Updating the input image sizes to have a higher resolution. Currently unclean data is reaching 70% accuracy.

ModelTraining/TrainingModelKeras.py

@@ -120,7 +120,6 @@ test_gen = test_idg.flow_from_directory(
 )
 len(test_gen.filenames)
 
-score = model.evaluate_generator(test_gen, workers=1, steps=len(test_gen))
 
 # predicts
 predicts = model.predict_generator(test_gen, verbose=True, workers=1, steps=len(test_gen))
@@ -129,9 +128,6 @@ predicts = model.predict_generator(test_gen, verbose=True, workers=1, steps=len(
 keras_file = 'finished.h5'
 keras.models.save_model(model, keras_file)
 
-print("Loss: ", score[0], "Accuracy: ", score[1])
-print(score)
-
 print(predicts)
 print(type(predicts))
 print(predicts.shape)
@@ -167,3 +163,4 @@ df_cm = pd.DataFrame(conf_mat, index=[i for i in list(set(reals))],
 plt.figure(figsize=(10, 7))
 sn.heatmap(df_cm, annot=True)
 plt.show()
+

ModelTraining/TransferLearningKeras.py

@@ -8,7 +8,7 @@ from PIL import ImageFile
 
 ImageFile.LOAD_TRUNCATED_IMAGES = True
 
-input_shape = (299, 299, 3)
+input_shape = (244, 244, 3)
 
 batch_size = 60
 model_name = "MobileNetV2FullDataset"