def __call__(self, handler):
for data in self.iter(handler):
for name in self.shape_dict.keys():
assert isinstance(data[name], np.ndarray)
t, n, h, w, c = data[name].shape
crop_h, crop_w = self.shape_dict[name]
max_r = h - crop_h
max_c = w - crop_w
row_indices = self.rnd.random_integers(0, max_r, n)
col_indices = self.rnd.random_integers(0, max_c, n)
cropped = np.zeros((t, n, crop_h, crop_w, c))
_crop_images(data[name], crop_h, crop_w, row_indices,
col_indices, cropped)
data[name] = cropped
yield data
def __call__(self, handler):
for data in self.iter(handler):
for name in self.shape_dict.keys():
assert isinstance(data[name], np.ndarray)
t, n, h, w, c = data[name].shape
crop_h, crop_w = self.shape_dict[name]
max_r = h - crop_h
max_c = w - crop_w
row_indices = self.rnd.random_integers(0, max_r, n)
col_indices = self.rnd.random_integers(0, max_c, n)
cropped = np.zeros((t, n, crop_h, crop_w, c))
_crop_images(data[name], crop_h, crop_w, row_indices,
col_indices, cropped)
data[name] = cropped
yield data
def test_crop_images_operation():
a = np.random.randn(3, 2, 5, 5, 4)
out = np.zeros((3, 2, 3, 3, 4))
_crop_images(a, 3, 3, np.array([0, 1]), np.array([0, 2]), out)
assert np.allclose(out[:, 0, ...], a[:, 0, 0:3, 0:3, :])
assert np.allclose(out[:, 1, ...], a[:, 1, 1:4, 2:5, :])
def test_crop_images_operation():
a = np.random.randn(3, 2, 5, 5, 4)
out = np.zeros((3, 2, 3, 3, 4))
_crop_images(a, 3, 3, np.array([0, 1]), np.array([0, 2]), out)
assert np.allclose(out[:, 0, ...], a[:, 0, 0:3, 0:3, :])
assert np.allclose(out[:, 1, ...], a[:, 1, 1:4, 2:5, :])