#ifndef PREPROCESS_KERNEL_CUH

#define PREPROCESS_KERNEL_CUH

#include "cuda_tools.hpp"

namespace CUDAKernel{

enum class NormType : int{

None = 0,

MeanStd = 1,

AlphaBeta = 2

};

enum class ChannelType : int{

None = 0,

Invert = 1

};

struct Norm{

float mean[3];

float std[3];

float alpha, beta;

NormType type = NormType::None;

ChannelType channel_type = ChannelType::None;

// out = (x * alpha - mean) / std

static Norm mean_std(const float mean[3], const float std[3], float alpha = 1/255.0f, ChannelType channel_type=ChannelType::None);

// out = x * alpha + beta

static Norm alpha_beta(float alpha, float beta = 0, ChannelType channel_type=ChannelType::None);

// None

static Norm None();

};

void warp_affine_bilinear_and_normalize_plane(

uint8_t* src, int src_line_size, int src_width, int src_height,

float* dst , int dst_width, int dst_height,

float* matrix_2_3, uint8_t const_value, const Norm& norm,

cudaStream_t stream);

void warp_affine_bilinear_and_normalize_focus(

uint8_t* src, int src_line_size, int src_width, int src_height,

float* dst , int dst_width, int dst_height,

float* matrix_2_3, uint8_t const_value, const Norm& norm,

cudaStream_t stream);

void resize_bilinear_and_normalize(

uint8_t* src, int src_line_size, int src_width, int src_height, float* dst, int dst_width, int dst_height,

uint8_t const_value, const Norm& norm,

cudaStream_t stream);

void norm_feature(

float* feature_array, int num_feature, int feature_length,

cudaStream_t stream

);

void convert_nv12_to_bgr_invoke(

const uint8_t* y, const uint8_t* uv, int width, int height,

int linesize, uint8_t* dst,

cudaStream_t stream);

};

#endif // PREPROCESS_KERNEL_CUH