C++ API: Reorder transforms.h alphabetically
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@ -46,59 +46,21 @@ class TensorOperation : public std::enable_shared_from_this<TensorOperation> {
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// Transform operations for performing computer vision.
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namespace vision {
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class NormalizeOperation;
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class DecodeOperation;
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class ResizeOperation;
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class RandomCropOperation;
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// Transform Op classes (in alphabetical order)
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class CenterCropOperation;
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class UniformAugOperation;
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class RandomHorizontalFlipOperation;
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class RandomVerticalFlipOperation;
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class RandomRotationOperation;
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class PadOperation;
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class CutOutOperation;
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class RandomColorAdjustOperation;
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class CropOperation;
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class CutOutOperation;
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class DecodeOperation;
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class NormalizeOperation;
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class PadOperation;
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class RandomColorAdjustOperation;
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class RandomCropOperation;
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class RandomHorizontalFlipOperation;
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class RandomRotationOperation;
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class RandomVerticalFlipOperation;
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class ResizeOperation;
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class SwapRedBlueOperation;
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/// \brief Function to create a Normalize TensorOperation.
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/// \notes Normalize the input image with respect to mean and standard deviation.
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/// \param[in] mean - a vector of mean values for each channel, w.r.t channel order.
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/// \param[in] std - a vector of standard deviations for each channel, w.r.t. channel order.
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/// \return Shared pointer to the current TensorOperation.
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std::shared_ptr<NormalizeOperation> Normalize(std::vector<float> mean, std::vector<float> std);
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/// \brief Function to create a Decode TensorOperation.
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/// \notes Decode the input image in RGB mode.
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/// \param[in] rgb - a boolean of whether to decode in RGB mode or not.
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/// \return Shared pointer to the current TensorOperation.
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std::shared_ptr<DecodeOperation> Decode(bool rgb = true);
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/// \brief Function to create a Resize TensorOperation.
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/// \notes Resize the input image to the given size..
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/// \param[in] size - a vector representing the output size of the resized image.
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/// If size is a single value, the image will be resized to this value with
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/// the same image aspect ratio. If size has 2 values, it should be (height, width).
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/// \param[in] interpolation An enum for the mode of interpolation
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/// \return Shared pointer to the current TensorOperation.
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std::shared_ptr<ResizeOperation> Resize(std::vector<int32_t> size,
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InterpolationMode interpolation = InterpolationMode::kLinear);
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/// \brief Function to create a RandomCrop TensorOperation.
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/// \notes Crop the input image at a random location.
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/// \param[in] size - a vector representing the output size of the cropped image.
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/// If size is a single value, a square crop of size (size, size) is returned.
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/// If size has 2 values, it should be (height, width).
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/// \param[in] padding - a vector with the value of pixels to pad the image. If 4 values are provided,
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/// it pads the left, top, right and bottom respectively.
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/// \param[in] pad_if_needed - a boolean whether to pad the image if either side is smaller than
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/// the given output size.
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/// \param[in] fill_value - a vector representing the pixel intensity of the borders, it is used to
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/// fill R, G, B channels respectively.
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/// \return Shared pointer to the current TensorOperation.
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std::shared_ptr<RandomCropOperation> RandomCrop(std::vector<int32_t> size, std::vector<int32_t> padding = {0, 0, 0, 0},
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bool pad_if_needed = false,
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std::vector<uint8_t> fill_value = {0, 0, 0});
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class UniformAugOperation;
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/// \brief Function to create a CenterCrop TensorOperation.
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/// \notes Crops the input image at the center to the given size.
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@ -108,37 +70,32 @@ std::shared_ptr<RandomCropOperation> RandomCrop(std::vector<int32_t> size, std::
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/// \return Shared pointer to the current TensorOperation.
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std::shared_ptr<CenterCropOperation> CenterCrop(std::vector<int32_t> size);
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/// \brief Function to create a UniformAugment TensorOperation.
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/// \notes Tensor operation to perform randomly selected augmentation.
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/// \param[in] transforms - a vector of TensorOperation transforms.
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/// \param[in] num_ops - integer representing the number of OPs to be selected and applied.
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/// \return Shared pointer to the current TensorOperation.
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std::shared_ptr<UniformAugOperation> UniformAugment(std::vector<std::shared_ptr<TensorOperation>> transforms,
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int32_t num_ops = 2);
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/// \brief Function to create a RandomHorizontalFlip TensorOperation.
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/// \notes Tensor operation to perform random horizontal flip.
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/// \param[in] prob - float representing the probability of flip.
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/// \return Shared pointer to the current TensorOperation.
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std::shared_ptr<RandomHorizontalFlipOperation> RandomHorizontalFlip(float prob = 0.5);
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/// \brief Function to create a RandomVerticalFlip TensorOperation.
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/// \notes Tensor operation to perform random vertical flip.
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/// \param[in] prob - float representing the probability of flip.
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/// \return Shared pointer to the current TensorOperation.
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std::shared_ptr<RandomVerticalFlipOperation> RandomVerticalFlip(float prob = 0.5);
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/// \brief Function to create a RandomRotation TensorOp
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/// \notes Rotates the image according to parameters
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/// \param[in] degrees A float vector size 2, representing the starting and ending degree
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/// \param[in] resample An enum for the mode of interpolation
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/// \param[in] expand A boolean representing whether the image is expanded after rotation
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/// \param[in] center A float vector size 2, representing the x and y center of rotation.
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/// \param[in] fill_value A uint8_t vector size 3, representing the rgb value of the fill color
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/// \brief Function to create a Crop TensorOp
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/// \notes Crop an image based on location and crop size
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/// \param[in] coordinates Starting location of crop. Must be a vector of two values, in the form of {x_coor, y_coor}
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/// \param[in] size Size of the cropped area. Must be a vector of two values, in the form of {height, width}
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/// \return Shared pointer to the current TensorOp
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std::shared_ptr<RandomRotationOperation> RandomRotation(
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std::vector<float> degrees, InterpolationMode resample = InterpolationMode::kNearestNeighbour, bool expand = false,
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std::vector<float> center = {-1, -1}, std::vector<uint8_t> fill_value = {0, 0, 0});
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std::shared_ptr<CropOperation> Crop(std::vector<int32_t> coordinates, std::vector<int32_t> size);
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/// \brief Function to create a CutOut TensorOp
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/// \notes Randomly cut (mask) out a given number of square patches from the input image
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/// \param[in] length Integer representing the side length of each square patch
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/// \param[in] num_patches Integer representing the number of patches to be cut out of an image
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/// \return Shared pointer to the current TensorOp
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std::shared_ptr<CutOutOperation> CutOut(int32_t length, int32_t num_patches = 1);
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/// \brief Function to create a Decode TensorOperation.
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/// \notes Decode the input image in RGB mode.
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/// \param[in] rgb - a boolean of whether to decode in RGB mode or not.
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/// \return Shared pointer to the current TensorOperation.
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std::shared_ptr<DecodeOperation> Decode(bool rgb = true);
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/// \brief Function to create a Normalize TensorOperation.
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/// \notes Normalize the input image with respect to mean and standard deviation.
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/// \param[in] mean - a vector of mean values for each channel, w.r.t channel order.
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/// \param[in] std - a vector of standard deviations for each channel, w.r.t. channel order.
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/// \return Shared pointer to the current TensorOperation.
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std::shared_ptr<NormalizeOperation> Normalize(std::vector<float> mean, std::vector<float> std);
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/// \brief Function to create a Pad TensorOp
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/// \notes Pads the image according to padding parameters
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@ -162,13 +119,6 @@ std::shared_ptr<RandomRotationOperation> RandomRotation(
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std::shared_ptr<PadOperation> Pad(std::vector<int32_t> padding, std::vector<uint8_t> fill_value = {0},
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BorderType padding_mode = BorderType::kConstant);
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/// \brief Function to create a CutOut TensorOp
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/// \notes Randomly cut (mask) out a given number of square patches from the input image
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/// \param[in] length Integer representing the side length of each square patch
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/// \param[in] num_patches Integer representing the number of patches to be cut out of an image
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/// \return Shared pointer to the current TensorOp
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std::shared_ptr<CutOutOperation> CutOut(int32_t length, int32_t num_patches = 1);
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/// \brief Randomly adjust the brightness, contrast, saturation, and hue of the input image
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/// \param[in] brightness Brightness adjustment factor. Must be a vector of one or two values
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/// if it's a vector of two values it needs to be in the form of [min, max]. Default value is {1, 1}
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@ -185,33 +135,113 @@ std::shared_ptr<RandomColorAdjustOperation> RandomColorAdjust(std::vector<float>
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std::vector<float> saturation = {1.0, 1.0},
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std::vector<float> hue = {0.0, 0.0});
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/// \brief Function to create a Crop TensorOp
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/// \notes Crop an image based on location and crop size
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/// \param[in] coordinates Starting location of crop. Must be a vector of two values, in the form of {x_coor, y_coor}
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/// \param[in] size Size of the cropped area. Must be a vector of two values, in the form of {height, width}
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/// \brief Function to create a RandomCrop TensorOperation.
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/// \notes Crop the input image at a random location.
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/// \param[in] size - a vector representing the output size of the cropped image.
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/// If size is a single value, a square crop of size (size, size) is returned.
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/// If size has 2 values, it should be (height, width).
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/// \param[in] padding - a vector with the value of pixels to pad the image. If 4 values are provided,
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/// it pads the left, top, right and bottom respectively.
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/// \param[in] pad_if_needed - a boolean whether to pad the image if either side is smaller than
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/// the given output size.
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/// \param[in] fill_value - a vector representing the pixel intensity of the borders, it is used to
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/// fill R, G, B channels respectively.
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/// \return Shared pointer to the current TensorOperation.
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std::shared_ptr<RandomCropOperation> RandomCrop(std::vector<int32_t> size, std::vector<int32_t> padding = {0, 0, 0, 0},
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bool pad_if_needed = false,
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std::vector<uint8_t> fill_value = {0, 0, 0});
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/// \brief Function to create a RandomHorizontalFlip TensorOperation.
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/// \notes Tensor operation to perform random horizontal flip.
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/// \param[in] prob - float representing the probability of flip.
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/// \return Shared pointer to the current TensorOperation.
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std::shared_ptr<RandomHorizontalFlipOperation> RandomHorizontalFlip(float prob = 0.5);
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/// \brief Function to create a RandomRotation TensorOp
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/// \notes Rotates the image according to parameters
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/// \param[in] degrees A float vector size 2, representing the starting and ending degree
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/// \param[in] resample An enum for the mode of interpolation
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/// \param[in] expand A boolean representing whether the image is expanded after rotation
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/// \param[in] center A float vector size 2, representing the x and y center of rotation.
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/// \param[in] fill_value A uint8_t vector size 3, representing the rgb value of the fill color
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/// \return Shared pointer to the current TensorOp
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std::shared_ptr<CropOperation> Crop(std::vector<int32_t> coordinates, std::vector<int32_t> size);
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std::shared_ptr<RandomRotationOperation> RandomRotation(
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std::vector<float> degrees, InterpolationMode resample = InterpolationMode::kNearestNeighbour, bool expand = false,
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std::vector<float> center = {-1, -1}, std::vector<uint8_t> fill_value = {0, 0, 0});
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/// \brief Function to create a RandomVerticalFlip TensorOperation.
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/// \notes Tensor operation to perform random vertical flip.
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/// \param[in] prob - float representing the probability of flip.
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/// \return Shared pointer to the current TensorOperation.
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std::shared_ptr<RandomVerticalFlipOperation> RandomVerticalFlip(float prob = 0.5);
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/// \brief Function to create a Resize TensorOperation.
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/// \notes Resize the input image to the given size..
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/// \param[in] size - a vector representing the output size of the resized image.
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/// If size is a single value, the image will be resized to this value with
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/// the same image aspect ratio. If size has 2 values, it should be (height, width).
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/// \param[in] interpolation An enum for the mode of interpolation
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/// \return Shared pointer to the current TensorOperation.
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std::shared_ptr<ResizeOperation> Resize(std::vector<int32_t> size,
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InterpolationMode interpolation = InterpolationMode::kLinear);
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/// \brief Function to create a SwapRedBlue TensorOp
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/// \notes Swaps the red and blue channels in image
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/// \return Shared pointer to the current TensorOp
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std::shared_ptr<SwapRedBlueOperation> SwapRedBlue();
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/// \brief Function to create a UniformAugment TensorOperation.
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/// \notes Tensor operation to perform randomly selected augmentation.
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/// \param[in] transforms - a vector of TensorOperation transforms.
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/// \param[in] num_ops - integer representing the number of OPs to be selected and applied.
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/// \return Shared pointer to the current TensorOperation.
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std::shared_ptr<UniformAugOperation> UniformAugment(std::vector<std::shared_ptr<TensorOperation>> transforms,
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int32_t num_ops = 2);
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/* ####################################### Derived TensorOperation classes ################################# */
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class NormalizeOperation : public TensorOperation {
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class CenterCropOperation : public TensorOperation {
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public:
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NormalizeOperation(std::vector<float> mean, std::vector<float> std);
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explicit CenterCropOperation(std::vector<int32_t> size);
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~NormalizeOperation() = default;
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~CenterCropOperation() = default;
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std::shared_ptr<TensorOp> Build() override;
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bool ValidateParams() override;
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private:
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std::vector<float> mean_;
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std::vector<float> std_;
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std::vector<int32_t> size_;
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};
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class CropOperation : public TensorOperation {
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public:
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CropOperation(std::vector<int32_t> coordinates, std::vector<int32_t> size);
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~CropOperation() = default;
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std::shared_ptr<TensorOp> Build() override;
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bool ValidateParams() override;
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private:
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std::vector<int32_t> coordinates_;
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std::vector<int32_t> size_;
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};
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class CutOutOperation : public TensorOperation {
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public:
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explicit CutOutOperation(int32_t length, int32_t num_patches = 1);
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~CutOutOperation() = default;
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std::shared_ptr<TensorOp> Build() override;
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bool ValidateParams() override;
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private:
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int32_t length_;
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int32_t num_patches_;
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};
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class DecodeOperation : public TensorOperation {
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@ -228,20 +258,54 @@ class DecodeOperation : public TensorOperation {
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bool rgb_;
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};
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class ResizeOperation : public TensorOperation {
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class NormalizeOperation : public TensorOperation {
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public:
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explicit ResizeOperation(std::vector<int32_t> size,
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InterpolationMode interpolation_mode = InterpolationMode::kLinear);
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NormalizeOperation(std::vector<float> mean, std::vector<float> std);
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~ResizeOperation() = default;
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~NormalizeOperation() = default;
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std::shared_ptr<TensorOp> Build() override;
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bool ValidateParams() override;
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private:
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std::vector<int32_t> size_;
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InterpolationMode interpolation_;
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std::vector<float> mean_;
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std::vector<float> std_;
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};
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class PadOperation : public TensorOperation {
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public:
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PadOperation(std::vector<int32_t> padding, std::vector<uint8_t> fill_value = {0},
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BorderType padding_mode = BorderType::kConstant);
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~PadOperation() = default;
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std::shared_ptr<TensorOp> Build() override;
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bool ValidateParams() override;
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private:
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std::vector<int32_t> padding_;
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std::vector<uint8_t> fill_value_;
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BorderType padding_mode_;
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};
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class RandomColorAdjustOperation : public TensorOperation {
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public:
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RandomColorAdjustOperation(std::vector<float> brightness = {1.0, 1.0}, std::vector<float> contrast = {1.0, 1.0},
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std::vector<float> saturation = {1.0, 1.0}, std::vector<float> hue = {0.0, 0.0});
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~RandomColorAdjustOperation() = default;
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std::shared_ptr<TensorOp> Build() override;
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bool ValidateParams() override;
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private:
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std::vector<float> brightness_;
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std::vector<float> contrast_;
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std::vector<float> saturation_;
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std::vector<float> hue_;
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};
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class RandomCropOperation : public TensorOperation {
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std::vector<uint8_t> fill_value_;
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};
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class CenterCropOperation : public TensorOperation {
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public:
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explicit CenterCropOperation(std::vector<int32_t> size);
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~CenterCropOperation() = default;
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std::shared_ptr<TensorOp> Build() override;
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bool ValidateParams() override;
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private:
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std::vector<int32_t> size_;
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};
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class UniformAugOperation : public TensorOperation {
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public:
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explicit UniformAugOperation(std::vector<std::shared_ptr<TensorOperation>> transforms, int32_t num_ops = 2);
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~UniformAugOperation() = default;
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std::shared_ptr<TensorOp> Build() override;
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bool ValidateParams() override;
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private:
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std::vector<std::shared_ptr<TensorOperation>> transforms_;
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int32_t num_ops_;
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};
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class RandomHorizontalFlipOperation : public TensorOperation {
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public:
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explicit RandomHorizontalFlipOperation(float probability = 0.5);
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float probability_;
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};
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class RandomVerticalFlipOperation : public TensorOperation {
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public:
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explicit RandomVerticalFlipOperation(float probability = 0.5);
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~RandomVerticalFlipOperation() = default;
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std::shared_ptr<TensorOp> Build() override;
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bool ValidateParams() override;
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private:
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float probability_;
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};
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class RandomRotationOperation : public TensorOperation {
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public:
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RandomRotationOperation(std::vector<float> degrees, InterpolationMode interpolation_mode, bool expand,
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@ -338,69 +359,49 @@ class RandomRotationOperation : public TensorOperation {
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std::vector<uint8_t> fill_value_;
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};
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class PadOperation : public TensorOperation {
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class RandomVerticalFlipOperation : public TensorOperation {
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public:
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PadOperation(std::vector<int32_t> padding, std::vector<uint8_t> fill_value = {0},
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BorderType padding_mode = BorderType::kConstant);
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explicit RandomVerticalFlipOperation(float probability = 0.5);
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~PadOperation() = default;
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~RandomVerticalFlipOperation() = default;
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std::shared_ptr<TensorOp> Build() override;
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bool ValidateParams() override;
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private:
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std::vector<int32_t> padding_;
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std::vector<uint8_t> fill_value_;
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BorderType padding_mode_;
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float probability_;
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};
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class CutOutOperation : public TensorOperation {
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class ResizeOperation : public TensorOperation {
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public:
|
||||
explicit CutOutOperation(int32_t length, int32_t num_patches = 1);
|
||||
explicit ResizeOperation(std::vector<int32_t> size,
|
||||
InterpolationMode interpolation_mode = InterpolationMode::kLinear);
|
||||
|
||||
~CutOutOperation() = default;
|
||||
~ResizeOperation() = default;
|
||||
|
||||
std::shared_ptr<TensorOp> Build() override;
|
||||
|
||||
bool ValidateParams() override;
|
||||
|
||||
private:
|
||||
int32_t length_;
|
||||
int32_t num_patches_;
|
||||
};
|
||||
|
||||
class RandomColorAdjustOperation : 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});
|
||||
|
||||
~RandomColorAdjustOperation() = 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_;
|
||||
};
|
||||
|
||||
class CropOperation : public TensorOperation {
|
||||
public:
|
||||
CropOperation(std::vector<int32_t> coordinates, std::vector<int32_t> size);
|
||||
|
||||
~CropOperation() = default;
|
||||
|
||||
std::shared_ptr<TensorOp> Build() override;
|
||||
|
||||
bool ValidateParams() override;
|
||||
|
||||
private:
|
||||
std::vector<int32_t> coordinates_;
|
||||
std::vector<int32_t> size_;
|
||||
InterpolationMode interpolation_;
|
||||
};
|
||||
|
||||
class UniformAugOperation : public TensorOperation {
|
||||
public:
|
||||
explicit UniformAugOperation(std::vector<std::shared_ptr<TensorOperation>> transforms, int32_t num_ops = 2);
|
||||
|
||||
~UniformAugOperation() = default;
|
||||
|
||||
std::shared_ptr<TensorOp> Build() override;
|
||||
|
||||
bool ValidateParams() override;
|
||||
|
||||
private:
|
||||
std::vector<std::shared_ptr<TensorOperation>> transforms_;
|
||||
int32_t num_ops_;
|
||||
};
|
||||
|
||||
class SwapRedBlueOperation : public TensorOperation {
|
||||
|
|
Loading…
Reference in New Issue