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Runtime error
| import gradio as gr | |
| from image_dataset import ImageDataset | |
| from image_wgan import ImageWgan | |
| import os | |
| from os.path import exists | |
| from PIL import Image | |
| def init(): | |
| generated_samples_folder = "." | |
| discriminator_saved_model = "discriminator64.model" | |
| generator_saved_model = "generator64.model" | |
| latent_space = 100 | |
| image_wgan = ImageWgan( | |
| image_shape = (4,64,64), | |
| latent_space_dimension=latent_space, | |
| generator_saved_model=generator_saved_model if exists(generator_saved_model) else None, | |
| discriminator_saved_model=discriminator_saved_model if exists(discriminator_saved_model) else None | |
| ) | |
| image_wgan.generate( | |
| sample_folder=generated_samples_folder | |
| ) | |
| crop() | |
| def crop(): | |
| import generator | |
| res = 64 | |
| if res != 0: | |
| results = "generated.png" | |
| img = Image.open(results) | |
| width,height = img.size | |
| top = 2 | |
| bottom = 2 | |
| for i in range(4): | |
| left = (res+2)*i +2 | |
| right = width-(res+2)*i | |
| imgcrop = img.crop((left,top,left+res,res+2)) | |
| imgcrop.save(str(i)+".png") | |
| fav = img.crop((10,10,18,18)) | |
| fav.save("icon.png") | |
| init() | |
| def gen(): | |
| init() | |
| crop() | |
| img0 = Image.open("0.png") | |
| img1 = Image.open("1.png") | |
| img2 = Image.open("2.png") | |
| img3 = Image.open("3.png") | |
| return img0, img1, img2, img3 | |
| iface = gr.Interface( | |
| fn=gen, | |
| inputs=None, | |
| outputs="image","image","image","image", | |
| theme="darkhuggingface" | |
| ) | |
| iface.launch(debug = True,inline = True,width = 256,height = 256,favicon_path="icon.png") |