import os #os.system("pip install --upgrade pip") #os.system("pip install gradio==2.5.3") import onnxruntime as rt import sys import PIL from PIL import Image, ImageOps, ImageFile import numpy as np from pathlib import Path import collections from typing import Union, List import scipy.ndimage import requests MODEL_FILE = "ffhqu2vintage512_pix2pixHD_v1E11-inp2inst-simp.onnx" so = rt.SessionOptions() so.inter_op_num_threads = 4 so.intra_op_num_threads = 4 session = rt.InferenceSession(MODEL_FILE, sess_options=so) input_name = session.get_inputs()[0].name print("input_name = " + str(input_name)) output_name = session.get_outputs()[0].name print("output_name = " + str(output_name)) import os os.system("pip install dlib") import face_detection def array_to_image(array_in): array_in = np.squeeze(255*(array_in + 1)/2) array_in = np.transpose(array_in, (1, 2, 0)) im = Image.fromarray(array_in.astype(np.uint8)) return im 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=512): 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=512): 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 face2vintage( img: Image.Image, size: int ) -> Image.Image: aligned_img = align_first_face(img) if aligned_img is None: output=None else: output = session.run([output_name], {input_name: aligned_img})[0] output = array_to_image(output) aligned_img = array_to_image(aligned_img).resize((output.width, output.height)) output = img_concat_h(aligned_img, output) return output def inference(img): out = face2vintage(img, 512) return out title = "Vintage style Pix2PixHD" description = "Style a face to look more \"Vintage\". Upload an image with a face, or click on one of the examples below. If a face could not be detected, an image will still be created." article = "

See the Github Repo

samples: Sample00001Sample00002Sample00003Sample00004Sample00005

The \"Vintage Style\" Pix2PixHD model was trained by Doron Adler

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