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| import gradio as gr | |
| import numpy as np | |
| import torch | |
| from torch import nn | |
| import imageio | |
| import cv2 | |
| class Generator(nn.Module): | |
| # Refer to the link below for explanations about nc, nz, and ngf | |
| # https://pytorch.org/tutorials/beginner/dcgan_faces_tutorial.html#inputs | |
| def __init__(self, nc=4, nz=100, ngf=64): | |
| super(Generator, self).__init__() | |
| self.network = nn.Sequential( | |
| nn.ConvTranspose2d(nz, ngf * 4, 3, 1, 0, bias=False), | |
| nn.BatchNorm2d(ngf * 4), | |
| nn.ReLU(True), | |
| nn.ConvTranspose2d(ngf * 4, ngf * 2, 3, 2, 1, bias=False), | |
| nn.BatchNorm2d(ngf * 2), | |
| nn.ReLU(True), | |
| nn.ConvTranspose2d(ngf * 2, ngf, 4, 2, 0, bias=False), | |
| nn.BatchNorm2d(ngf), | |
| nn.ReLU(True), | |
| nn.ConvTranspose2d(ngf, nc, 4, 2, 1, bias=False), | |
| nn.Tanh(), | |
| ) | |
| def forward(self, input): | |
| output = self.network(input) | |
| return output | |
| def display_gif(file_name, save_name): | |
| images = [] | |
| for frame in range(8): | |
| frame_name = '%d' % (frame) | |
| image_filename = file_name + frame_name + '.png' | |
| images.append(imageio.imread(image_filename)) | |
| gif_filename = 'avatar_source.gif' | |
| return imageio.mimsave(gif_filename, images) | |
| def display_gif_pad(file_name, save_name): | |
| images = [] | |
| for frame in range(8): | |
| frame_name = '%d' % (frame) | |
| image_filename = file_name + frame_name + '.png' | |
| image = imageio.imread(image_filename) | |
| image = image[:, :, :3] | |
| image_pad = cv2.copyMakeBorder(image, 0, 0, 125, 125, cv2.BORDER_CONSTANT, value=0) | |
| images.append(image_pad) | |
| return imageio.mimsave(save_name, images) | |
| def display_image(file_name): | |
| image_filename = file_name + '0' + '.png' | |
| print(image_filename) | |
| image = imageio.imread(image_filename) | |
| imageio.imwrite('image.png', image) | |
| def run(action, hair, top, bottom): | |
| # == Source Avatar == | |
| # body | |
| #if body == "human":body = '0' | |
| #elif body == "alien": body = '1' | |
| body = '0' | |
| # hair | |
| if hair == "green": hair = '0' | |
| elif hair == "yellow": hair = '2' | |
| elif hair == "rose": hair = '4' | |
| elif hair == "red": hair = '7' | |
| elif hair == "wine": hair = '8' | |
| # top | |
| if top == "brown": top = '0' | |
| elif top == "blue": top = '1' | |
| elif top == "white": top = '2' | |
| # bottom | |
| if bottom == "white": bottom = '0' | |
| elif bottom == "golden": bottom = '1' | |
| elif bottom == "red": bottom = '2' | |
| elif bottom == "silver": bottom = '3' | |
| file_name_source = './Sprite/frames/domain_1/' + action + '/' | |
| file_name_source = file_name_source + 'front' + '_' + str(body) + str(bottom) + str(top) + str(hair) + '_' | |
| gif = display_gif_pad(file_name_source, 'avatar_source.gif') | |
| # == Target Avatar == | |
| body_target = '1' | |
| hair_target = np.random.choice('1', '3', '5', '6', '9') | |
| top_target = np.random.choice('3', '4', '5', '6') | |
| bottom_target = np.random.choice('4', '5', '6') | |
| file_name_target = './Sprite/frames/domain_2/' + action + '/' | |
| file_name_target = file_name_target + 'front' + '_' + str(body_target) + str(bottom_target) + str(top_target) + str(hair_target) + '_' | |
| gif_target = display_gif_pad(file_name_target, 'avatar_target.gif') | |
| return 'avatar_source.gif', 'avatar_target.gif' | |
| gr.Interface( | |
| run, | |
| inputs=[ | |
| gr.Radio(choices=["shoot", "slash", "spellcard", "thrust", "walk"], value="shoot"), | |
| gr.Radio(choices=["green", "yellow", "rose", "red", "wine"], value="green"), | |
| gr.Radio(choices=["brown", "blue", "white"], value="brown"), | |
| gr.Radio(choices=["white", "golden", "red", "silver"], value="white"), | |
| ], | |
| outputs=[ | |
| gr.components.Image(type="file", label="Source Avatar (Costumed by You)"), | |
| gr.components.Image(type="file", label="Target Avatar (Randomly Chosen)"), | |
| ], | |
| live=True, | |
| title="TransferVAE for Unsupervised Video Domain Adaptation", | |
| ).launch() | |