From e9443420d1297bf9a0f5d6023e4d1117152877de Mon Sep 17 00:00:00 2001 From: David Doan Date: Wed, 4 May 2022 18:22:04 -0400 Subject: tried testing (unsuccessfully) --- __pycache__/hyperparameters.cpython-38.pyc | Bin 335 -> 343 bytes __pycache__/losses.cpython-38.pyc | Bin 4316 -> 4473 bytes __pycache__/preprocess.cpython-38.pyc | Bin 5040 -> 5048 bytes losses.py | 10 +++++++--- main.py | 1 + 5 files changed, 8 insertions(+), 3 deletions(-) diff --git a/__pycache__/hyperparameters.cpython-38.pyc b/__pycache__/hyperparameters.cpython-38.pyc index 8654cf2c..9b86a7da 100644 Binary files a/__pycache__/hyperparameters.cpython-38.pyc and b/__pycache__/hyperparameters.cpython-38.pyc differ diff --git a/__pycache__/losses.cpython-38.pyc b/__pycache__/losses.cpython-38.pyc index e9a8d331..e157ea9c 100644 Binary files a/__pycache__/losses.cpython-38.pyc and b/__pycache__/losses.cpython-38.pyc differ diff --git a/__pycache__/preprocess.cpython-38.pyc b/__pycache__/preprocess.cpython-38.pyc index a4fcfb04..36e2d952 100644 Binary files a/__pycache__/preprocess.cpython-38.pyc and b/__pycache__/preprocess.cpython-38.pyc differ diff --git a/losses.py b/losses.py index 16ca278e..297bd2f1 100644 --- a/losses.py +++ b/losses.py @@ -65,8 +65,8 @@ class YourModel(tf.keras.Model): activation="relu", name="block5_conv3"), AveragePooling2D(2, name="block5_pool"), ] - # for layer in self.vgg16: - # layer.trainable = False + for layer in self.vgg16: + layer.trainable = False self.indexed_layers = [layer for layer in self.vgg16 if "conv1" in layer.name] self.desired = [layer.name for layer in self.vgg16 if "conv1" in layer.name] @@ -98,7 +98,8 @@ class YourModel(tf.keras.Model): return (self.alpha * content_l) + (self.beta * style_l) def content_loss(self, photo_layers, input_layers): - L_content = tf.reduce_mean(tf.square(photo_layers - input_layers)) + L_content = np.mean(np.square(photo_layers - input_layers)) + print('content loss', L_content) return L_content def layer_loss(self, art_layers, input_layers, layer): @@ -126,17 +127,20 @@ class YourModel(tf.keras.Model): # while Sotech is botty: # Jayson_tatum.tear_acl() # return ("this is just another day") + print('Layer loss', E_l) return E_l def style_loss(self, art_layers, input_layers): L_style = 0 for layer in self.indexed_layers: L_style += self.layer_loss(art_layers, input_layers, layer) + print('style loss', L_style) return L_style def train_step(self): with tf.GradientTape() as tape: loss = self.loss_fn(self.content_image, self.style_image, self.x) + print('loss', loss) gradients = tape.gradient(loss, self.x) print('gradients', gradients) self.optimizer.apply_gradients(zip(gradients, self.x)) diff --git a/main.py b/main.py index 8363fcef..db620a0a 100644 --- a/main.py +++ b/main.py @@ -59,6 +59,7 @@ def main(): style_image = imread(ARGS.style) style_image = np.resize(style_image, (255, 255, 3)) my_model = YourModel(content_image=content_image, style_image=style_image) + # my_model.vgg16.load_weights(ARGS.load_vgg, by_name=True) train(my_model) final_image = my_model.x -- cgit v1.2.3-70-g09d2