#include #include #include #include #include #include #include #include #include "stable-diffusion.h" #define STB_IMAGE_IMPLEMENTATION #include "stb_image.h" #define STB_IMAGE_WRITE_IMPLEMENTATION #define STB_IMAGE_WRITE_STATIC #include "stb_image_write.h" #if defined(__APPLE__) && defined(__MACH__) #include #include #endif #if !defined(_WIN32) #include #include #endif #define TXT2IMG "txt2img" #define IMG2IMG "img2img" // get_num_physical_cores is copy from // https://github.com/ggerganov/llama.cpp/blob/master/examples/common.cpp // LICENSE: https://github.com/ggerganov/llama.cpp/blob/master/LICENSE int32_t get_num_physical_cores() { #ifdef __linux__ // enumerate the set of thread siblings, num entries is num cores std::unordered_set siblings; for (uint32_t cpu = 0; cpu < UINT32_MAX; ++cpu) { std::ifstream thread_siblings("/sys/devices/system/cpu" + std::to_string(cpu) + "/topology/thread_siblings"); if (!thread_siblings.is_open()) { break; // no more cpus } std::string line; if (std::getline(thread_siblings, line)) { siblings.insert(line); } } if (siblings.size() > 0) { return static_cast(siblings.size()); } #elif defined(__APPLE__) && defined(__MACH__) int32_t num_physical_cores; size_t len = sizeof(num_physical_cores); int result = sysctlbyname("hw.perflevel0.physicalcpu", &num_physical_cores, &len, NULL, 0); if (result == 0) { return num_physical_cores; } result = sysctlbyname("hw.physicalcpu", &num_physical_cores, &len, NULL, 0); if (result == 0) { return num_physical_cores; } #elif defined(_WIN32) // TODO: Implement #endif unsigned int n_threads = std::thread::hardware_concurrency(); return n_threads > 0 ? (n_threads <= 4 ? n_threads : n_threads / 2) : 4; } const char* rng_type_to_str[] = { "std_default", "cuda", }; // Names of the sampler method, same order as enum SampleMethod in stable-diffusion.h const char* sample_method_str[] = { "euler_a", "euler", "heun", "dpm2", "dpm++2s_a", "dpm++2m", "dpm++2mv2"}; // Names of the sigma schedule overrides, same order as Schedule in stable-diffusion.h const char* schedule_str[] = { "default", "discrete", "karras"}; struct Option { int n_threads = -1; std::string mode = TXT2IMG; std::string model_path; std::string output_path = "output.png"; std::string init_img; std::string prompt; std::string negative_prompt; float cfg_scale = 7.0f; int w = 512; int h = 512; SampleMethod sample_method = EULER_A; Schedule schedule = DEFAULT; int sample_steps = 20; float strength = 0.75f; RNGType rng_type = CUDA_RNG; int64_t seed = 42; bool verbose = false; void print() { printf("Option: \n"); printf(" n_threads: %d\n", n_threads); printf(" mode: %s\n", mode.c_str()); printf(" model_path: %s\n", model_path.c_str()); printf(" output_path: %s\n", output_path.c_str()); printf(" init_img: %s\n", init_img.c_str()); printf(" prompt: %s\n", prompt.c_str()); printf(" negative_prompt: %s\n", negative_prompt.c_str()); printf(" cfg_scale: %.2f\n", cfg_scale); printf(" width: %d\n", w); printf(" height: %d\n", h); printf(" sample_method: %s\n", sample_method_str[sample_method]); printf(" schedule: %s\n", schedule_str[schedule]); printf(" sample_steps: %d\n", sample_steps); printf(" strength: %.2f\n", strength); printf(" rng: %s\n", rng_type_to_str[rng_type]); printf(" seed: %ld\n", seed); } }; void print_usage(int argc, const char* argv[]) { printf("usage: %s [arguments]\n", argv[0]); printf("\n"); printf("arguments:\n"); printf(" -h, --help show this help message and exit\n"); printf(" -M, --mode [txt2img or img2img] generation mode (default: txt2img)\n"); printf(" -t, --threads N number of threads to use during computation (default: -1).\n"); printf(" If threads <= 0, then threads will be set to the number of CPU physical cores\n"); printf(" -m, --model [MODEL] path to model\n"); printf(" -i, --init-img [IMAGE] path to the input image, required by img2img\n"); printf(" -o, --output OUTPUT path to write result image to (default: .\\output.png)\n"); printf(" -p, --prompt [PROMPT] the prompt to render\n"); printf(" -n, --negative-prompt PROMPT the negative prompt (default: \"\")\n"); printf(" --cfg-scale SCALE unconditional guidance scale: (default: 7.0)\n"); printf(" --strength STRENGTH strength for noising/unnoising (default: 0.75)\n"); printf(" 1.0 corresponds to full destruction of information in init image\n"); printf(" -H, --height H image height, in pixel space (default: 512)\n"); printf(" -W, --width W image width, in pixel space (default: 512)\n"); printf(" --sampling-method {euler, euler_a, heun, dpm2, dpm++2s_a, dpm++2m, dpm++2mv2}\n"); printf(" sampling method (default: \"euler_a\")\n"); printf(" --steps STEPS number of sample steps (default: 20)\n"); printf(" --rng {std_default, cuda} RNG (default: cuda)\n"); printf(" -s SEED, --seed SEED RNG seed (default: 42, use random seed for < 0)\n"); printf(" --schedule {discrete, karras} Denoiser sigma schedule (default: discrete)\n"); printf(" -v, --verbose print extra info\n"); } void parse_args(int argc, const char* argv[], Option* opt) { bool invalid_arg = false; for (int i = 1; i < argc; i++) { std::string arg = argv[i]; if (arg == "-t" || arg == "--threads") { if (++i >= argc) { invalid_arg = true; break; } opt->n_threads = std::stoi(argv[i]); } else if (arg == "-M" || arg == "--mode") { if (++i >= argc) { invalid_arg = true; break; } opt->mode = argv[i]; } else if (arg == "-m" || arg == "--model") { if (++i >= argc) { invalid_arg = true; break; } opt->model_path = argv[i]; } else if (arg == "-i" || arg == "--init-img") { if (++i >= argc) { invalid_arg = true; break; } opt->init_img = argv[i]; } else if (arg == "-o" || arg == "--output") { if (++i >= argc) { invalid_arg = true; break; } opt->output_path = argv[i]; } else if (arg == "-p" || arg == "--prompt") { if (++i >= argc) { invalid_arg = true; break; } opt->prompt = argv[i]; } else if (arg == "-n" || arg == "--negative-prompt") { if (++i >= argc) { invalid_arg = true; break; } opt->negative_prompt = argv[i]; } else if (arg == "--cfg-scale") { if (++i >= argc) { invalid_arg = true; break; } opt->cfg_scale = std::stof(argv[i]); } else if (arg == "--strength") { if (++i >= argc) { invalid_arg = true; break; } opt->strength = std::stof(argv[i]); } else if (arg == "-H" || arg == "--height") { if (++i >= argc) { invalid_arg = true; break; } opt->h = std::stoi(argv[i]); } else if (arg == "-W" || arg == "--width") { if (++i >= argc) { invalid_arg = true; break; } opt->w = std::stoi(argv[i]); } else if (arg == "--steps") { if (++i >= argc) { invalid_arg = true; break; } opt->sample_steps = std::stoi(argv[i]); } else if (arg == "--rng") { if (++i >= argc) { invalid_arg = true; break; } std::string rng_type_str = argv[i]; if (rng_type_str == "std_default") { opt->rng_type = STD_DEFAULT_RNG; } else if (rng_type_str == "cuda") { opt->rng_type = CUDA_RNG; } else { invalid_arg = true; break; } } else if (arg == "--schedule") { if (++i >= argc) { invalid_arg = true; break; } const char* schedule_selected = argv[i]; int schedule_found = -1; for (int d = 0; d < N_SCHEDULES; d++) { if (!strcmp(schedule_selected, schedule_str[d])) { schedule_found = d; } } if (schedule_found == -1) { invalid_arg = true; break; } opt->schedule = (Schedule)schedule_found; } else if (arg == "-s" || arg == "--seed") { if (++i >= argc) { invalid_arg = true; break; } opt->seed = std::stoll(argv[i]); } else if (arg == "--sampling-method") { if (++i >= argc) { invalid_arg = true; break; } const char* sample_method_selected = argv[i]; int sample_method_found = -1; for (int m = 0; m < N_SAMPLE_METHODS; m++) { if (!strcmp(sample_method_selected, sample_method_str[m])) { sample_method_found = m; } } if (sample_method_found == -1) { invalid_arg = true; break; } opt->sample_method = (SampleMethod)sample_method_found; } else if (arg == "-h" || arg == "--help") { print_usage(argc, argv); exit(0); } else if (arg == "-v" || arg == "--verbose") { opt->verbose = true; } else { fprintf(stderr, "error: unknown argument: %s\n", arg.c_str()); print_usage(argc, argv); exit(1); } if (invalid_arg) { fprintf(stderr, "error: invalid parameter for argument: %s\n", arg.c_str()); print_usage(argc, argv); exit(1); } } if (opt->n_threads <= 0) { opt->n_threads = get_num_physical_cores(); } if (opt->mode != TXT2IMG && opt->mode != IMG2IMG) { fprintf(stderr, "error: invalid mode %s, must be one of ['%s', '%s']\n", opt->mode.c_str(), TXT2IMG, IMG2IMG); exit(1); } if (opt->prompt.length() == 0) { fprintf(stderr, "error: the following arguments are required: prompt\n"); print_usage(argc, argv); exit(1); } if (opt->model_path.length() == 0) { fprintf(stderr, "error: the following arguments are required: model_path\n"); print_usage(argc, argv); exit(1); } if (opt->mode == IMG2IMG && opt->init_img.length() == 0) { fprintf(stderr, "error: when using the img2img mode, the following arguments are required: init-img\n"); print_usage(argc, argv); exit(1); } if (opt->output_path.length() == 0) { fprintf(stderr, "error: the following arguments are required: output_path\n"); print_usage(argc, argv); exit(1); } if (opt->w <= 0 || opt->w % 64 != 0) { fprintf(stderr, "error: the width must be a multiple of 64\n"); exit(1); } if (opt->h <= 0 || opt->h % 64 != 0) { fprintf(stderr, "error: the height must be a multiple of 64\n"); exit(1); } if (opt->sample_steps <= 0) { fprintf(stderr, "error: the sample_steps must be greater than 0\n"); exit(1); } if (opt->strength < 0.f || opt->strength > 1.f) { fprintf(stderr, "error: can only work with strength in [0.0, 1.0]\n"); exit(1); } if (opt->seed < 0) { srand((int)time(NULL)); opt->seed = rand(); } } std::string basename(const std::string& path) { size_t pos = path.find_last_of('/'); if (pos != std::string::npos) { return path.substr(pos + 1); } pos = path.find_last_of('\\'); if (pos != std::string::npos) { return path.substr(pos + 1); } return path; } int main(int argc, const char* argv[]) { Option opt; parse_args(argc, argv, &opt); if (opt.verbose) { opt.print(); printf("%s", sd_get_system_info().c_str()); set_sd_log_level(SDLogLevel::DEBUG); } bool vae_decode_only = true; std::vector init_img; if (opt.mode == IMG2IMG) { vae_decode_only = false; int c = 0; unsigned char* img_data = stbi_load(opt.init_img.c_str(), &opt.w, &opt.h, &c, 3); if (img_data == NULL) { fprintf(stderr, "load image from '%s' failed\n", opt.init_img.c_str()); return 1; } if (c != 3) { fprintf(stderr, "input image must be a 3 channels RGB image, but got %d channels\n", c); free(img_data); return 1; } if (opt.w <= 0 || opt.w % 64 != 0) { fprintf(stderr, "error: the width of image must be a multiple of 64\n"); free(img_data); return 1; } if (opt.h <= 0 || opt.h % 64 != 0) { fprintf(stderr, "error: the height of image must be a multiple of 64\n"); free(img_data); return 1; } init_img.assign(img_data, img_data + (opt.w * opt.h * c)); } StableDiffusion sd(opt.n_threads, vae_decode_only, true, opt.rng_type); if (!sd.load_from_file(opt.model_path, opt.schedule)) { return 1; } std::vector img; if (opt.mode == TXT2IMG) { img = sd.txt2img(opt.prompt, opt.negative_prompt, opt.cfg_scale, opt.w, opt.h, opt.sample_method, opt.sample_steps, opt.seed); } else { img = sd.img2img(init_img, opt.prompt, opt.negative_prompt, opt.cfg_scale, opt.w, opt.h, opt.sample_method, opt.sample_steps, opt.strength, opt.seed); } if (img.size() == 0) { fprintf(stderr, "generate failed\n"); return 1; } std::string parameter_string = opt.prompt + "\n"; if (opt.negative_prompt.size() != 0) { parameter_string += "Negative prompt: " + opt.negative_prompt + "\n"; } parameter_string += "Steps: " + std::to_string(opt.sample_steps) + ", "; parameter_string += "CFG scale: " + std::to_string(opt.cfg_scale) + ", "; parameter_string += "Seed: " + std::to_string(opt.seed) + ", "; parameter_string += "Size: " + std::to_string(opt.w) + "x" + std::to_string(opt.h) + ", "; parameter_string += "Model: " + basename(opt.model_path) + ", "; parameter_string += "RNG: " + std::string(rng_type_to_str[opt.rng_type]) + ", "; parameter_string += "Sampler: " + std::string(sample_method_str[opt.sample_method]); if (opt.schedule == KARRAS) { parameter_string += " karras"; } parameter_string += ", "; parameter_string += "Version: stable-diffusion.cpp"; stbi_write_png(opt.output_path.c_str(), opt.w, opt.h, 3, img.data(), 0, parameter_string.c_str()); printf("save result image to '%s'\n", opt.output_path.c_str()); return 0; }