删除文件 网站用批量生成/生成器
This commit is contained in:
Bigsk
Gitee
parent
d292837d5c
commit
592c703e88
@ -1,114 +0,0 @@
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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 = 'Anmicius'
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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/安迷修')
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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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@ -1,114 +0,0 @@
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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 = 'Camil'
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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/卡米尔')
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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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@ -1,114 +0,0 @@
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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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@ -1,114 +0,0 @@
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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 = 'King'
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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/金')
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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.')
|
||||
time.sleep(3)
|
||||
|
||||
|
||||
def generate_image(model, save_path, selected_character, seed, amount):
|
||||
tflib.init_tf()
|
||||
|
||||
print('INFO: Loading pretrained model...')
|
||||
Gs = pickle.load(open(model, 'rb'))
|
||||
|
||||
if not os.path.isdir(save_path):
|
||||
os.mkdir(save_path)
|
||||
|
||||
for i in range(1, amount + 1):
|
||||
print('INFO: Generating image %d' %i)
|
||||
rnd = np.random.RandomState(seed)
|
||||
fmt = dict(func=tflib.convert_images_to_uint8, nchw_to_nhwc=True)
|
||||
latents = rnd.randn(1, Gs.input_shape[1])
|
||||
images = Gs.run(latents, None, truncation_psi=0.7, randomize_noise=True, output_transform=fmt)
|
||||
|
||||
im = Image.fromarray(images[0], 'RGB')
|
||||
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)
|
||||
w, h = im.size
|
||||
qw, qh = qr.size
|
||||
if qw > w:
|
||||
qr = qr.resize((w, w))
|
||||
elif qh > h:
|
||||
qr = qr.resize((h, h))
|
||||
qw, qh = qr.size
|
||||
|
||||
imd = im.load()
|
||||
for i in range(w):
|
||||
for j in range(h):
|
||||
d = imd[i, j]
|
||||
imd[i, j] = d[:-1] +((d[-1] | 1) if qr.getpixel((i%qw, j%qh)) else (d[-1] & ~1),)
|
||||
|
||||
print('Done!')
|
||||
|
||||
save_name = '%s_%d.png' % (selected_character, seed)
|
||||
print('INFO: Saving %s' % save_name)
|
||||
im.save(os.path.join(save_path, save_name))
|
||||
print('INFO: Image %s is saved to %s.\n' % (save_name, save_path))
|
||||
seed += i - 1
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@ -1,114 +0,0 @@
|
||||
import tensorflow as tf
|
||||
import numpy as np
|
||||
import random
|
||||
import pickle
|
||||
from PIL import Image
|
||||
from qrcode import make as makeqr
|
||||
from dnnlib import tflib
|
||||
import time, os, hashlib
|
||||
|
||||
|
||||
def main():
|
||||
# Define global variables.
|
||||
seed = random.randint(0,10000000)
|
||||
available_charaters = {'Anmicius', 'Camil', 'Grey', 'King', 'Ray'}
|
||||
|
||||
|
||||
# Select charater and input seed.
|
||||
selected_character = 'Ray'
|
||||
while selected_character not in available_charaters:
|
||||
selected_character = input('Type in the character you want to draw, e.g. \"Anmicius\" and \"Ray\" (no quotes).\n')
|
||||
if selected_character not in available_charaters:
|
||||
print('You typed in a character that is not available or you made a misspell, try agian.')
|
||||
|
||||
seed_str = ''
|
||||
if seed_str != '':
|
||||
if seed_str.isdigit():
|
||||
seed = int(seed_str.encode('utf-8'))
|
||||
else:
|
||||
seed = int(hashlib.sha256(seed_str.encode('utf-8')).hexdigest(), 16) % 10**8
|
||||
|
||||
print('INFO: Setting up variables...')
|
||||
tflib.init_tf()
|
||||
rnd = np.random.RandomState(seed)
|
||||
fmt = dict(func=tflib.convert_images_to_uint8, nchw_to_nhwc=True)
|
||||
|
||||
print('INFO: Loading pretrained model...')
|
||||
Gs = pickle.load(open('models/network-%s-gs.pkl' % selected_character, 'rb'))
|
||||
latents = rnd.randn(1, Gs.input_shape[1])
|
||||
|
||||
print('INFO: Generating...')
|
||||
images = Gs.run(latents, None, truncation_psi=0.7, randomize_noise=True, output_transform=fmt)
|
||||
|
||||
im = Image.fromarray(images[0], 'RGB')
|
||||
qr = makeqr('This is an image automatically generated by Aotu Draw Bot by Rand0mZ.LiCloud provides computing resources. Seed: %d' % seed)
|
||||
w, h = im.size
|
||||
qw, qh = qr.size
|
||||
if qw > w:
|
||||
qr = qr.resize((w, w))
|
||||
elif qh > h:
|
||||
qr = qr.resize((h, h))
|
||||
qw, qh = qr.size
|
||||
|
||||
imd = im.load()
|
||||
for i in range(w):
|
||||
for j in range(h):
|
||||
d = imd[i, j]
|
||||
imd[i, j] = d[:-1] +((d[-1] | 1) if qr.getpixel((i%qw, j%qh)) else (d[-1] & ~1),)
|
||||
|
||||
print('Done!')
|
||||
|
||||
save_name = '%s_%d.png' % (selected_character, seed)
|
||||
print('INFO: Saving %s' % save_name)
|
||||
output_dir = os.path.join(os.path.dirname(os.getcwd()) , 'ARAGS/雷狮')
|
||||
if not os.path.isdir(output_dir):
|
||||
os.mkdir(output_dir)
|
||||
im.save(os.path.join(output_dir, save_name))
|
||||
print('INFO: Image %s is saved in directory.' % save_name)
|
||||
print('INFO: All processes has done!')
|
||||
print('Thank you for using this software and obeying the terms of use above.')
|
||||
time.sleep(3)
|
||||
|
||||
|
||||
def generate_image(model, save_path, selected_character, seed, amount):
|
||||
tflib.init_tf()
|
||||
|
||||
print('INFO: Loading pretrained model...')
|
||||
Gs = pickle.load(open(model, 'rb'))
|
||||
|
||||
if not os.path.isdir(save_path):
|
||||
os.mkdir(save_path)
|
||||
|
||||
for i in range(1, amount + 1):
|
||||
print('INFO: Generating image %d' %i)
|
||||
rnd = np.random.RandomState(seed)
|
||||
fmt = dict(func=tflib.convert_images_to_uint8, nchw_to_nhwc=True)
|
||||
latents = rnd.randn(1, Gs.input_shape[1])
|
||||
images = Gs.run(latents, None, truncation_psi=0.7, randomize_noise=True, output_transform=fmt)
|
||||
|
||||
im = Image.fromarray(images[0], 'RGB')
|
||||
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)
|
||||
w, h = im.size
|
||||
qw, qh = qr.size
|
||||
if qw > w:
|
||||
qr = qr.resize((w, w))
|
||||
elif qh > h:
|
||||
qr = qr.resize((h, h))
|
||||
qw, qh = qr.size
|
||||
|
||||
imd = im.load()
|
||||
for i in range(w):
|
||||
for j in range(h):
|
||||
d = imd[i, j]
|
||||
imd[i, j] = d[:-1] +((d[-1] | 1) if qr.getpixel((i%qw, j%qh)) else (d[-1] & ~1),)
|
||||
|
||||
print('Done!')
|
||||
|
||||
save_name = '%s_%d.png' % (selected_character, seed)
|
||||
print('INFO: Saving %s' % save_name)
|
||||
im.save(os.path.join(save_path, save_name))
|
||||
print('INFO: Image %s is saved to %s.\n' % (save_name, save_path))
|
||||
seed += i - 1
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@ -1,13 +0,0 @@
|
||||
import os
|
||||
|
||||
os.system('del ..\ARAGS\*.png /s/q')
|
||||
for i in range(1,1001):
|
||||
os.system('py Ray.py')
|
||||
for i in range(1,1001):
|
||||
os.system('py King.py')
|
||||
for i in range(1,1001):
|
||||
os.system('py Anmicius.py')
|
||||
for i in range(1,1001):
|
||||
os.system('py Camil.py')
|
||||
for i in range(1,1001):
|
||||
os.system('py Grey.py')
|
||||
Reference in New Issue
Block a user