def load_training_samples():
""" Load the training samples. """
train_image_path = Settings.get("TRAIN_IMAGE_PATH")
label_path = Settings.get("LABEL_PATH")
data_frame = pandas.read_csv(label_path)
samples: List[Sample] = []
for index, row in data_frame.iterrows():
sample = Sample(image_id=row["Image"], image_dir=train_image_path, label=row["Id"])
samples.append(sample)
return samples
def load_testing_samples():
""" Load the training samples. """
test_image_path = Settings.get("TEST_IMAGE_PATH")
samples: List[Sample] = []
files = os.listdir(test_image_path)
for file_name in files:
if ".jpg" not in file_name and ".png" not in file_name:
continue
sample = Sample(image_id=file_name, image_dir=test_image_path)
samples.append(sample)
return samples
