import matplotlib
matplotlib.use('Agg')
from dataObj.image import pvpObj
from tf.slp_sparse_code import SLP
import numpy as np
import pdb
#Paths to list of filenames
trainFileList = "/home/slundquist/mountData/tfSparseCode/fista_cifar_nf256_eval/fista_train_cifar_256_eval.pvp"
trainGtList = "/home/slundquist/mountData/datasets/cifar/images/train.txt"
testFileList = "/home/slundquist/mountData/tfSparseCode/fista_cifar_nf256_eval/fista_test_cifar_256_eval.pvp"
testGtList = "/home/slundquist/mountData/datasets/cifar/images/test.txt"
#Get object from which tensorflow will pull data from
trainDataObj = pvpObj(trainFileList, trainGtList, (16, 16, 256), resizeMethod="crop", shuffle=True, skip=1, seed=None, rangeIdx=range(128))
testDataObj = pvpObj(testFileList, testGtList, (16, 16, 256), resizeMethod="crop", shuffle=True, skip=1, seed=None)
params = {
#Base output directory
'outDir': "/home/slundquist/mountData/tfSparseCode/",
#Inner run directory
'runDir': "/cifar_fista_slp_limited/",
'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
import matplotlib
matplotlib.use('Agg')
from dataObj.image import pvpObj
from tf.mlp_sparse_code import MLPSP
import numpy as np
import pdb
#Paths to list of filenames
trainFileList = "/home/slundquist/mountData/tfSparseCode/fista_cifar_nf256_eval/fista_train_cifar_256_eval.pvp"
trainGtList = "/home/slundquist/mountData/datasets/cifar/images/train.txt"
testFileList = "/home/slundquist/mountData/tfSparseCode/fista_cifar_nf256_eval/fista_test_cifar_256_eval.pvp"
testGtList = "/home/slundquist/mountData/datasets/cifar/images/test.txt"
#Get object from which tensorflow will pull data from
trainDataObj = pvpObj(trainFileList, trainGtList, (16, 16, 256), resizeMethod="crop", shuffle=True, skip=1, seed=None)
testDataObj = pvpObj(testFileList, testGtList, (16, 16, 256), resizeMethod="crop", shuffle=True, skip=1, seed=None)
params = {
#Base output directory
'outDir': "/home/slundquist/mountData/tfSparseCode/",
#Inner run directory
'runDir': "/cifar_fista_mlp_nf256/",
'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
trainGtList = "/home/slundquist/mountData/cifar_pv/cifar_trainset/cifar_train.txt"
#testFileList = "/home/slundquist/mountData/cifar_pv/cifar_testset/S4.pvp"
#testFileList = "/home/slundquist/mountData/cifar_pv/cifar_testset/S3.pvp"
#testFileList = "/home/slundquist/mountData/cifar_pv/cifar_testset/S2.pvp"
testFileList = "/home/slundquist/mountData/cifar_pv/cifar_testset/S1.pvp"
testGtList = "/home/slundquist/mountData/cifar_pv/cifar_testset/cifar_test.txt"
#Get object from which tensorflow will pull data from
#trainDataObj = pvpObj(trainFileList, trainGtList, (1, 1, 1536), resizeMethod="crop", shuffle=True, skip=1, seed=None)
#testDataObj = pvpObj(testFileList, testGtList, (1, 1, 1536), resizeMethod="crop", shuffle=True, skip=1, seed=None)
#trainDataObj = pvpObj(trainFileList, trainGtList, (4, 4, 384), resizeMethod="crop", shuffle=True, skip=1, seed=None)
#testDataObj = pvpObj(testFileList, testGtList, (4, 4, 384), resizeMethod="crop", shuffle=True, skip=1, seed=None)
#trainDataObj = pvpObj(trainFileList, trainGtList, (8, 8, 96), resizeMethod="crop", shuffle=True, skip=1, seed=None)
#testDataObj = pvpObj(testFileList, testGtList, (8, 8, 96), resizeMethod="crop", shuffle=True, skip=1, seed=None)
trainDataObj = pvpObj(trainFileList, trainGtList, (16, 16, 24), resizeMethod="crop", shuffle=True, skip=1, seed=None)
testDataObj = pvpObj(testFileList, testGtList, (16, 16, 24), resizeMethod="crop", shuffle=True, skip=1, seed=None)
params = {
#Base output directory
'outDir': "/home/slundquist/mountData/tfLCA/",
#Inner run directory
'runDir': "/cifar_lca_topdown_s1only/",
'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
