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Commit 0d6427c2 authored by tomrink's avatar tomrink
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test...

parent 8d334349
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......@@ -173,6 +173,7 @@ class ESPCN:
self.X_img = tf.keras.Input(shape=(None, None, self.n_chans))
# self.X_img = tf.keras.Input(shape=(36, 36, self.n_chans))
self.X_img = tf.keras.Input(shape=(32, 32, self.n_chans))
# self.X_img = tf.keras.Input(shape=(66, 66, self.n_chans))
self.inputs.append(self.X_img)
......@@ -196,12 +197,12 @@ class ESPCN:
# label = label[:, label_idx, :, :]
label = label[:, label_idx, 3:67, 3:67]
label = np.expand_dims(label, axis=3)
#label = tf.image.resize(label, (32, 32), method='nearest').numpy()
label = tf.image.resize(label, (32, 32), method='nearest').numpy()
# data = data[:, data_idx, :, :]
data = data[:, data_idx, 3:67, 3:67]
data = np.expand_dims(data, axis=3)
#data = tf.image.resize(data, (32, 32), method='nearest').numpy()
data = tf.image.resize(data, (32, 32), method='nearest').numpy()
# data = tf.image.resize(data, (36, 36)).numpy()
data = data.astype(np.float32)
......@@ -346,6 +347,8 @@ class ESPCN:
print('input: ', conv.shape)
conv = conv_b = tf.keras.layers.Conv2D(num_filters, kernel_size=3, padding=padding)(input_2d)
# conv = conv_b = tf.keras.layers.Conv2D(num_filters, kernel_size=3, padding='VALID')(input_2d)
print(conv.shape)
if NOISE_TRAINING:
conv = conv_b = tf.keras.layers.GaussianNoise(stddev=NOISE_STDDEV)(conv)
......
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