def create_data_from_image(self ,image_path):
print("Create data patches for model")
dim = self.dim_label
image = self.open_image(image_path)
dp = 2* self.padding
vertical = int((image.shape[0] - dp) / dim)
horizontal = int((image.shape[1] - dp) / dim)
number_of_patches = vertical * horizontal
data = np.empty((number_of_patches, self.dim_data*self.dim_data*3), dtype=theano.config.floatX)
label = np.empty((number_of_patches, dim*dim), dtype=theano.config.floatX)
idx = 0
for i in range(vertical):
for j in range(horizontal):
img_i = i * dim
img_j = j * dim
image_patch = from_rgb_to_arr(image[img_i: img_i + dim + dp, img_j: img_j + dim + dp])
if self.normalize:
image_patch = normalize(image_patch, self.std)
data[idx] = image_patch
idx += 1
aerial = AerialDataset()
return aerial.shared_dataset([data, label], cast_to_int=True), (vertical, horizontal)
def _create_dataset(self, set_name):
dim = (self.dataset_config.input_dim, self.dataset_config.output_dim)
path = self.dataset_path
preprocessing = self.dataset_config.use_preprocessing
print("---- Using preprossing: {}".format(preprocessing))
std = self.dataset_config.dataset_std
samples_per_image = 200
creator = Creator(path, dim=dim, preproccessing=preprocessing, std=std)
creator.load_dataset()
#Creating a shared variable of sampled test data
raw_set = None
if set_name == "valid":
raw_set = creator.valid
else:
raw_set = creator.test
aerial = AerialDataset()
return aerial.shared_dataset(creator.sample_data(raw_set, samples_per_image), cast_to_int=True)
def _create_dataset(self, set_name):
dim = (self.dataset_config.input_dim, self.dataset_config.output_dim)
path = self.dataset_path
preprocessing = self.dataset_config.use_preprocessing
print("---- Using preprossing: {}".format(preprocessing))
std = self.dataset_config.dataset_std
samples_per_image = 200
creator = Creator(path, dim=dim, preproccessing=preprocessing, std=std)
creator.load_dataset()
#Creating a shared variable of sampled test data
raw_set = None
if set_name == "valid":
raw_set = creator.valid
else:
raw_set = creator.test
aerial = AerialDataset()
return aerial.shared_dataset(creator.sample_data(
raw_set, samples_per_image),
cast_to_int=True)