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mindspore
提交 49a1e013 编写于 作者: C Cathy Wong
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C++ API: Reorder transforms.h alphabetically

上级 6f701461
隐藏空白更改
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Showing with 161 addition and 160 deletion
mindspore/ccsrc/minddata/dataset/include/transforms.h
浏览文件 @ 49a1e013
......@@ -46,59 +46,21 @@ class TensorOperation : public std::enable_shared_from_this<TensorOperation> {
// Transform operations for performing computer vision.
namespace vision {
class NormalizeOperation;
// Transform Op classes (in alphabetical order)
class CenterCropOperation;
class CropOperation;
class CutOutOperation;
class DecodeOperation;
class ResizeOperation;
class NormalizeOperation;
class PadOperation;
class RandomColorAdjustOperation;
class RandomCropOperation;
class CenterCropOperation;
class UniformAugOperation;
class RandomHorizontalFlipOperation;
class RandomVerticalFlipOperation;
class RandomRotationOperation;
class PadOperation;
class CutOutOperation;
class RandomColorAdjustOperation;
class CropOperation;
class RandomVerticalFlipOperation;
class ResizeOperation;
class SwapRedBlueOperation;
/// \brief Function to create a Normalize TensorOperation.
/// \notes Normalize the input image with respect to mean and standard deviation.
/// \param[in] mean - a vector of mean values for each channel, w.r.t channel order.
/// \param[in] std - a vector of standard deviations for each channel, w.r.t. channel order.
/// \return Shared pointer to the current TensorOperation.
std::shared_ptr<NormalizeOperation> Normalize(std::vector<float> mean, std::vector<float> std);
/// \brief Function to create a Decode TensorOperation.
/// \notes Decode the input image in RGB mode.
/// \param[in] rgb - a boolean of whether to decode in RGB mode or not.
/// \return Shared pointer to the current TensorOperation.
std::shared_ptr<DecodeOperation> Decode(bool rgb = true);
/// \brief Function to create a Resize TensorOperation.
/// \notes Resize the input image to the given size..
/// \param[in] size - a vector representing the output size of the resized image.
/// If size is a single value, the image will be resized to this value with
/// the same image aspect ratio. If size has 2 values, it should be (height, width).
/// \param[in] interpolation An enum for the mode of interpolation
/// \return Shared pointer to the current TensorOperation.
std::shared_ptr<ResizeOperation> Resize(std::vector<int32_t> size,
InterpolationMode interpolation = InterpolationMode::kLinear);
/// \brief Function to create a RandomCrop TensorOperation.
/// \notes Crop the input image at a random location.
/// \param[in] size - a vector representing the output size of the cropped image.
/// If size is a single value, a square crop of size (size, size) is returned.
/// If size has 2 values, it should be (height, width).
/// \param[in] padding - a vector with the value of pixels to pad the image. If 4 values are provided,
/// it pads the left, top, right and bottom respectively.
/// \param[in] pad_if_needed - a boolean whether to pad the image if either side is smaller than
/// the given output size.
/// \param[in] fill_value - a vector representing the pixel intensity of the borders, it is used to
/// fill R, G, B channels respectively.
/// \return Shared pointer to the current TensorOperation.
std::shared_ptr<RandomCropOperation> RandomCrop(std::vector<int32_t> size, std::vector<int32_t> padding = {0, 0, 0, 0},
bool pad_if_needed = false,
std::vector<uint8_t> fill_value = {0, 0, 0});
class UniformAugOperation;
/// \brief Function to create a CenterCrop TensorOperation.
/// \notes Crops the input image at the center to the given size.
......@@ -108,37 +70,32 @@ std::shared_ptr<RandomCropOperation> RandomCrop(std::vector<int32_t> size, std::
/// \return Shared pointer to the current TensorOperation.
std::shared_ptr<CenterCropOperation> CenterCrop(std::vector<int32_t> size);
/// \brief Function to create a UniformAugment TensorOperation.
/// \notes Tensor operation to perform randomly selected augmentation.
/// \param[in] transforms - a vector of TensorOperation transforms.
/// \param[in] num_ops - integer representing the number of OPs to be selected and applied.
/// \return Shared pointer to the current TensorOperation.
std::shared_ptr<UniformAugOperation> UniformAugment(std::vector<std::shared_ptr<TensorOperation>> transforms,
int32_t num_ops = 2);
/// \brief Function to create a Crop TensorOp
/// \notes Crop an image based on location and crop size
/// \param[in] coordinates Starting location of crop. Must be a vector of two values, in the form of {x_coor, y_coor}
/// \param[in] size Size of the cropped area. Must be a vector of two values, in the form of {height, width}
/// \return Shared pointer to the current TensorOp
std::shared_ptr<CropOperation> Crop(std::vector<int32_t> coordinates, std::vector<int32_t> size);
/// \brief Function to create a RandomHorizontalFlip TensorOperation.
/// \notes Tensor operation to perform random horizontal flip.
/// \param[in] prob - float representing the probability of flip.
/// \return Shared pointer to the current TensorOperation.
std::shared_ptr<RandomHorizontalFlipOperation> RandomHorizontalFlip(float prob = 0.5);
/// \brief Function to create a CutOut TensorOp
/// \notes Randomly cut (mask) out a given number of square patches from the input image
/// \param[in] length Integer representing the side length of each square patch
/// \param[in] num_patches Integer representing the number of patches to be cut out of an image
/// \return Shared pointer to the current TensorOp
std::shared_ptr<CutOutOperation> CutOut(int32_t length, int32_t num_patches = 1);
/// \brief Function to create a RandomVerticalFlip TensorOperation.
/// \notes Tensor operation to perform random vertical flip.
/// \param[in] prob - float representing the probability of flip.
/// \brief Function to create a Decode TensorOperation.
/// \notes Decode the input image in RGB mode.
/// \param[in] rgb - a boolean of whether to decode in RGB mode or not.
/// \return Shared pointer to the current TensorOperation.
std::shared_ptr<RandomVerticalFlipOperation> RandomVerticalFlip(float prob = 0.5);
std::shared_ptr<DecodeOperation> Decode(bool rgb = true);
/// \brief Function to create a RandomRotation TensorOp
/// \notes Rotates the image according to parameters
/// \param[in] degrees A float vector size 2, representing the starting and ending degree
/// \param[in] resample An enum for the mode of interpolation
/// \param[in] expand A boolean representing whether the image is expanded after rotation
/// \param[in] center A float vector size 2, representing the x and y center of rotation.
/// \param[in] fill_value A uint8_t vector size 3, representing the rgb value of the fill color
/// \return Shared pointer to the current TensorOp
std::shared_ptr<RandomRotationOperation> RandomRotation(
std::vector<float> degrees, InterpolationMode resample = InterpolationMode::kNearestNeighbour, bool expand = false,
std::vector<float> center = {-1, -1}, std::vector<uint8_t> fill_value = {0, 0, 0});
/// \brief Function to create a Normalize TensorOperation.
/// \notes Normalize the input image with respect to mean and standard deviation.
/// \param[in] mean - a vector of mean values for each channel, w.r.t channel order.
/// \param[in] std - a vector of standard deviations for each channel, w.r.t. channel order.
/// \return Shared pointer to the current TensorOperation.
std::shared_ptr<NormalizeOperation> Normalize(std::vector<float> mean, std::vector<float> std);
/// \brief Function to create a Pad TensorOp
/// \notes Pads the image according to padding parameters
......@@ -162,13 +119,6 @@ std::shared_ptr<RandomRotationOperation> RandomRotation(
std::shared_ptr<PadOperation> Pad(std::vector<int32_t> padding, std::vector<uint8_t> fill_value = {0},
BorderType padding_mode = BorderType::kConstant);
/// \brief Function to create a CutOut TensorOp
/// \notes Randomly cut (mask) out a given number of square patches from the input image
/// \param[in] length Integer representing the side length of each square patch
/// \param[in] num_patches Integer representing the number of patches to be cut out of an image
/// \return Shared pointer to the current TensorOp
std::shared_ptr<CutOutOperation> CutOut(int32_t length, int32_t num_patches = 1);
/// \brief Randomly adjust the brightness, contrast, saturation, and hue of the input image
/// \param[in] brightness Brightness adjustment factor. Must be a vector of one or two values
/// if it's a vector of two values it needs to be in the form of [min, max]. Default value is {1, 1}
......@@ -185,222 +135,273 @@ std::shared_ptr<RandomColorAdjustOperation> RandomColorAdjust(std::vector<float>
std::vector<float> saturation = {1.0, 1.0},
std::vector<float> hue = {0.0, 0.0});
/// \brief Function to create a Crop TensorOp
/// \notes Crop an image based on location and crop size
/// \param[in] coordinates Starting location of crop. Must be a vector of two values, in the form of {x_coor, y_coor}
/// \param[in] size Size of the cropped area. Must be a vector of two values, in the form of {height, width}
/// \brief Function to create a RandomCrop TensorOperation.
/// \notes Crop the input image at a random location.
/// \param[in] size - a vector representing the output size of the cropped image.
/// If size is a single value, a square crop of size (size, size) is returned.
/// If size has 2 values, it should be (height, width).
/// \param[in] padding - a vector with the value of pixels to pad the image. If 4 values are provided,
/// it pads the left, top, right and bottom respectively.
/// \param[in] pad_if_needed - a boolean whether to pad the image if either side is smaller than
/// the given output size.
/// \param[in] fill_value - a vector representing the pixel intensity of the borders, it is used to
/// fill R, G, B channels respectively.
/// \return Shared pointer to the current TensorOperation.
std::shared_ptr<RandomCropOperation> RandomCrop(std::vector<int32_t> size, std::vector<int32_t> padding = {0, 0, 0, 0},
bool pad_if_needed = false,
std::vector<uint8_t> fill_value = {0, 0, 0});
/// \brief Function to create a RandomHorizontalFlip TensorOperation.
/// \notes Tensor operation to perform random horizontal flip.
/// \param[in] prob - float representing the probability of flip.
/// \return Shared pointer to the current TensorOperation.
std::shared_ptr<RandomHorizontalFlipOperation> RandomHorizontalFlip(float prob = 0.5);
/// \brief Function to create a RandomRotation TensorOp
/// \notes Rotates the image according to parameters
/// \param[in] degrees A float vector size 2, representing the starting and ending degree
/// \param[in] resample An enum for the mode of interpolation
/// \param[in] expand A boolean representing whether the image is expanded after rotation
/// \param[in] center A float vector size 2, representing the x and y center of rotation.
/// \param[in] fill_value A uint8_t vector size 3, representing the rgb value of the fill color
/// \return Shared pointer to the current TensorOp
std::shared_ptr<CropOperation> Crop(std::vector<int32_t> coordinates, std::vector<int32_t> size);
std::shared_ptr<RandomRotationOperation> RandomRotation(
std::vector<float> degrees, InterpolationMode resample = InterpolationMode::kNearestNeighbour, bool expand = false,
std::vector<float> center = {-1, -1}, std::vector<uint8_t> fill_value = {0, 0, 0});
/// \brief Function to create a RandomVerticalFlip TensorOperation.
/// \notes Tensor operation to perform random vertical flip.
/// \param[in] prob - float representing the probability of flip.
/// \return Shared pointer to the current TensorOperation.
std::shared_ptr<RandomVerticalFlipOperation> RandomVerticalFlip(float prob = 0.5);
/// \brief Function to create a Resize TensorOperation.
/// \notes Resize the input image to the given size..
/// \param[in] size - a vector representing the output size of the resized image.
/// If size is a single value, the image will be resized to this value with
/// the same image aspect ratio. If size has 2 values, it should be (height, width).
/// \param[in] interpolation An enum for the mode of interpolation
/// \return Shared pointer to the current TensorOperation.
std::shared_ptr<ResizeOperation> Resize(std::vector<int32_t> size,
InterpolationMode interpolation = InterpolationMode::kLinear);
/// \brief Function to create a SwapRedBlue TensorOp
/// \notes Swaps the red and blue channels in image
/// \return Shared pointer to the current TensorOp
std::shared_ptr<SwapRedBlueOperation> SwapRedBlue();
/// \brief Function to create a UniformAugment TensorOperation.
/// \notes Tensor operation to perform randomly selected augmentation.
/// \param[in] transforms - a vector of TensorOperation transforms.
/// \param[in] num_ops - integer representing the number of OPs to be selected and applied.
/// \return Shared pointer to the current TensorOperation.
std::shared_ptr<UniformAugOperation> UniformAugment(std::vector<std::shared_ptr<TensorOperation>> transforms,
int32_t num_ops = 2);
/* ####################################### Derived TensorOperation classes ################################# */
class NormalizeOperation : public TensorOperation {
class CenterCropOperation : public TensorOperation {
public:
NormalizeOperation(std::vector<float> mean, std::vector<float> std);
explicit CenterCropOperation(std::vector<int32_t> size);
~NormalizeOperation() = default;
~CenterCropOperation() = default;
std::shared_ptr<TensorOp> Build() override;
bool ValidateParams() override;
private:
std::vector<float> mean_;
std::vector<float> std_;
std::vector<int32_t> size_;
};
class DecodeOperation : public TensorOperation {
class CropOperation : public TensorOperation {
public:
explicit DecodeOperation(bool rgb = true);
CropOperation(std::vector<int32_t> coordinates, std::vector<int32_t> size);
~DecodeOperation() = default;
~CropOperation() = default;
std::shared_ptr<TensorOp> Build() override;
bool ValidateParams() override;
private:
bool rgb_;
std::vector<int32_t> coordinates_;
std::vector<int32_t> size_;
};
class ResizeOperation : public TensorOperation {
class CutOutOperation : public TensorOperation {
public:
explicit ResizeOperation(std::vector<int32_t> size,
InterpolationMode interpolation_mode = InterpolationMode::kLinear);
explicit CutOutOperation(int32_t length, int32_t num_patches = 1);
~ResizeOperation() = default;
~CutOutOperation() = default;
std::shared_ptr<TensorOp> Build() override;
bool ValidateParams() override;
private:
std::vector<int32_t> size_;
InterpolationMode interpolation_;
int32_t length_;
int32_t num_patches_;
};
class RandomCropOperation : public TensorOperation {
class DecodeOperation : public TensorOperation {
public:
RandomCropOperation(std::vector<int32_t> size, std::vector<int32_t> padding = {0, 0, 0, 0},
bool pad_if_needed = false, std::vector<uint8_t> fill_value = {0, 0, 0});
explicit DecodeOperation(bool rgb = true);
~RandomCropOperation() = default;
~DecodeOperation() = default;
std::shared_ptr<TensorOp> Build() override;
bool ValidateParams() override;
private:
std::vector<int32_t> size_;
std::vector<int32_t> padding_;
bool pad_if_needed_;
std::vector<uint8_t> fill_value_;
bool rgb_;
};
class CenterCropOperation : public TensorOperation {
class NormalizeOperation : public TensorOperation {
public:
explicit CenterCropOperation(std::vector<int32_t> size);
NormalizeOperation(std::vector<float> mean, std::vector<float> std);
~CenterCropOperation() = default;
~NormalizeOperation() = default;
std::shared_ptr<TensorOp> Build() override;
bool ValidateParams() override;
private:
std::vector<int32_t> size_;
std::vector<float> mean_;
std::vector<float> std_;
};
class UniformAugOperation : public TensorOperation {
class PadOperation : public TensorOperation {
public:
explicit UniformAugOperation(std::vector<std::shared_ptr<TensorOperation>> transforms, int32_t num_ops = 2);
PadOperation(std::vector<int32_t> padding, std::vector<uint8_t> fill_value = {0},
BorderType padding_mode = BorderType::kConstant);
~UniformAugOperation() = default;
~PadOperation() = default;
std::shared_ptr<TensorOp> Build() override;
bool ValidateParams() override;
private:
std::vector<std::shared_ptr<TensorOperation>> transforms_;
int32_t num_ops_;
std::vector<int32_t> padding_;
std::vector<uint8_t> fill_value_;
BorderType padding_mode_;
};
class RandomHorizontalFlipOperation : public TensorOperation {
class RandomColorAdjustOperation : public TensorOperation {
public:
explicit RandomHorizontalFlipOperation(float probability = 0.5);
RandomColorAdjustOperation(std::vector<float> brightness = {1.0, 1.0}, std::vector<float> contrast = {1.0, 1.0},
std::vector<float> saturation = {1.0, 1.0}, std::vector<float> hue = {0.0, 0.0});
~RandomHorizontalFlipOperation() = default;
~RandomColorAdjustOperation() = default;
std::shared_ptr<TensorOp> Build() override;
bool ValidateParams() override;
private:
float probability_;
std::vector<float> brightness_;
std::vector<float> contrast_;
std::vector<float> saturation_;
std::vector<float> hue_;
};
class RandomVerticalFlipOperation : public TensorOperation {
class RandomCropOperation : public TensorOperation {
public:
explicit RandomVerticalFlipOperation(float probability = 0.5);
RandomCropOperation(std::vector<int32_t> size, std::vector<int32_t> padding = {0, 0, 0, 0},
bool pad_if_needed = false, std::vector<uint8_t> fill_value = {0, 0, 0});
~RandomVerticalFlipOperation() = default;
~RandomCropOperation() = default;
std::shared_ptr<TensorOp> Build() override;
bool ValidateParams() override;
private:
float probability_;
std::vector<int32_t> size_;
std::vector<int32_t> padding_;
bool pad_if_needed_;
std::vector<uint8_t> fill_value_;
};
class RandomRotationOperation : public TensorOperation {
class RandomHorizontalFlipOperation : public TensorOperation {
public:
RandomRotationOperation(std::vector<float> degrees, InterpolationMode interpolation_mode, bool expand,
std::vector<float> center, std::vector<uint8_t> fill_value);
explicit RandomHorizontalFlipOperation(float probability = 0.5);
~RandomRotationOperation() = default;
~RandomHorizontalFlipOperation() = default;
std::shared_ptr<TensorOp> Build() override;
bool ValidateParams() override;
private:
std::vector<float> degrees_;
InterpolationMode interpolation_mode_;
std::vector<float> center_;
bool expand_;
std::vector<uint8_t> fill_value_;
float probability_;
};
class PadOperation : public TensorOperation {
class RandomRotationOperation : public TensorOperation {
public:
PadOperation(std::vector<int32_t> padding, std::vector<uint8_t> fill_value = {0},
BorderType padding_mode = BorderType::kConstant);
RandomRotationOperation(std::vector<float> degrees, InterpolationMode interpolation_mode, bool expand,
std::vector<float> center, std::vector<uint8_t> fill_value);
~PadOperation() = default;
~RandomRotationOperation() = default;
std::shared_ptr<TensorOp> Build() override;
bool ValidateParams() override;
private:
std::vector<int32_t> padding_;
std::vector<float> degrees_;
InterpolationMode interpolation_mode_;
std::vector<float> center_;
bool expand_;
std::vector<uint8_t> fill_value_;
BorderType padding_mode_;
};
class CutOutOperation : public TensorOperation {
class RandomVerticalFlipOperation : public TensorOperation {
public:
explicit CutOutOperation(int32_t length, int32_t num_patches = 1);
explicit RandomVerticalFlipOperation(float probability = 0.5);
~CutOutOperation() = default;
~RandomVerticalFlipOperation() = default;
std::shared_ptr<TensorOp> Build() override;
bool ValidateParams() override;
private:
int32_t length_;
int32_t num_patches_;
float probability_;
};
class RandomColorAdjustOperation : public TensorOperation {
class ResizeOperation : public TensorOperation {
public:
RandomColorAdjustOperation(std::vector<float> brightness = {1.0, 1.0}, std::vector<float> contrast = {1.0, 1.0},
std::vector<float> saturation = {1.0, 1.0}, std::vector<float> hue = {0.0, 0.0});
explicit ResizeOperation(std::vector<int32_t> size,
InterpolationMode interpolation_mode = InterpolationMode::kLinear);
~RandomColorAdjustOperation() = default;
~ResizeOperation() = default;
std::shared_ptr<TensorOp> Build() override;
bool ValidateParams() override;
private:
std::vector<float> brightness_;
std::vector<float> contrast_;
std::vector<float> saturation_;
std::vector<float> hue_;
std::vector<int32_t> size_;
InterpolationMode interpolation_;
};
class CropOperation : public TensorOperation {
class UniformAugOperation : public TensorOperation {
public:
CropOperation(std::vector<int32_t> coordinates, std::vector<int32_t> size);
explicit UniformAugOperation(std::vector<std::shared_ptr<TensorOperation>> transforms, int32_t num_ops = 2);
~CropOperation() = default;
~UniformAugOperation() = default;
std::shared_ptr<TensorOp> Build() override;
bool ValidateParams() override;
private:
std::vector<int32_t> coordinates_;
std::vector<int32_t> size_;
std::vector<std::shared_ptr<TensorOperation>> transforms_;
int32_t num_ops_;
};
class SwapRedBlueOperation : public TensorOperation {
......
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