da66e64f1eff8b52ae90cccc6f75a75d1af94c50,examples/convolutional_model.py,,,#,3

Before Change

print("Creating training/testing data...")
validation_split = 0.15
X_train, X_test, y_train, y_test = train_test_split(image_data, labels,
                                                    test_size=validation_split, random_state=42, stratify=labels)


train_gen = DataGenerator().fit(X_train, y_train)
test_gen = DataGenerator().fit(X_test, y_test)

After Change

image_data = list()

for image in image_array:
    image_data.append(np.array([image]).reshape((target_dimensions[0], target_dimensions[1], 1)))
image_data = np.array(image_data)
if verbose:
    print("Processed image data shape: " + str(image_data.shape))

Instances