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#!/usr/bin/env python3
import os
import tensorflow as tf
from tensorflow.keras.layers import Input, Flatten, Dense, Subtract
from tensorflow.keras.models import Model
import sys
sys.path.append(os.getcwd())
from config import SIA_MODEL_PATH
def build_dummy_siamese():
inp_a = Input(shape=(224, 224, 1), name="img_a")
inp_b = Input(shape=(224, 224, 1), name="img_b")
encoder_input = Input(shape=(224, 224, 1))
x = Flatten()(encoder_input)
x = Dense(16, activation="relu")(x)
encoder = Model(encoder_input, x)
encoded_a = encoder(inp_a)
encoded_b = encoder(inp_b)
distance = Subtract()([encoded_a, encoded_b])
model = Model(inputs=[inp_a, inp_b], outputs=distance)
return model
if __name__ == "__main__":
print("Building and converting dummy Siamese model...")
model = build_dummy_siamese()
converter = tf.lite.TFLiteConverter.from_keras_model(model)
converter.optimizations = [tf.lite.Optimize.DEFAULT]
tflite_model = converter.convert()
os.makedirs(os.path.dirname(SIA_MODEL_PATH), exist_ok=True)
with open(SIA_MODEL_PATH, "wb") as f:
f.write(tflite_model)
print(f"✅ Dummy TFLite signature model saved to '{SIA_MODEL_PATH}'")
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