def load_dataset_in_memory_and_resize(data_access, set, division, dataset_path, targets_path, tmp_size,
final_size, batch_size):
if data_access == "in-memory":
with timer("Loading %s data"%set):
dataset = InMemoryDataset(set, dataset_path, source_targets=targets_path, division=division)
draw_data = np.copy(dataset.dataset)
targets = np.copy(dataset.targets)
del dataset
elif data_access == "fuel":
with timer("Loading %s data"%set):
dataset = FuelDataset(set, tmp_size, batch_size=batch_size, shuffle=False, division=division)
draw_data,targets = dataset.return_whole_dataset()
del dataset
else:
raise Exception("Data access not available. Must be 'fuel' or 'in-memory'. Here : %s."%data_access)
if tmp_size != final_size:
# Resize images from the validset
out = np.zeros((draw_data.shape[0], final_size[0], final_size[1], final_size[2]), dtype="float32")
with timer("Resizing %s images"%set):
for i in range(draw_data.shape[0]):
out[i] = resize_pil(draw_data[i], final_size[0:2])
del draw_data
return out, targets
else:
return draw_data, targets
