# Copyright 2021 Asuhariet Ygvar
# 
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# 
# http://www.apache.org/licenses/LICENSE-2.0
# 
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express
# or implied. See the License for the specific language governing
# permissions and limitations under the License.

import sys
import onnxruntime
import numpy as np
from PIL import Image
import gradio as gr



# Load ONNX model
session = onnxruntime.InferenceSession('model.onnx')

# Load output hash matrix
seed1 = open('neuralhash_128x96_seed1.dat', 'rb').read()[128:]
seed1 = np.frombuffer(seed1, dtype=np.float32)
seed1 = seed1.reshape([96, 128])

# Preprocess image
def inference(img):
  image = Image.open(img.name).convert('RGB')
  image = image.resize([360, 360])
  arr = np.array(image).astype(np.float32) / 255.0
  arr = arr * 2.0 - 1.0
  arr = arr.transpose(2, 0, 1).reshape([1, 3, 360, 360])
  
  # Run model
  inputs = {session.get_inputs()[0].name: arr}
  outs = session.run(None, inputs)
  
  # Convert model output to hex hash
  hash_output = seed1.dot(outs[0].flatten())
  hash_bits = ''.join(['1' if it >= 0 else '0' for it in hash_output])
  hash_hex = '{:0{}x}'.format(int(hash_bits, 2), len(hash_bits) // 4)
  
  return hash_hex
 
title = "Anime2Sketch"
description = "demo for Anime2Sketch. To use it, simply upload your image, or click one of the examples to load them. Read more at the links below."
article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2104.05703'>Adversarial Open Domain Adaption for Sketch-to-Photo Synthesis</a> | <a href='https://github.com/Mukosame/Anime2Sketch'>Github Repo</a></p>"

gr.Interface(
    inference, 
    gr.inputs.Image(type="file", label="Input"), 
    gr.outputs.Textbox(label="Output Text"),
    title=title,
    description=description,
    article=article
    ).launch(debug=True)