mirror of
https://github.com/leejet/stable-diffusion.cpp.git
synced 2026-08-02 00:00:41 -05:00
feat: add img2img mode (#5)
This commit is contained in:
119
main.cpp
119
main.cpp
@@ -8,13 +8,16 @@
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#include "stable-diffusion.h"
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#define STB_IMAGE_IMPLEMENTATION
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#include "stb_image.h"
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#define STB_IMAGE_WRITE_IMPLEMENTATION
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#define STB_IMAGE_WRITE_STATIC
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#include "stb_image_write.h"
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#if defined(__APPLE__) && defined(__MACH__)
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#include <sys/types.h>
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#include <sys/sysctl.h>
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#include <sys/types.h>
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#endif
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#if !defined(_WIN32)
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@@ -22,6 +25,9 @@
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#include <unistd.h>
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#endif
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#define TXT2IMG "txt2img"
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#define IMG2IMG "img2img"
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// get_num_physical_cores is copy from
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// https://github.com/ggerganov/llama.cpp/blob/master/examples/common.cpp
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// LICENSE: https://github.com/ggerganov/llama.cpp/blob/master/LICENSE
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@@ -63,8 +69,10 @@ int32_t get_num_physical_cores() {
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struct Option {
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int n_threads = -1;
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std::string mode = TXT2IMG;
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std::string model_path;
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std::string output_path = "output.png";
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std::string init_img;
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std::string prompt;
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std::string negative_prompt;
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float cfg_scale = 7.0f;
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@@ -72,14 +80,17 @@ struct Option {
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int h = 512;
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SampleMethod sample_method = EULAR_A;
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int sample_steps = 20;
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float strength = 0.75f;
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int seed = 42;
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bool verbose = false;
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void print() {
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printf("Option: \n");
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printf(" n_threads: %d\n", n_threads);
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printf(" mode: %s\n", mode.c_str());
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printf(" model_path: %s\n", model_path.c_str());
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printf(" output_path: %s\n", output_path.c_str());
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printf(" init_img: %s\n", init_img.c_str());
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printf(" prompt: %s\n", prompt.c_str());
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printf(" negative_prompt: %s\n", negative_prompt.c_str());
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printf(" cfg_scale: %.2f\n", cfg_scale);
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@@ -87,6 +98,7 @@ struct Option {
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printf(" height: %d\n", h);
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printf(" sample_method: %s\n", "eular a");
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printf(" sample_steps: %d\n", sample_steps);
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printf(" strength: %.2f\n", strength);
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printf(" seed: %d\n", seed);
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}
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};
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@@ -96,13 +108,17 @@ void print_usage(int argc, const char* argv[]) {
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printf("\n");
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printf("arguments:\n");
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printf(" -h, --help show this help message and exit\n");
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printf(" -M, --mode [txt2img or img2img] generation mode (default: txt2img)\n");
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printf(" -t, --threads N number of threads to use during computation (default: -1).\n");
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printf(" If threads <= 0, then threads will be set to the number of CPU physical cores\n");
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printf(" -m, --model [MODEL] path to model\n");
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printf(" -i, --init-img [IMAGE] path to the input image, required by img2img\n");
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printf(" -o, --output OUTPUT path to write result image to (default: .\\output.png)\n");
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printf(" -p, --prompt [PROMPT] the prompt to render\n");
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printf(" -n, --negative-prompt PROMPT the negative prompt (default: \"\")\n");
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printf(" --cfg-scale SCALE unconditional guidance scale: (default: 7.0)\n");
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printf(" --strength STRENGTH strength for noising/unnoising (default: 0.75)\n");
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printf(" 1.0 corresponds to full destruction of information in init image\n");
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printf(" -H, --height H image height, in pixel space (default: 512)\n");
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printf(" -W, --width W image width, in pixel space (default: 512)\n");
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printf(" --sample-method SAMPLE_METHOD sample method (default: \"eular a\")\n");
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@@ -123,12 +139,25 @@ void parse_args(int argc, const char* argv[], Option* opt) {
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break;
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}
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opt->n_threads = std::stoi(argv[i]);
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} else if (arg == "-M" || arg == "--mode") {
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if (++i >= argc) {
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invalid_arg = true;
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break;
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}
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opt->mode = argv[i];
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} else if (arg == "-m" || arg == "--model") {
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if (++i >= argc) {
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invalid_arg = true;
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break;
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}
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opt->model_path = argv[i];
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} else if (arg == "-i" || arg == "--init-img") {
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if (++i >= argc) {
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invalid_arg = true;
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break;
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}
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opt->init_img = argv[i];
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} else if (arg == "-o" || arg == "--output") {
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if (++i >= argc) {
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invalid_arg = true;
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@@ -153,6 +182,12 @@ void parse_args(int argc, const char* argv[], Option* opt) {
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break;
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}
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opt->cfg_scale = std::stof(argv[i]);
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} else if (arg == "--strength") {
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if (++i >= argc) {
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invalid_arg = true;
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break;
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}
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opt->strength = std::stof(argv[i]);
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} else if (arg == "-H" || arg == "--height") {
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if (++i >= argc) {
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invalid_arg = true;
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@@ -198,6 +233,12 @@ void parse_args(int argc, const char* argv[], Option* opt) {
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opt->n_threads = get_num_physical_cores();
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}
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if (opt->mode != TXT2IMG && opt->mode != IMG2IMG) {
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fprintf(stderr, "error: invalid mode %s, must be one of ['%s', '%s']\n",
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opt->mode.c_str(), TXT2IMG, IMG2IMG);
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exit(1);
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}
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if (opt->prompt.length() == 0) {
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fprintf(stderr, "error: the following arguments are required: prompt\n");
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print_usage(argc, argv);
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@@ -210,6 +251,12 @@ void parse_args(int argc, const char* argv[], Option* opt) {
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exit(1);
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}
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if (opt->mode == IMG2IMG && opt->init_img.length() == 0) {
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fprintf(stderr, "error: when using the img2img mode, the following arguments are required: init-img\n");
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print_usage(argc, argv);
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exit(1);
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}
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if (opt->output_path.length() == 0) {
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fprintf(stderr, "error: the following arguments are required: output_path\n");
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print_usage(argc, argv);
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@@ -230,6 +277,11 @@ void parse_args(int argc, const char* argv[], Option* opt) {
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fprintf(stderr, "error: the sample_steps must be greater than 0\n");
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exit(1);
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}
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if (opt->strength < 0.f || opt->strength > 1.f) {
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fprintf(stderr, "error: can only work with strength in [0.0, 1.0]\n");
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exit(1);
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}
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}
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int main(int argc, const char* argv[]) {
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@@ -242,19 +294,66 @@ int main(int argc, const char* argv[]) {
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set_sd_log_level(SDLogLevel::DEBUG);
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}
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StableDiffusion sd(opt.n_threads);
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bool vae_decode_only = true;
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std::vector<uint8_t> init_img;
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if (opt.mode == IMG2IMG) {
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vae_decode_only = false;
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int c = 0;
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unsigned char* img_data = stbi_load(opt.init_img.c_str(), &opt.w, &opt.h, &c, 3);
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if (img_data == NULL) {
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fprintf(stderr, "load image from '%s' failed\n", opt.init_img.c_str());
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return 1;
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}
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if (c != 3) {
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fprintf(stderr, "input image must be a 3 channels RGB image, but got %d channels\n", c);
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free(img_data);
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return 1;
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}
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if (opt.w <= 0 || opt.w % 32 != 0) {
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fprintf(stderr, "error: the width of image must be a multiple of 32\n");
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free(img_data);
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return 1;
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}
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if (opt.h <= 0 || opt.h % 32 != 0) {
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fprintf(stderr, "error: the height of image must be a multiple of 32\n");
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free(img_data);
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return 1;
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}
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init_img.assign(img_data, img_data + (opt.w * opt.h * c));
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}
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StableDiffusion sd(opt.n_threads, vae_decode_only);
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if (!sd.load_from_file(opt.model_path)) {
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return 1;
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}
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std::vector<uint8_t> img = sd.txt2img(opt.prompt,
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opt.negative_prompt,
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opt.cfg_scale,
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opt.w,
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opt.h,
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opt.sample_method,
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opt.sample_steps,
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opt.seed);
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std::vector<uint8_t> img;
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if (opt.mode == TXT2IMG) {
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img = sd.txt2img(opt.prompt,
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opt.negative_prompt,
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opt.cfg_scale,
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opt.w,
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opt.h,
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opt.sample_method,
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opt.sample_steps,
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opt.seed);
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} else {
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img = sd.img2img(init_img,
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opt.prompt,
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opt.negative_prompt,
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opt.cfg_scale,
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opt.w,
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opt.h,
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opt.sample_method,
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opt.sample_steps,
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opt.strength,
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opt.seed);
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}
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if (img.size() == 0) {
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fprintf(stderr, "generate failed\n");
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return 1;
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}
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stbi_write_png(opt.output_path.c_str(), opt.w, opt.h, 3, img.data(), 0);
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printf("save result image to '%s'\n", opt.output_path.c_str());
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