115 lines
4.3 KiB
Python
115 lines
4.3 KiB
Python
import tensorflow as tf
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import numpy as np
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import random
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import pickle
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from PIL import Image
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from qrcode import make as makeqr
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from dnnlib import tflib
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import time, os, hashlib
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def main():
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# Define global variables.
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seed = random.randint(0,10000000)
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available_charaters = {'Anmicius', 'Camil', 'Grey', 'King', 'Ray'}
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# Select charater and input seed.
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selected_character = 'Grey'
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while selected_character not in available_charaters:
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selected_character = input('Type in the character you want to draw, e.g. \"Anmicius\" and \"Ray\" (no quotes).\n')
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if selected_character not in available_charaters:
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print('You typed in a character that is not available or you made a misspell, try agian.')
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seed_str = ''
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if seed_str != '':
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if seed_str.isdigit():
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seed = int(seed_str.encode('utf-8'))
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else:
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seed = int(hashlib.sha256(seed_str.encode('utf-8')).hexdigest(), 16) % 10**8
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print('INFO: Setting up variables...')
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tflib.init_tf()
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rnd = np.random.RandomState(seed)
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fmt = dict(func=tflib.convert_images_to_uint8, nchw_to_nhwc=True)
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print('INFO: Loading pretrained model...')
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Gs = pickle.load(open('models/network-%s-gs.pkl' % selected_character, 'rb'))
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latents = rnd.randn(1, Gs.input_shape[1])
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print('INFO: Generating...')
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images = Gs.run(latents, None, truncation_psi=0.7, randomize_noise=True, output_transform=fmt)
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im = Image.fromarray(images[0], 'RGB')
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qr = makeqr('This is an image automatically generated by Aotu Draw Bot by Rand0mZ.LiCloud provides computing resources. Seed: %d' % seed)
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w, h = im.size
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qw, qh = qr.size
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if qw > w:
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qr = qr.resize((w, w))
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elif qh > h:
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qr = qr.resize((h, h))
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qw, qh = qr.size
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imd = im.load()
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for i in range(w):
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for j in range(h):
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d = imd[i, j]
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imd[i, j] = d[:-1] +((d[-1] | 1) if qr.getpixel((i%qw, j%qh)) else (d[-1] & ~1),)
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print('Done!')
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save_name = '%s_%d.png' % (selected_character, seed)
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print('INFO: Saving %s' % save_name)
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output_dir = os.path.join(os.path.dirname(os.getcwd()) , 'ARAGS/格瑞')
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if not os.path.isdir(output_dir):
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os.mkdir(output_dir)
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im.save(os.path.join(output_dir, save_name))
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print('INFO: Image %s is saved in directory.' % save_name)
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print('INFO: All processes has done!')
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print('Thank you for using this software and obeying the terms of use above.')
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time.sleep(3)
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def generate_image(model, save_path, selected_character, seed, amount):
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tflib.init_tf()
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print('INFO: Loading pretrained model...')
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Gs = pickle.load(open(model, 'rb'))
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if not os.path.isdir(save_path):
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os.mkdir(save_path)
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for i in range(1, amount + 1):
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print('INFO: Generating image %d' %i)
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rnd = np.random.RandomState(seed)
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fmt = dict(func=tflib.convert_images_to_uint8, nchw_to_nhwc=True)
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latents = rnd.randn(1, Gs.input_shape[1])
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images = Gs.run(latents, None, truncation_psi=0.7, randomize_noise=True, output_transform=fmt)
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im = Image.fromarray(images[0], 'RGB')
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qr = makeqr('This is an image automatically generated by Aotu Draw Bot CLI by Rand0mZ hence this image is not for commercial propose. Seed: %d' % seed)
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w, h = im.size
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qw, qh = qr.size
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if qw > w:
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qr = qr.resize((w, w))
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elif qh > h:
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qr = qr.resize((h, h))
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qw, qh = qr.size
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imd = im.load()
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for i in range(w):
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for j in range(h):
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d = imd[i, j]
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imd[i, j] = d[:-1] +((d[-1] | 1) if qr.getpixel((i%qw, j%qh)) else (d[-1] & ~1),)
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print('Done!')
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save_name = '%s_%d.png' % (selected_character, seed)
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print('INFO: Saving %s' % save_name)
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im.save(os.path.join(save_path, save_name))
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print('INFO: Image %s is saved to %s.\n' % (save_name, save_path))
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seed += i - 1
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if __name__ == "__main__":
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main()
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