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ai_sdk/3rd/win/mnn/include/MNN/ImageProcess.hpp
2025-01-18 21:11:17 +08:00

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C++

//
// ImageProcess.hpp
// MNN
//
// Created by MNN on 2018/09/19.
// Copyright © 2018, Alibaba Group Holding Limited
//
#ifndef ImageProcess_hpp
#define ImageProcess_hpp
#include <MNN/ErrorCode.hpp>
#include <MNN/Matrix.h>
#include <MNN/Tensor.hpp>
namespace MNN {
namespace CV {
enum ImageFormat {
RGBA = 0,
RGB,
BGR,
GRAY,
BGRA,
YUV_NV21 = 11,
YUV_NV12 = 12,
YUV_I420 = 13,
};
enum Filter { NEAREST = 0, BILINEAR = 1, BICUBIC = 2 };
enum Wrap { CLAMP_TO_EDGE = 0, ZERO = 1, REPEAT = 2 };
/**
* handle image process for tensor.
* step:
* 1: Do transform compute and get points
* 2: Sample line and do format convert
* 3: Turn RGBA to float tensor, and do sub and normalize
*/
class MNN_PUBLIC ImageProcess {
public:
struct Inside;
struct Config {
/** data filter */
Filter filterType = NEAREST;
/** format of source data */
ImageFormat sourceFormat = RGBA;
/** format of destination data */
ImageFormat destFormat = RGBA;
// Only valid if the dest type is float
float mean[4] = {0.0f, 0.0f, 0.0f, 0.0f};
float normal[4] = {1.0f, 1.0f, 1.0f, 1.0f};
/** edge wrapper */
Wrap wrap = CLAMP_TO_EDGE;
};
public:
/**
* @brief create image process with given config for given tensor.
* @param config given config.
* @param dstTensor given tensor.
* @return image processor.
*/
static ImageProcess* create(const Config& config, const Tensor* dstTensor = nullptr);
/**
* @brief create image process with given config for given tensor.
* @param means given means
* @param meanCount given means count
* @param normals given normals
* @param normalCount given normal count
* @param sourceFormat format of source data
* @param destFormat format of destination data
* @param dstTensor given tensor.
* @return image processor.
*/
static ImageProcess* create(const ImageFormat sourceFormat = RGBA, const ImageFormat destFormat = RGBA,
const float* means = nullptr, const int meanCount = 0, const float* normals = nullptr,
const int normalCount = 0, const Tensor* dstTensor = nullptr);
~ImageProcess();
/**
* @brief get affine transform matrix.
* @return affine transform matrix.
*/
inline const Matrix& matrix() const {
return mTransform;
}
void setMatrix(const Matrix& matrix);
/**
* @brief convert source data to given tensor.
* @param source source data.
* @param iw source width.
* @param ih source height.
* @param stride number of elements per row. eg: 100 width RGB contains at least 300 elements.
* @param dest given tensor.
* @return result code.
*/
ErrorCode convert(const uint8_t* source, int iw, int ih, int stride, Tensor* dest);
/**
* @brief convert source data to given tensor.
* @param source source data.
* @param iw source width.
* @param ih source height.
* @param stride number of elements per row. eg: 100 width RGB contains at least 300 elements.
* @param dest dest data.
* @param ow output width.
* @param oh output height.
* @param outputBpp output bpp, if 0, set as the save and config.destFormat.
* @param outputStride output stride, if 0, set as ow * outputBpp.
* @param type Only support halide_type_of<uint8_t> and halide_type_of<float>.
* @return result code.
*/
ErrorCode convert(const uint8_t* source, int iw, int ih, int stride, void* dest, int ow, int oh, int outputBpp = 0,
int outputStride = 0, halide_type_t type = halide_type_of<float>());
/**
* @brief create tensor with given data.
* @param w image width.
* @param h image height.
* @param bpp bytes per pixel.
* @param p pixel data pointer.
* @return created tensor.
*/
template <typename T>
static Tensor* createImageTensor(int w, int h, int bpp, void* p = nullptr) {
return createImageTensor(halide_type_of<T>(), w, h, bpp, p);
}
static Tensor* createImageTensor(halide_type_t type, int w, int h, int bpp, void* p = nullptr);
private:
ImageProcess(const Config& config);
Matrix mTransform;
Matrix mTransformInvert;
Inside* mInside;
};
} // namespace CV
} // namespace MNN
#endif /* ImageProcess_hpp */