import os os.system("pip install --upgrade pip") os.system("pip install dlib") import sys import face_detection import PIL from PIL import Image, ImageOps import numpy as np import torch torch.set_grad_enabled(False) net = torch.jit.load('apocalyptify_p2s2p_torchscript_cpu.pt') net.eval() def tensor2im(var): var = var.cpu().detach().transpose(0, 2).transpose(0, 1).numpy() var = ((var + 1) / 2) var[var < 0] = 0 var[var > 1] = 1 var = var * 255 return Image.fromarray(var.astype('uint8')) def image_as_array(image_in): im_array = np.array(image_in, np.float32) im_array = (im_array/255)*2 - 1 im_array = np.transpose(im_array, (2, 0, 1)) im_array = np.expand_dims(im_array, 0) return im_array def find_aligned_face(image_in, size=256): aligned_image, n_faces, quad = face_detection.align(image_in, face_index=0, output_size=size) return aligned_image, n_faces, quad def align_first_face(image_in, size=256): aligned_image, n_faces, quad = find_aligned_face(image_in,size=size) if n_faces == 0: try: image_in = ImageOps.exif_transpose(image_in) except: print("exif problem, not rotating") image_in = image_in.resize((size, size)) im_array = image_as_array(image_in) else: im_array = image_as_array(aligned_image) return im_array def img_concat_h(im1, im2): dst = Image.new('RGB', (im1.width + im2.width, im1.height)) dst.paste(im1, (0, 0)) dst.paste(im2, (im1.width, 0)) return dst import gradio as gr def face2drag( img: Image.Image, size: int ) -> Image.Image: aligned_img = align_first_face(img) if aligned_img is None: output=None else: input = torch.Tensor(aligned_img) output = net(input) output = tensor2im(output[0]) output = img_concat_h(tensor2im(torch.Tensor(aligned_img)[0]), output) return output import os import collections from typing import Union, List import numpy as np from PIL import Image import PIL.Image import PIL.ImageFile import numpy as np import scipy.ndimage import requests def inference(img): out = face2drag(img, 256) return out title = "Apocalyptify" description = "How will your face look after the Apocalypse? Will you become a Zombie? A Ghoul? A person who fights them? Upload an image with a face, or click one of the examples below. If a face could not be detected, A face will still be created based on the features of the input." article = "

Github Repo

samples: Sample00001Sample00002Sample00003Sample00004Sample00005

The Apocalypse model was fine tuned on a pre-trained Pixel2Style2Pixel model by Doron Adler

" examples=[['Example00001.jpg'],['Example00002.jpg'],['Example00003.jpg'],['Example00004.jpg'],['Example00005.jpg'], ['Example00006.jpg']] gr.Interface(inference, gr.inputs.Image(type="pil",shape=(1024,1024)), gr.outputs.Image(type="pil"),title=title,description=description,article=article,examples=examples,enable_queue=True).launch()