nnhash.py

# 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

# Load ONNX model
session = onnxruntime.InferenceSession(sys.argv[1])

# Load output hash matrix
seed1 = open(sys.argv[2], 'rb').read()[128:]
seed1 = np.frombuffer(seed1, dtype=np.float32)
seed1 = seed1.reshape([96, 128])

# Preprocess image
image = Image.open(sys.argv[3]).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)

print(hash_hex)