def update(self):
self.images = []
self.images_ui.clear()
path = self.selecter.getPath()
files = []
files = os.listdir(path)
# print "update_path:" + path
if path != "/":
files.insert(0, "..")
for f in files:
# Create QCustomQWidget
full_path = os.path.join(self.selecter.getPath(), f)
# print full_path
myQCustomQWidget = ImageFile(full_path)
# Create QListWidgetItem
myQListWidgetItem = QtGui.QListWidgetItem(self.images_ui)
# Set size hint# self.update()
myQListWidgetItem.setSizeHint(myQCustomQWidget.sizeHint()) #
myQListWidgetItem.setData(0, QtCore.QVariant(myQCustomQWidget))
# Add QListWidgetItem into QListWidget# self.images_ui.itemClicked.connect(self.itemClicked)
self.images_ui.addItem(
myQListWidgetItem) # self.setShown(True)
self.images_ui.setItemWidget(
myQListWidgetItem, myQCustomQWidget) # self.show()
self.images.append(myQCustomQWidget)
import sys import numpy as np import random as ran import tensorflow as tf import matplotlib.pyplot as plt from ImageFile import * from LabelFile import * from util import * fn_trn_img = "train-images-idx3-ubyte" fn_trn_lbl = "train-labels-idx1-ubyte" fn_tst_img = "t10k-images-idx3-ubyte" fn_tst_lbl = "t10k-labels-idx1-ubyte" trn_img = ImageFile(fn_trn_img) trn_lbl = LabelFile(fn_trn_lbl) tst_img = ImageFile(fn_tst_img) tst_lbl = LabelFile(fn_tst_lbl) # plot aggregated first N image vectors N=400 imgplot = plt.imshow(trn_img.image_data[:N], cmap='gray_r') plt.show() # plot a single digit display_digit_image(k=80, img=tst_img, lbl=tst_lbl) # data augmentation routines def rotate(img):
