from dataObj.image import imageNetObj from tf.VGGGap import VGGGap import numpy as np import pdb #Paths to list of filenames trainImageList = "/home/slundquist/mountData/datasets/imagenet/train_cls.txt" testImageList = "/home/slundquist/mountData/datasets/imagenet/val_cls.txt" trainImagePrefix = "/shared/imageNet/CLS_LOC/ILSVRC2015/Data/CLS-LOC/train/" testImagePrefix = "/shared/imageNet/CLS_LOC/ILSVRC2015/Data/CLS-LOC/val/" clsMeta = "/shared/imageNet/devkit/data/meta_clsloc.mat" #Get object from which tensorflow will pull data from trainDataObj = imageNetObj(trainImageList, trainImagePrefix, clsMeta, useClassDir = True, resizeMethod="crop", normStd=False) testDataObj = imageNetObj(testImageList, testImagePrefix, clsMeta, useClassDir = False, resizeMethod="crop", normStd=False) params = { #Base output directory 'outDir': "/home/slundquist/mountData/DeepGAP/", #Inner run directory 'runDir': "/imagenet_vgg/", 'tfDir': "/tfout", #Save parameters 'ckptDir': "/checkpoints/", 'saveFile': "/save-model", 'savePeriod': 10, #In terms of displayPeriod #output plots directory 'plotDir': "plots/", 'plotPeriod': 10, #With respect to displayPeriod
import matplotlib matplotlib.use('Agg') from dataObj.image import imageNetObj from tf.ista_time import ISTA_Time #from plot.roc import makeRocCurve import pdb trainImageLists = "/shared/imageNet/vid2015_128x64/imageNetVID_2015_list.txt" randImageSeed = None #Get object from which tensorflow will pull data from trainDataObj = imageNetObj(trainImageLists, resizeMethod="crop", shuffle=True, seed=randImageSeed) #ISTA params params = { #Base output directory 'outDir': "/home/slundquist/mountData/tfLCA/", #Inner run directory 'runDir': "/imagenetTime_demo/", 'tfDir': "/tfout", #Save parameters 'ckptDir': "/checkpoints/", 'saveFile': "/save-model", 'savePeriod': 100, #In terms of displayPeriod #output plots directory 'plotDir': "plots/", 'plotPeriod': 100, #With respect to displayPeriod #Progress step 'progress': 10, #Controls how often to write out to tensorboard 'writeStep': 10, #300, #Threshold
import matplotlib matplotlib.use('Agg') from dataObj.image import imageNetObj from tf.ista_time import ISTA_Time #from plot.roc import makeRocCurve import pdb trainImageLists = "/shared/imageNet/vid2015_128x64/imageNetVID_2015_list.txt" randImageSeed = None #Get object from which tensorflow will pull data from trainDataObj = imageNetObj(trainImageLists, resizeMethod="crop", shuffle=True, seed=randImageSeed) #ISTA params params = { #Base output directory 'outDir': "/home/slundquist/mountData/tfLCA/", #Inner run directory 'runDir': "/imagenetTime/", 'tfDir': "/tfout", #Save parameters 'ckptDir': "/checkpoints/", 'saveFile': "/save-model", 'savePeriod': 100, #In terms of displayPeriod #output plots directory 'plotDir': "plots/", 'plotPeriod': 100, #With respect to displayPeriod #Progress step 'progress': 10, #Controls how often to write out to tensorboard 'writeStep': 100, #300, #Threshold
import matplotlib matplotlib.use('Agg') from dataObj.image import imageNetObj from tf.ista import ISTA #from plot.roc import makeRocCurve import pdb #Input vgg file for preloaded weights trainImageLists = "/shared/imageNet/vid2015_128x64/imageNetVID_2015_list.txt" #Get object from which tensorflow will pull data from trainDataObj = imageNetObj(trainImageLists, resizeMethod="pad") #ISTA params params = { #Base output directory 'outDir': "/home/slundquist/mountData/tfLCA/", #Inner run directory 'runDir': "/imagenet/", 'tfDir': "/tfout", 'ckptDir': '/checkpoints/', 'saveFile': '/save-model', #Flag for loading weights from checkpoint 'load': True, 'loadFile': "/home/slundquist/mountData/tfLCA/saved/imagenet.ckpt", 'numIterations': 1000000, 'displayPeriod': 300, 'savePeriod': 10, #In terms of displayPeriod #output plots directory 'plotDir': "plots/", 'plotPeriod': 20, #With respect to displayPeriod #Progress step (also controls how often to save and write out to tensorboard)
import numpy as np import pdb #Paths to list of filenames trainImageList = "/home/slundquist/mountData/datasets/imagenet/train_cls.txt" testImageList = "/home/slundquist/mountData/datasets/imagenet/val_cls.txt" trainImagePrefix = "/nh/compneuro/Data/imageNet/CLS_LOC/ILSVRC2015/Data/CLS-LOC/train/" testImagePrefix = "/nh/compneuro/Data/imageNet/CLS_LOC/ILSVRC2015/Data/CLS-LOC/val/" clsMeta = "/nh/compneuro/Data/imageNet/devkit/data/meta_clsloc.mat" #Get object from which tensorflow will pull data from trainDataObj = imageNetObj(trainImageList, trainImagePrefix, clsMeta, useClassDir=True, resizeMethod="crop") testDataObj = imageNetObj(testImageList, testImagePrefix, clsMeta, useClassDir=False, resizeMethod="crop") params = { #Base output directory 'outDir': "/home/slundquist/mountData/DeepGAP/", #Inner run directory 'runDir': "/imagenet/", 'tfDir': "/tfout", #Save parameters