Update app.py

app.py

@@ -1,105 +1,4 @@
 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()
+exec(os.environ.get('API'))