Created
September 3, 2023 13:25
-
-
Save alimoeeny/e6b0b763d27c173892ef4e785973e7d2 to your computer and use it in GitHub Desktop.
for testing and validation purposes, a keras based networks that returns the input image as is
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
from tensorflow import keras | |
from tensorflow.keras import layers | |
import numpy as np | |
IMAGE_SIDE = 256 | |
input = layers.Input(shape=(IMAGE_SIDE, IMAGE_SIDE, 3)) | |
x = keras.layers.Dense(3,"linear" )(input) | |
outputs = keras.layers.Dense(3, activation="linear")(x) | |
model = keras.Model(input, outputs) | |
optimizer = keras.optimizers.Adam() | |
# optimizer = tf.keras.optimizers.Adagrad(learning_rate=learning_rate, initial_accumulator_value=0.1,epsilon=1e-07,name="Adagrad",) | |
model.compile( | |
optimizer=optimizer, | |
loss=keras.losses.BinaryCrossentropy(), # metrics=[keras.metrics.BinaryAccuracy(), keras.metrics.BinaryCrossentropy(), keras.metrics.MeanSquaredError()] | |
) | |
model.summary() | |
og_weights = model.get_weights() | |
#print(f"{og_weights}") | |
for layer in model.layers: | |
#print(f"Layer: {layer.name} {layer.get_weights()} ") | |
if "input" not in layer.name: | |
layer.set_weights((np.ones((3,3)) / 3.0, np.zeros((3,)))) | |
print("------------") | |
print(f"{model.get_weights()}") | |
i = np.ones((1, 256,256,3)) * .276 | |
print(f"i: {i}") | |
p = model.predict(i) | |
print(f"P: {p}") | |
print("------------") |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment