app.py

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 = "<span style='color: #191970;'>Aiconvert.online</span>"
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 = ""

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,
    css=".gradio-container {background-color: #FFF8DC;} footer{display:none !important;}",
    examples=examples,
    enable_queue=True,
    allow_flagging=False
    ).launch()