MercuriXito

""" ImageViewer which supports dragging and scaling and
fits altered size of windows.
"""
import os
import cv2
import numpy as np
from PIL import ImageTk
import PIL.Image as Image
from copy import deepcopy

MercuriXito

Train Frame

GAN 训练框架版本v2。

Modified

对简单的 Conditional GAN 和 Unconditional GAN 可以直接简单套用。 自定义的训练方式通过继承TrainerFrame类，并重写某些函数的形式，如例子的DCGANTrainer。

Problems Remained

MercuriXito

import os, sys, json
import re

class BibtexParser:
    """ Simple Parser of bibtex
    """
    def __init__(self, path, encoding = "utf-8"):
        # self.path = os.path.abspath(path)
        self.path = path
        self.encoding = encoding

MercuriXito

import torch
import torch.nn.functional as F
from torch.nn.functional import conv2d
import numpy as np 

mse = lambda x,y: np.mean((x-y).flatten() ** 2)

def psnr(image1, image2, L = 255, eps = 1e-6):
    m = mse(image1, image2)
    return np.log10(L**2 / (m + eps)) * 10

MercuriXito

import torch
import torch.nn as nn 
import torch.nn.functional as F 

# apply 函数针对net.children()， apply的参数为一个函数，该函数的输入是 Module
def weights_init(m):
    class_name = m.__class__.__name__
    if class_name.find("conv") != -1:
        m.weight.data.normal_(0,0.02)
    elif class_name.find("norm") !=  -1:

MercuriXito