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# 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) |