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!2348 fix image.CenterCrop. 

Merge pull request !2348 from liuxiao/central_crop
This commit is contained in:
mindspore-ci-bot 2020-06-19 17:58:02 +08:00 committed by Gitee
parent 3e299270d6 858f2b59b2
commit c55b81e94f
1 changed files with 8 additions and 7 deletions
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15
mindspore/nn/layer/image.py
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@ -267,11 +267,9 @@ class PSNR(Cell):
@constexpr @constexpr
def _check_input_3d_or_4d(input_shape, param_name, func_name): def _raise_dims_rank_error(input_shape, param_name, func_name):
"""check input 3d or 4d""" """raise error if input is not 3d or 4d"""
if len(input_shape) != 3 and len(input_shape) != 4: raise ValueError(f"{func_name} {param_name} should be 3d or 4d, but got shape {input_shape}")
raise ValueError(f"{func_name} {param_name} should be 3d or 4d, but got shape {input_shape}")
return True
@constexpr @constexpr
def _get_bbox(rank, shape, central_fraction): def _get_bbox(rank, shape, central_fraction):
@ -281,6 +279,7 @@ def _get_bbox(rank, shape, central_fraction):
else: else:
n, c, h, w = shape n, c, h, w = shape
central_fraction = central_fraction.asnumpy()[0]
bbox_h_start = int((float(h) - float(h) * central_fraction) / 2) bbox_h_start = int((float(h) - float(h) * central_fraction) / 2)
bbox_w_start = int((float(w) - float(w) * central_fraction) / 2) bbox_w_start = int((float(w) - float(w) * central_fraction) / 2)
bbox_h_size = h - bbox_h_start * 2 bbox_h_size = h - bbox_h_start * 2
@ -319,16 +318,18 @@ class CentralCrop(Cell):
validator.check_value_type("central_fraction", central_fraction, [float], self.cls_name) validator.check_value_type("central_fraction", central_fraction, [float], self.cls_name)
self.central_fraction = validator.check_number_range('central_fraction', central_fraction, self.central_fraction = validator.check_number_range('central_fraction', central_fraction,
0.0, 1.0, Rel.INC_RIGHT, self.cls_name) 0.0, 1.0, Rel.INC_RIGHT, self.cls_name)
self.central_fraction_tensor = Tensor(np.array([central_fraction]).astype(np.float64))
self.slice = P.Slice() self.slice = P.Slice()
def construct(self, image): def construct(self, image):
image_shape = F.shape(image) image_shape = F.shape(image)
rank = len(image_shape) rank = len(image_shape)
_check_input_3d_or_4d(image_shape, "image", self.cls_name) if not rank in (3, 4):
return _raise_dims_rank_error(image_shape, "image", self.cls_name)
if self.central_fraction == 1.0: if self.central_fraction == 1.0:
return image return image
bbox_begin, bbox_size = _get_bbox(rank, image_shape, self.central_fraction) bbox_begin, bbox_size = _get_bbox(rank, image_shape, self.central_fraction_tensor)
image = self.slice(image, bbox_begin, bbox_size) image = self.slice(image, bbox_begin, bbox_size)
return image return image