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| import os | |
| import torch | |
| import PIL.Image | |
| import numpy as np | |
| import gradio as gr | |
| from yarg import get | |
| from models.stylegan_generator import StyleGANGenerator | |
| from models.stylegan2_generator import StyleGAN2Generator | |
| from utils.constants import VALID_CHOICES, ENABLE_GPU, MODEL_NAME, OUTPUT_LIST, description, title, css, article | |
| from utils.image_manip import tensor_to_pil, concat_images | |
| def get_generator(model_name): | |
| if model_name == 'stylegan_ffhq': | |
| generator = StyleGANGenerator(model_name) | |
| elif model_name == 'stylegan2_ffhq': | |
| generator = StyleGAN2Generator(model_name) | |
| else: | |
| raise ValueError('Model name not recognized') | |
| if ENABLE_GPU: | |
| generator = generator.cuda() | |
| return generator | |
| generator = get_generator(MODEL_NAME) | |
| boundaries = { | |
| boundary:np.squeeze(np.load(open(os.path.join('boundaries', MODEL_NAME, 'boundary_%s.npy' % boundary), 'rb'))) | |
| for boundary in VALID_CHOICES | |
| } | |
| def inference(seed, coef, nb_images, list_choices): | |
| global generator, boundaries | |
| np.random.seed(seed) | |
| latent_codes = generator.easy_sample(nb_images) | |
| if ENABLE_GPU: | |
| latent_codes = latent_codes.cuda() | |
| generator = generator.cuda() | |
| generated_images = generator.easy_synthesize(latent_codes) | |
| generated_images = tensor_to_pil(generated_images) | |
| new_latent_codes = latent_codes.copy() | |
| for i, _ in enumerate(generated_images): | |
| for choice in list_choices: | |
| new_latent_codes[i, :] += boundaries[choice]*coef | |
| modified_generated_images = generator.easy_synthesize(new_latent_codes) | |
| modified_generated_images = tensor_to_pil(modified_generated_images) | |
| concatenated_output = concat_images(generated_images, modified_generated_images) | |
| return concatenated_output | |
| # https://huggingface.co/spaces/osanseviero/6DRepNet/blob/main/app.py | |
| iface = gr.Interface( | |
| fn=inference, | |
| inputs=[ | |
| gr.inputs.Slider( | |
| minimum=0, | |
| maximum=1000, | |
| step=1, | |
| default=644, | |
| label="Random seed to use for the generation" | |
| ), | |
| gr.inputs.Slider( | |
| minimum=-3, | |
| maximum=3, | |
| step=0.1, | |
| default=1, | |
| label="Modification coefficient", | |
| ), | |
| gr.inputs.Slider( | |
| minimum=1, | |
| maximum=10, | |
| step=1, | |
| default=2, | |
| label="Number of images to generate", | |
| ), | |
| gr.inputs.CheckboxGroup( | |
| VALID_CHOICES, | |
| default=[], | |
| type="value", | |
| label="Select attributes to modify", | |
| optional=False | |
| ) | |
| ], | |
| outputs=OUTPUT_LIST, | |
| layout="horizontal", | |
| theme="peach", | |
| description=description, | |
| title=title, | |
| css=css, | |
| article=article | |
| ) | |
| iface.launch() |