README-2.md

Applied Programming Coding Challenge #2

Approach #1 DCGAN with Pokemon sprites

• 

The GAN contained in the Jupyter notebook creates new images based on 151 pixelated Pokemon sprites.

Data

• Raw data for this GAN can be found in ./data/pokemon-sprites/raw or downloaded using the following functions which are contained in the notebook but commented.

import urllib.request

try:
 from google.colab import drive
 IN_COLAB = True
except:
 IN_COLAB = False

if IN_COLAB:
   drive.mount('/content/gdrive')
   dataroot_parent = "/content/gdrive/My Drive/Colab Files"
else:
   dataroot_parent = ".."

dataroot = dataroot_parent + "/data/pokemon-sprites"

def download_file(url, file_name):
   """Downloads a file from a given URL using to arbitrary headers"""
   
   hdr = {'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.11 (KHTML, like Gecko) Chrome/23.0.1271.64 Safari/537.11',
      'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
      'Accept-Charset': 'ISO-8859-1,utf-8;q=0.7,*;q=0.3',
      'Accept-Ecolor_channelsoding': 'none',
      'Accept-Language': 'en-US,en;q=0.8',
      'Connection': 'keep-alive'}
   req = urllib.request.Request(url, headers=hdr)
   response = urllib.request.urlopen(req)
   
   # Write response to file
   with open(file_name, mode="wb") as d:
       d.write(response.read())

def download_sprites_151():
   """Download sprites of original pokemon from alexonsager.net"""
   
   pokemon_count = 151
   for i in range(1, pokemon_count+1):
       url = "https://images.alexonsager.net/pokemon/" + str(i) + ".png"
       file_name = dataroot + "/raw/" + str(i).zfill(3) + ".png"
       download_file(url, file_name)

Approach #2 DCGAN with Pokemon sprites + augmented fused images

• 

The GAN contained in the Jupyter notebook creates new images based on 151 pixelated Pokemon sprites + fused versions resulting in 22801 images in total.

Data

• Raw data for this GAN (partially) can be found in ./data/pokemon-sprites-fused/raw or downloaded using the following functions which are contained in the notebook but commented.

import urllib.request

try:
 from google.colab import drive
 IN_COLAB = True
except:
 IN_COLAB = False

if IN_COLAB:
   drive.mount('/content/gdrive')
   dataroot_parent = "/content/gdrive/My Drive/Colab Files"
else:
   dataroot_parent = ".."

dataroot = dataroot_parent + "/data/pokemon-sprites"

def download_file(url, file_name):
   """Downloads a file from a given URL using to arbitrary headers"""
   
   hdr = {'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.11 (KHTML, like Gecko) Chrome/23.0.1271.64 Safari/537.11',
      'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
      'Accept-Charset': 'ISO-8859-1,utf-8;q=0.7,*;q=0.3',
      'Accept-Ecolor_channelsoding': 'none',
      'Accept-Language': 'en-US,en;q=0.8',
      'Connection': 'keep-alive'}
   req = urllib.request.Request(url, headers=hdr)
   response = urllib.request.urlopen(req)
   
   # Write response to file
   with open(file_name, mode="wb") as d:
       d.write(response.read())

#%%

       
def download_sprites_fused_151():
   """Download sprites of fused pokemon from alexonsager.net"""
   
   pokemon_count = 151
   for i in range(1, pokemon_count+1):
       for j in range(1, pokemon_count+1):
           url = "https://images.alexonsager.net/pokemon/fused/" + str(i) + "/" + str(i) + "." + str(j) + ".png"
           file_name = dataroot + "/raw/" + str(i).zfill(3) + "_" + str(j).zfill(3) + ".png"
           download_file(url, file_name)

Approach #2 DCGAN with Pokemon images

• 

The GAN contained in the Jupyter notebook creates new images based on 801 Pokemon images.

Data

• Raw data for this GAN can be found in ./data/pokemon-images-jpg/raw.