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+### Copyright (C) 2017 NVIDIA Corporation. All rights reserved. 
+### Licensed under the CC BY-NC-SA 4.0 license (https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode).
+import numpy as np
+import os
+import ntpath
+import time
+from . import util
+from . import html
+import scipy.misc 
+try:
+    from StringIO import StringIO  # Python 2.7
+except ImportError:
+    from io import BytesIO         # Python 3.x
+
+class Visualizer():
+    def __init__(self, opt):
+        # self.opt = opt
+        self.tf_log = opt.tf_log
+        self.use_html = opt.isTrain and not opt.no_html
+        self.win_size = opt.display_winsize
+        self.name = opt.name
+        if self.tf_log:
+            import tensorflow as tf
+            self.tf = tf
+            self.log_dir = os.path.join(opt.checkpoints_dir, opt.name, 'logs')
+            self.writer = tf.summary.FileWriter(self.log_dir)
+
+        if self.use_html:
+            self.web_dir = os.path.join(opt.checkpoints_dir, opt.name, 'web')
+            self.img_dir = os.path.join(self.web_dir, 'images')
+            print('create web directory %s...' % self.web_dir)
+            util.mkdirs([self.web_dir, self.img_dir])
+        self.log_name = os.path.join(opt.checkpoints_dir, opt.name, 'loss_log.txt')
+        with open(self.log_name, "a") as log_file:
+            now = time.strftime("%c")
+            log_file.write('================ Training Loss (%s) ================\n' % now)
+
+    # |visuals|: dictionary of images to display or save
+    def display_current_results(self, visuals, epoch, step):
+        if self.tf_log: # show images in tensorboard output
+            img_summaries = []
+            for label, image_numpy in visuals.items():
+                # Write the image to a string
+                try:
+                    s = StringIO()
+                except:
+                    s = BytesIO()
+                scipy.misc.toimage(image_numpy).save(s, format="jpeg")
+                # Create an Image object
+                img_sum = self.tf.Summary.Image(encoded_image_string=s.getvalue(), height=image_numpy.shape[0], width=image_numpy.shape[1])
+                # Create a Summary value
+                img_summaries.append(self.tf.Summary.Value(tag=label, image=img_sum))
+
+            # Create and write Summary
+            summary = self.tf.Summary(value=img_summaries)
+            self.writer.add_summary(summary, step)
+
+        if self.use_html: # save images to a html file
+            for label, image_numpy in visuals.items():
+                if isinstance(image_numpy, list):
+                    for i in range(len(image_numpy)):
+                        img_path = os.path.join(self.img_dir, 'epoch%.3d_%s_%d.jpg' % (epoch, label, i))
+                        util.save_image(image_numpy[i], img_path)
+                else:
+                    img_path = os.path.join(self.img_dir, 'epoch%.3d_%s.jpg' % (epoch, label))
+                    util.save_image(image_numpy, img_path)
+
+            # update website
+            webpage = html.HTML(self.web_dir, 'Experiment name = %s' % self.name, reflesh=1)
+            for n in range(epoch, 0, -1):
+                webpage.add_header('epoch [%d]' % n)
+                ims = []
+                txts = []
+                links = []
+
+                for label, image_numpy in visuals.items():
+                    if isinstance(image_numpy, list):
+                        for i in range(len(image_numpy)):
+                            img_path = 'epoch%.3d_%s_%d.jpg' % (n, label, i)
+                            ims.append(img_path)
+                            txts.append(label+str(i))
+                            links.append(img_path)
+                    else:
+                        img_path = 'epoch%.3d_%s.jpg' % (n, label)
+                        ims.append(img_path)
+                        txts.append(label)
+                        links.append(img_path)
+                if len(ims) < 10:
+                    webpage.add_images(ims, txts, links, width=self.win_size)
+                else:
+                    num = int(round(len(ims)/2.0))
+                    webpage.add_images(ims[:num], txts[:num], links[:num], width=self.win_size)
+                    webpage.add_images(ims[num:], txts[num:], links[num:], width=self.win_size)
+            webpage.save()
+
+    # errors: dictionary of error labels and values
+    def plot_current_errors(self, errors, step):
+        if self.tf_log:
+            for tag, value in errors.items():            
+                summary = self.tf.Summary(value=[self.tf.Summary.Value(tag=tag, simple_value=value)])
+                self.writer.add_summary(summary, step)
+
+    # errors: same format as |errors| of plotCurrentErrors
+    def print_current_errors(self, epoch, i, errors, t):
+        message = '(epoch: %d, iters: %d, time: %.3f) ' % (epoch, i, t)
+        for k, v in errors.items():
+            if v != 0:
+                message += '%s: %.3f ' % (k, v)
+
+        print(message)
+        with open(self.log_name, "a") as log_file:
+            log_file.write('%s\n' % message)
+
+    # save image to the disk
+    def save_images(self, webpage, visuals, image_path):
+        image_dir = webpage.get_image_dir()
+        short_path = ntpath.basename(image_path[0])
+        name = os.path.splitext(short_path)[0]
+
+        webpage.add_header(name)
+        ims = []
+        txts = []
+        links = []
+
+        for label, image_numpy in visuals.items():
+            image_name = '%s_%s.jpg' % (name, label)
+            save_path = os.path.join(image_dir, image_name)
+            util.save_image(image_numpy, save_path)
+
+            ims.append(image_name)
+            txts.append(label)
+            links.append(image_name)
+        webpage.add_images(ims, txts, links, width=self.win_size)