stable-diffusion.cpp/stable-diffusion.h
2023-11-28 20:49:11 +08:00

79 lines
1.6 KiB
C++

#ifndef __STABLE_DIFFUSION_H__
#define __STABLE_DIFFUSION_H__
#include <string>
#include <memory>
#include <vector>
enum SDLogLevel {
DEBUG,
INFO,
WARN,
ERROR
};
enum RNGType {
STD_DEFAULT_RNG,
CUDA_RNG
};
enum SampleMethod {
EULER_A,
EULER,
HEUN,
DPM2,
DPMPP2S_A,
DPMPP2M,
DPMPP2Mv2,
LCM,
N_SAMPLE_METHODS
};
enum Schedule {
DEFAULT,
DISCRETE,
KARRAS,
N_SCHEDULES
};
class StableDiffusionGGML;
class StableDiffusion {
private:
std::shared_ptr<StableDiffusionGGML> sd;
public:
StableDiffusion(int n_threads = -1,
bool vae_decode_only = false,
bool free_params_immediately = false,
std::string lora_model_dir = "",
RNGType rng_type = STD_DEFAULT_RNG);
bool load_from_file(const std::string& file_path, Schedule d = DEFAULT);
std::vector<uint8_t*> txt2img(
std::string prompt,
std::string negative_prompt,
float cfg_scale,
int width,
int height,
SampleMethod sample_method,
int sample_steps,
int64_t seed,
int batch_count);
std::vector<uint8_t*> img2img(
const uint8_t* init_img_data,
std::string prompt,
std::string negative_prompt,
float cfg_scale,
int width,
int height,
SampleMethod sample_method,
int sample_steps,
float strength,
int64_t seed);
};
void set_sd_log_level(SDLogLevel level);
std::string sd_get_system_info();
#endif // __STABLE_DIFFUSION_H__