Arief-AK · Arief-AK · Feb 27, 2025 · Feb 26, 2025 · Feb 26, 2025 · Feb 27, 2025
diff --git a/README.md b/README.md
@@ -1,4 +1,7 @@
 # Machine-Learning: Real-Time-Object-Classification
+
+[![CML](https://github.com/Arief-AK/Machine-Learning-Real-Time-Object-Classification/actions/workflows/ci.yml/badge.svg)](https://github.com/Arief-AK/Machine-Learning-Real-Time-Object-Classification/actions/workflows/ci.yml)
+
 Application of machine learning models to recognise objects from the [CIFAR-10](https://www.cs.toronto.edu/~kriz/cifar.html) dataset. This work uses the [TensorFlow](https://www.tensorflow.org/) framework to build, train, and deploy models to produce real-time object classifications.
 
 >[!NOTE]

diff --git a/Train.py b/Train.py
@@ -6,13 +6,18 @@
 from include.TensorModel import TensorModel
 from include.ModelProfiler import ModelProfiler
 
-NUM_EPOCHS = 25
+NUM_EPOCHS = 5
 BATCH_FITTING = 128
 BATCH_PROFILING = [32, 64, 128]
 
 MODELS = ["base_model", "batch_norm_model", "batch_norm_model_sgd", "batch_norm_model_rmsprop"]
 USE_EXISTING_MODELS = True
 
+SAVE_MODELS = True
+SAVE_MODELS_AS_H5 = True
+SAVE_MODELS_AS_KERAS = True
+SAVE_MODELS_AS_SavedModel = True
+
 def create_predicition_matrix(model_handler: TensorModel, visualiser: Visualiser, model, x_test, y_test, str_model):
     conf_matrix = model_handler.compute_confusion_matrix(model, x_test, y_test)
     visualiser.plot_confusion_matrix(conf_matrix, model_handler.get_class_names(), str_model)
@@ -22,8 +27,6 @@ def create_predicition_matrix(model_handler: TensorModel, visualiser: Visualiser
     visualiser.plot_diagonal_confusion_matrix(diagonal_matrix, model_handler.get_class_names(), str_model)
 
 def train_model(model_name:str, model_handler: TensorModel, visualiser: Visualiser, logger: Logger, x_train, y_train, x_test, y_test, batch_size) -> tuple:
-    logger.info(f"Eager enabled: {tf.executing_eagerly()}")
-
     # Check if model exists
     if USE_EXISTING_MODELS and os.path.exists(f"models/{model_name}.h5"):
         model = model = tf.keras.models.load_model(f"models/{model_name}.h5")
@@ -38,7 +41,16 @@ def train_model(model_name:str, model_handler: TensorModel, visualiser: Visualis
 
     history = model.fit(x_train, y_train, epochs=NUM_EPOCHS, batch_size=batch_size, validation_data=(x_test, y_test))
     test_loss, test_acc = model.evaluate(x_test, y_test)
-    model.save(f"models/{model_name}.h5")
+
+    if SAVE_MODELS:
+        if SAVE_MODELS_AS_H5:
+            model.save(f"models/{model_name}.h5")
+
+        if SAVE_MODELS_AS_KERAS:
+            model.save(f"models/{model_name}.keras")
+
+        if SAVE_MODELS_AS_SavedModel:
+            model.export(f"models/{model_name}_saved_model")
 
     logger.info(f"Model accuracy: {test_acc * 100:.2f}%")
     visualiser.plot_training_history(history, model_name)
@@ -76,14 +88,14 @@ def profile_models(model_acc_results:dict, visualiser: Visualiser, logger: Logge
             logger.info(f"Accuracy:{accuracy * 100:.2f}%\n")
 
 if __name__ == "__main__":
-    # Initialise variables
+    # # Initialise variables
     model_acc_results = {}
 
-    # Create a logger
+    # # Create a logger
     logger = Logger(__name__)
     logger.set_level(logging.INFO)
 
-    # Initialise visualiser
+    # # Initialise visualiser
     visualiser = Visualiser()
 
     # Initalise model handler

diff --git a/images/Inference/base_model/base_model_128_inference_timings.png b/images/Inference/base_model/base_model_128_inference_timings.png
diff --git a/images/Inference/base_model/base_model_32_inference_timings.png b/images/Inference/base_model/base_model_32_inference_timings.png
diff --git a/images/Inference/base_model/base_model_64_inference_timings.png b/images/Inference/base_model/base_model_64_inference_timings.png
diff --git a/images/Inference/batch_norm_model/batch_norm_model_128_inference_timings.png b/images/Inference/batch_norm_model/batch_norm_model_128_inference_timings.png
diff --git a/images/Inference/batch_norm_model/batch_norm_model_32_inference_timings.png b/images/Inference/batch_norm_model/batch_norm_model_32_inference_timings.png
diff --git a/images/Inference/batch_norm_model/batch_norm_model_64_inference_timings.png b/images/Inference/batch_norm_model/batch_norm_model_64_inference_timings.png
diff --git a/...nce/batch_norm_model_rmsprop/batch_norm_model_rmsprop_128_inference_timings.png b/...nce/batch_norm_model_rmsprop/batch_norm_model_rmsprop_128_inference_timings.png
diff --git a/...ence/batch_norm_model_rmsprop/batch_norm_model_rmsprop_32_inference_timings.png b/...ence/batch_norm_model_rmsprop/batch_norm_model_rmsprop_32_inference_timings.png
diff --git a/...ence/batch_norm_model_rmsprop/batch_norm_model_rmsprop_64_inference_timings.png b/...ence/batch_norm_model_rmsprop/batch_norm_model_rmsprop_64_inference_timings.png
diff --git a/...s/Inference/batch_norm_model_sgd/batch_norm_model_sgd_128_inference_timings.png b/...s/Inference/batch_norm_model_sgd/batch_norm_model_sgd_128_inference_timings.png
diff --git a/...es/Inference/batch_norm_model_sgd/batch_norm_model_sgd_32_inference_timings.png b/...es/Inference/batch_norm_model_sgd/batch_norm_model_sgd_32_inference_timings.png
diff --git a/...es/Inference/batch_norm_model_sgd/batch_norm_model_sgd_64_inference_timings.png b/...es/Inference/batch_norm_model_sgd/batch_norm_model_sgd_64_inference_timings.png
diff --git a/images/Training/base_model/base_model_training_confusion_matrix.png b/images/Training/base_model/base_model_training_confusion_matrix.png
diff --git a/images/Training/base_model/base_model_training_diagonal_confusion_matrix.png b/images/Training/base_model/base_model_training_diagonal_confusion_matrix.png
diff --git a/images/Training/base_model/base_model_training_history.png b/images/Training/base_model/base_model_training_history.png
diff --git a/images/Training/batch_norm_model/batch_norm_model_training_confusion_matrix.png b/images/Training/batch_norm_model/batch_norm_model_training_confusion_matrix.png
diff --git a/...aining/batch_norm_model/batch_norm_model_training_diagonal_confusion_matrix.png b/...aining/batch_norm_model/batch_norm_model_training_diagonal_confusion_matrix.png
diff --git a/images/Training/batch_norm_model/batch_norm_model_training_history.png b/images/Training/batch_norm_model/batch_norm_model_training_history.png
diff --git a/...batch_norm_model_rmsprop/batch_norm_model_rmsprop_training_confusion_matrix.png b/...batch_norm_model_rmsprop/batch_norm_model_rmsprop_training_confusion_matrix.png
diff --git a/...m_model_rmsprop/batch_norm_model_rmsprop_training_diagonal_confusion_matrix.png b/...m_model_rmsprop/batch_norm_model_rmsprop_training_diagonal_confusion_matrix.png
diff --git a/...Training/batch_norm_model_rmsprop/batch_norm_model_rmsprop_training_history.png b/...Training/batch_norm_model_rmsprop/batch_norm_model_rmsprop_training_history.png
diff --git a/...raining/batch_norm_model_sgd/batch_norm_model_sgd_training_confusion_matrix.png b/...raining/batch_norm_model_sgd/batch_norm_model_sgd_training_confusion_matrix.png
diff --git a/...atch_norm_model_sgd/batch_norm_model_sgd_training_diagonal_confusion_matrix.png b/...atch_norm_model_sgd/batch_norm_model_sgd_training_diagonal_confusion_matrix.png
diff --git a/images/Training/batch_norm_model_sgd/batch_norm_model_sgd_training_history.png b/images/Training/batch_norm_model_sgd/batch_norm_model_sgd_training_history.png
diff --git a/images/augmented_sample_image.png b/images/augmented_sample_image.png
diff --git a/include/TensorModel.py b/include/TensorModel.py
@@ -47,9 +47,13 @@ def load_data(self) -> tuple:
     def get_augmentation(self) -> tf.keras.Sequential:
         # Create a data augmentation layer
         data_augmentation = tf.keras.Sequential([
-            tf.keras.layers.RandomFlip("horizontal"),   # Randomly flip images horizontally
-            tf.keras.layers.RandomRotation(0.1),        # Randomly rotate image up to 10%
-            tf.keras.layers.RandomZoom(0.1)    # Randomly zoom image up to 10%
+            tf.keras.layers.RandomFlip("horizontal"),                                                               # Randomly flip images horizontally
+            tf.keras.layers.RandomRotation(0.1),                                                                    # Randomly rotate image up to 10%
+            tf.keras.layers.RandomZoom(0.1),                                                                        # Randomly zoom image up to 10%
+            tf.keras.layers.RandomContrast(0.1),                                                                    # Randomly adjust contrast up to 10%
+            tf.keras.layers.Lambda(lambda x: tf.image.random_brightness(x, max_delta=0.2)),                         # Randomly adjust brightness
+            tf.keras.layers.Lambda(lambda x: tf.image.random_crop(x, size=[tf.shape(x)[0], tf.shape(x)[1] - 8, tf.shape(x)[2] - 8, tf.shape(x)[3]])),   # Cutout augmentation
+            tf.keras.layers.Lambda(lambda x: 0.5 * x + 0.5 * tf.roll(x, shift=1, axis=0))                                                               # MixUp augmentation (approximate)
         ])
 
         return data_augmentation

diff --git a/models/base_model.h5 b/models/base_model.h5
diff --git a/models/base_model.keras b/models/base_model.keras
diff --git a/models/base_model_saved_model/fingerprint.pb b/models/base_model_saved_model/fingerprint.pb
@@ -0,0 +1 @@
+���������ݙ�ٝ�x�������� ������(���������2
diff --git a/models/base_model_saved_model/saved_model.pb b/models/base_model_saved_model/saved_model.pb
diff --git a/models/base_model_saved_model/variables/variables.data-00000-of-00001 b/models/base_model_saved_model/variables/variables.data-00000-of-00001
diff --git a/models/base_model_saved_model/variables/variables.index b/models/base_model_saved_model/variables/variables.index
diff --git a/models/batch_norm_model.h5 b/models/batch_norm_model.h5
diff --git a/models/batch_norm_model.keras b/models/batch_norm_model.keras
diff --git a/models/batch_norm_model_rmsprop.h5 b/models/batch_norm_model_rmsprop.h5
diff --git a/models/batch_norm_model_rmsprop.keras b/models/batch_norm_model_rmsprop.keras
diff --git a/models/batch_norm_model_rmsprop_saved_model/fingerprint.pb b/models/batch_norm_model_rmsprop_saved_model/fingerprint.pb
@@ -0,0 +1 @@
+����қ��u��ﳆЭ���������8 ���گ��ւ(Ȅ����=2
diff --git a/models/batch_norm_model_rmsprop_saved_model/saved_model.pb b/models/batch_norm_model_rmsprop_saved_model/saved_model.pb
diff --git a/models/batch_norm_model_rmsprop_saved_model/variables/variables.data-00000-of-00001 b/models/batch_norm_model_rmsprop_saved_model/variables/variables.data-00000-of-00001
diff --git a/models/batch_norm_model_rmsprop_saved_model/variables/variables.index b/models/batch_norm_model_rmsprop_saved_model/variables/variables.index
diff --git a/models/batch_norm_model_saved_model/fingerprint.pb b/models/batch_norm_model_saved_model/fingerprint.pb
@@ -0,0 +1 @@
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diff --git a/models/batch_norm_model_saved_model/saved_model.pb b/models/batch_norm_model_saved_model/saved_model.pb
diff --git a/models/batch_norm_model_saved_model/variables/variables.data-00000-of-00001 b/models/batch_norm_model_saved_model/variables/variables.data-00000-of-00001
diff --git a/models/batch_norm_model_saved_model/variables/variables.index b/models/batch_norm_model_saved_model/variables/variables.index
diff --git a/models/batch_norm_model_sgd.h5 b/models/batch_norm_model_sgd.h5
diff --git a/models/batch_norm_model_sgd.keras b/models/batch_norm_model_sgd.keras
diff --git a/models/batch_norm_model_sgd_saved_model/fingerprint.pb b/models/batch_norm_model_sgd_saved_model/fingerprint.pb
@@ -0,0 +1 @@
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diff --git a/models/batch_norm_model_sgd_saved_model/saved_model.pb b/models/batch_norm_model_sgd_saved_model/saved_model.pb
diff --git a/models/batch_norm_model_sgd_saved_model/variables/variables.data-00000-of-00001 b/models/batch_norm_model_sgd_saved_model/variables/variables.data-00000-of-00001
diff --git a/models/batch_norm_model_sgd_saved_model/variables/variables.index b/models/batch_norm_model_sgd_saved_model/variables/variables.index
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