本文整理汇总了Python中tensorflow.space_to_depth函数的典型用法代码示例。如果您正苦于以下问题:Python space_to_depth函数的具体用法?Python space_to_depth怎么用?Python space_to_depth使用的例子?那么恭喜您, 这里精选的函数代码示例或许可以为您提供帮助。
在下文中一共展示了space_to_depth函数的20个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于我们的系统推荐出更棒的Python代码示例。
示例1: testDepthInterleaved
def testDepthInterleaved(self):
x_np = [[[[1, 10], [2, 20]],
[[3, 30], [4, 40]]]]
with self.test_session(use_gpu=False):
block_size = 2
out_tf = tf.space_to_depth(x_np, block_size)
self.assertAllEqual(out_tf.eval(), [[[[1, 10, 2, 20, 3, 30, 4, 40]]]])
开发者ID:CdricGmd,项目名称:tensorflow,代码行数:7,代码来源:spacetodepth_op_test.py
示例2: testBlockSizeNotDivisibleWidth
def testBlockSizeNotDivisibleWidth(self):
# The block size divides width but not height.
x_np = [[[[1], [2], [3]],
[[3], [4], [7]]]]
block_size = 3
with self.assertRaises(IndexError):
_ = tf.space_to_depth(x_np, block_size)
开发者ID:CdricGmd,项目名称:tensorflow,代码行数:7,代码来源:spacetodepth_op_test.py
示例3: testBlockSizeNotDivisibleBoth
def testBlockSizeNotDivisibleBoth(self):
# The block size does not divide neither width or height.
x_np = [[[[1], [2]],
[[3], [4]]]]
block_size = 3
with self.assertRaises(IndexError):
_ = tf.space_to_depth(x_np, block_size)
开发者ID:CdricGmd,项目名称:tensorflow,代码行数:7,代码来源:spacetodepth_op_test.py
示例4: testBasic
def testBasic(self):
x_np = [[[[1], [2]],
[[3], [4]]]]
with self.test_session(use_gpu=False):
block_size = 2
out_tf = tf.space_to_depth(x_np, block_size)
self.assertAllEqual(out_tf.eval(), [[[[1, 2, 3, 4]]]])
开发者ID:CdricGmd,项目名称:tensorflow,代码行数:7,代码来源:spacetodepth_op_test.py
示例5: testInputWrongDimMissingBatch
def testInputWrongDimMissingBatch(self):
# The input is missing the first dimension ("batch")
x_np = [[[1], [2]],
[[3], [4]]]
block_size = 2
with self.assertRaises(ValueError):
_ = tf.space_to_depth(x_np, block_size)
开发者ID:CdricGmd,项目名称:tensorflow,代码行数:7,代码来源:spacetodepth_op_test.py
示例6: testBlockSize0
def testBlockSize0(self):
# The block size is 0.
x_np = [[[[1], [2]],
[[3], [4]]]]
block_size = 0
with self.assertRaises(ValueError):
out_tf = tf.space_to_depth(x_np, block_size)
out_tf.eval()
开发者ID:CdricGmd,项目名称:tensorflow,代码行数:8,代码来源:spacetodepth_op_test.py
示例7: testBlockSizeOne
def testBlockSizeOne(self):
# The block size is 1. The block size needs to be > 1.
x_np = [[[[1], [2]],
[[3], [4]]]]
block_size = 1
with self.assertRaises(ValueError):
out_tf = tf.space_to_depth(x_np, block_size)
out_tf.eval()
开发者ID:CdricGmd,项目名称:tensorflow,代码行数:8,代码来源:spacetodepth_op_test.py
示例8: testBlockSizeLarger
def testBlockSizeLarger(self):
# The block size is too large for this input.
x_np = [[[[1], [2]],
[[3], [4]]]]
block_size = 10
with self.assertRaises(IndexError):
out_tf = tf.space_to_depth(x_np, block_size)
out_tf.eval()
开发者ID:CdricGmd,项目名称:tensorflow,代码行数:8,代码来源:spacetodepth_op_test.py
示例9: testBlockSizeNotDivisibleHeight
def testBlockSizeNotDivisibleHeight(self):
# The block size divides height but not width.
x_np = [[[[1], [2]],
[[3], [4]],
[[5], [6]]]]
block_size = 3
with self.assertRaises(IndexError):
_ = tf.space_to_depth(x_np, block_size)
开发者ID:CdricGmd,项目名称:tensorflow,代码行数:8,代码来源:spacetodepth_op_test.py
示例10: testSpaceToDepthTranspose
def testSpaceToDepthTranspose(self):
x = np.arange(5 * 10 * 16 * 7, dtype=np.float32).reshape([5, 10, 16, 7])
block_size = 2
paddings = np.zeros((2, 2), dtype=np.int32)
y1 = tf.space_to_batch(x, paddings, block_size=block_size)
y2 = tf.transpose(tf.space_to_depth(tf.transpose(x, [3, 1, 2, 0]), block_size=block_size), [3, 1, 2, 0])
with self.test_session():
self.assertAllEqual(y1.eval(), y2.eval())
开发者ID:passiweinberger,项目名称:tensorflow,代码行数:8,代码来源:spacetobatch_op_test.py
示例11: testDepthInterleavedDepth3
def testDepthInterleavedDepth3(self):
x_np = [[[[1, 2, 3], [4, 5, 6]],
[[7, 8, 9], [10, 11, 12]]]]
with self.test_session(use_gpu=False):
block_size = 2
out_tf = tf.space_to_depth(x_np, block_size)
self.assertAllEqual(out_tf.eval(),
[[[[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]]]])
开发者ID:CdricGmd,项目名称:tensorflow,代码行数:8,代码来源:spacetodepth_op_test.py
示例12: testInputWrongDimMissingDepth
def testInputWrongDimMissingDepth(self):
# The input is missing the last dimension ("depth")
x_np = [[[1, 2],
[3, 4]]]
block_size = 2
with self.assertRaises(ValueError):
out_tf = tf.space_to_depth(x_np, block_size)
out_tf.eval()
开发者ID:CdricGmd,项目名称:tensorflow,代码行数:8,代码来源:spacetodepth_op_test.py
示例13: testBlockSizeNotDivisibleDepth
def testBlockSizeNotDivisibleDepth(self):
# The depth is not divisible by the square of the block size.
x_np = [[[[1, 1, 1, 1],
[2, 2, 2, 2]],
[[3, 3, 3, 3],
[4, 4, 4, 4]]]]
block_size = 3
with self.assertRaises(IndexError):
_ = tf.space_to_depth(x_np, block_size)
开发者ID:AdamPalmar,项目名称:tensorflow,代码行数:9,代码来源:depthtospace_op_test.py
示例14: testLargerInput4x4
def testLargerInput4x4(self):
x_np = [[[[1], [2], [5], [6]],
[[3], [4], [7], [8]],
[[9], [10], [13], [14]],
[[11], [12], [15], [16]]]]
with self.test_session(use_gpu=False):
block_size = 4
out_tf = tf.space_to_depth(x_np, block_size)
self.assertAllEqual(
out_tf.eval(),
[[[[1, 2, 5, 6, 3, 4, 7, 8, 9, 10, 13, 14, 11, 12, 15, 16]]]])
开发者ID:CdricGmd,项目名称:tensorflow,代码行数:12,代码来源:spacetodepth_op_test.py
示例15: testDepthInterleavedLarge
def testDepthInterleavedLarge(self):
x_np = [[[[1, 10], [2, 20], [5, 50], [6, 60]],
[[3, 30], [4, 40], [7, 70], [8, 80]],
[[9, 90], [10, 100], [13, 130], [14, 140]],
[[11, 110], [12, 120], [15, 150], [16, 160]]]]
with self.test_session(use_gpu=False):
block_size = 2
out_tf = tf.space_to_depth(x_np, block_size)
self.assertAllEqual(out_tf.eval(),
[[[[1, 10, 2, 20, 3, 30, 4, 40],
[5, 50, 6, 60, 7, 70, 8, 80]],
[[9, 90, 10, 100, 11, 110, 12, 120],
[13, 130, 14, 140, 15, 150, 16, 160]]]])
开发者ID:CdricGmd,项目名称:tensorflow,代码行数:13,代码来源:spacetodepth_op_test.py
示例16: testNonSquare
def testNonSquare(self):
x_np = [[[[1, 10], [2, 20]],
[[3, 30], [4, 40]],
[[5, 50], [6, 60]],
[[7, 70], [8, 80]],
[[9, 90], [10, 100]],
[[11, 110], [12, 120]]]]
with self.test_session(use_gpu=False):
block_size = 2
out_tf = tf.space_to_depth(x_np, block_size)
self.assertAllEqual(out_tf.eval(),
[[[[1, 10, 2, 20, 3, 30, 4, 40]],
[[5, 50, 6, 60, 7, 70, 8, 80]],
[[9, 90, 10, 100, 11, 110, 12, 120]]]])
开发者ID:CdricGmd,项目名称:tensorflow,代码行数:14,代码来源:spacetodepth_op_test.py
示例17: _checkGrad
def _checkGrad(self, x, block_size):
assert 4 == x.ndim
with self.test_session():
tf_x = tf.convert_to_tensor(x)
tf_y = tf.space_to_depth(tf_x, block_size)
epsilon = 1e-2
((x_jacob_t, x_jacob_n)) = tf.test.compute_gradient(
tf_x,
x.shape,
tf_y,
tf_y.get_shape().as_list(),
x_init_value=x,
delta=epsilon)
self.assertAllClose(x_jacob_t, x_jacob_n, rtol=1e-2, atol=epsilon)
开发者ID:CdricGmd,项目名称:tensorflow,代码行数:15,代码来源:spacetodepth_op_test.py
示例18: __call__
def __call__(self, shape, dtype='float32'): # tf needs partition_info=None
shape = list(shape)
if self.scale == 1:
return self.initializer(shape)
new_shape = shape[:3] + [shape[3] // (self.scale ** 2)]
if type(self.initializer) is dict:
self.initializer = initializers.deserialize(self.initializer)
var_x = self.initializer(new_shape, dtype)
var_x = tf.transpose(var_x, perm=[2, 0, 1, 3])
var_x = tf.image.resize_nearest_neighbor(
var_x,
size=(shape[0] * self.scale, shape[1] * self.scale),
align_corners=True)
var_x = tf.space_to_depth(var_x, block_size=self.scale, data_format='NHWC')
var_x = tf.transpose(var_x, perm=[1, 2, 0, 3])
return var_x
开发者ID:stonezuohui,项目名称:faceswap,代码行数:16,代码来源:initializers.py
示例19: icnr_keras
def icnr_keras(shape, dtype=None):
"""
Custom initializer for subpix upscaling
From https://github.com/kostyaev/ICNR
Note: upscale factor is fixed to 2, and the base initializer is fixed to random normal.
"""
# TODO Roll this into ICNR_init when porting GAN 2.2
shape = list(shape)
scale = 2
initializer = tf.keras.initializers.RandomNormal(0, 0.02)
new_shape = shape[:3] + [int(shape[3] / (scale ** 2))]
var_x = initializer(new_shape, dtype)
var_x = tf.transpose(var_x, perm=[2, 0, 1, 3])
var_x = tf.image.resize_nearest_neighbor(var_x, size=(shape[0] * scale, shape[1] * scale))
var_x = tf.space_to_depth(var_x, block_size=scale)
var_x = tf.transpose(var_x, perm=[1, 2, 0, 3])
return var_x
开发者ID:stonezuohui,项目名称:faceswap,代码行数:18,代码来源:initializers.py
示例20: read_and_batchify_image
def read_and_batchify_image(image_path, shape, image_type="jpg"):
"""Return the original image as read from image_path and the image splitted as a batch tensor.
Args:
image_path: image path
shape: batch shape, like: [no_patches_per_side**2, patch_side, patch_side, 3]
image_type: image type
Returns:
original_image, patches
where original image is a tensor in the format [widht, height 3]
and patches is a tensor of processed images, ready to be classified, with size
[batch_size, w, h, 3]"""
original_image = read_image(image_path, 3, image_type)
# extract values from shape
patch_side = shape[1]
no_patches_per_side = int(math.sqrt(shape[0]))
resized_input_side = patch_side * no_patches_per_side
resized_image = resize_bl(original_image, resized_input_side)
resized_image = tf.expand_dims(resized_image, 0)
patches = tf.space_to_depth(resized_image, patch_side)
print(patches)
patches = tf.squeeze(patches, [0]) #4,4,192*192*3
print(patches)
patches = tf.reshape(patches,
[no_patches_per_side**2, patch_side, patch_side, 3])
print(patches)
patches_a = tf.split(0, no_patches_per_side**2, patches)
print(patches_a)
normalized_patches = []
for patch in patches_a:
patch_as_input_image = zm_mp(
tf.reshape(tf.squeeze(patch, [0]), [patch_side, patch_side, 3]))
print(patch_as_input_image)
normalized_patches.append(patch_as_input_image)
# the last patch is not a "patch" but the whole image resized to patch_side² x 3
# to give a glance to the whole image, in parallel with the patch analysis
normalized_patches.append(zm_mp(resize_bl(original_image, patch_side)))
batch_of_patches = tf.pack(normalized_patches)
return tf.image.convert_image_dtype(original_image,
tf.uint8), batch_of_patches
开发者ID:galeone,项目名称:pgnet,代码行数:44,代码来源:image_processing.py
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