in the generated image？
Excuse me, I would like to ask how the matching of color distribution is realized in the original paper chart 7. What should I do for this experiment? I have...
running step 4 python batch_hed.py --images_dir=/data/photos/ --hed_mat_dir=/data/photos1 but always get "Import Error: no module named caffe" what do you suggest?
Can anybody give me some advise for how to create labels from images. For example like the cityscapes dataset, Thanks in advance, amazing project!
checkpoints_dir ./checkpoints /home/csdept/torch/install/bin/luajit: /home/csdept/torch/install/share/lua/5.1/torch/File.lua:272: read error: read 5499 blocks instead of 1484150018 at /home/csdept/torch/pkg/torch/lib/TH/THDiskFile.c:344 stack traceback: [C]: in function 'readChar' /home/csdept/torch/install/share/lua/5.1/torch/File.lua:272: in function 'readObject' /home/csdept/torch/install/share/lua/5.1/torch/File.lua:368: in function 'readObject' /home/csdept/torch/install/share/lua/5.1/torch/File.lua:353: in...
I want see the values while training, tf.log(predict_real + EPS) and tf.log(1 - predict_fake + EPS). so, i'm add the code(#add code) in the main. if should(a.progress_freq): fetches["discrim_loss"] = model.discrim_loss...
