tiny_dnn
1.0.0
A header only, dependency-free deep learning framework in C++11
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Simple image utility class. More...
#include <image.h>
Public Types | |
typedef T | intensity_t |
typedef std::vector< intensity_t >::iterator | iterator |
typedef std::vector< intensity_t >::const_iterator | const_iterator |
Public Member Functions | |
image (const T *data, size_t width, size_t height, image_type type) | |
create image from raw pointer | |
image (const shape3d &size, image_type type) | |
create WxHxD image filled with 0 | |
template<typename U > | |
image (const image< U > &rhs) | |
image (const std::string &filename, image_type type) | |
create image from file supported file format: JPEG/PNG/TGA/BMP/PSD/GIF/HDR/PIC/PNM (see detail at the comments in thrid_party/stb/stb_image.h) | |
void | save (const std::string &path) const |
void | write (const std::string &path) const |
void | resize (size_t width, size_t height) |
void | fill (intensity_t value) |
intensity_t & | at (size_t x, size_t y, size_t z=0) |
const intensity_t & | at (size_t x, size_t y, size_t z=0) const |
bool | empty () const |
iterator | begin () |
iterator | end () |
const_iterator | begin () const |
const_iterator | end () const |
intensity_t & | operator[] (std::size_t idx) |
const intensity_t & | operator[] (std::size_t idx) const |
size_t | width () const |
size_t | height () const |
size_t | depth () const |
image_type | type () const |
shape3d | shape () const |
const std::vector< intensity_t > & | data () const |
vec_t | to_vec () const |
template<typename U > | |
std::vector< U > | to_rgb () const |
template<typename Iter > | |
void | from_rgb (Iter begin, Iter end) |
Simple image utility class.