mirror of
https://github.com/leejet/stable-diffusion.cpp.git
synced 2026-07-25 04:10:52 -05:00
Compare commits
6 Commits
master-83e
...
master-19f
| Author | SHA1 | Date | |
|---|---|---|---|
|
|
19fbfd8639 | ||
|
|
76c72628b1 | ||
|
|
3bae667f3d | ||
|
|
8d0819c548 | ||
|
|
7a8ff2e819 | ||
|
|
0927e8e322 |
@@ -50,7 +50,7 @@ Inference of Stable Diffusion and Flux in pure C/C++
|
||||
- Linux
|
||||
- Mac OS
|
||||
- Windows
|
||||
- Android (via Termux)
|
||||
- Android (via Termux, [Local Diffusion](https://github.com/rmatif/Local-Diffusion))
|
||||
|
||||
### TODO
|
||||
|
||||
@@ -392,10 +392,12 @@ Using formats of different precisions will yield results of varying quality.
|
||||
|
||||
These projects wrap `stable-diffusion.cpp` for easier use in other languages/frameworks.
|
||||
|
||||
* Golang: [seasonjs/stable-diffusion](https://github.com/seasonjs/stable-diffusion)
|
||||
* Golang (non-cgo): [seasonjs/stable-diffusion](https://github.com/seasonjs/stable-diffusion)
|
||||
* Golang (cgo): [Binozo/GoStableDiffusion](https://github.com/Binozo/GoStableDiffusion)
|
||||
* C#: [DarthAffe/StableDiffusion.NET](https://github.com/DarthAffe/StableDiffusion.NET)
|
||||
* Python: [william-murray1204/stable-diffusion-cpp-python](https://github.com/william-murray1204/stable-diffusion-cpp-python)
|
||||
* Rust: [newfla/diffusion-rs](https://github.com/newfla/diffusion-rs)
|
||||
* Flutter/Dart: [rmatif/Local-Diffusion](https://github.com/rmatif/Local-Diffusion)
|
||||
|
||||
## UIs
|
||||
|
||||
@@ -404,6 +406,7 @@ These projects use `stable-diffusion.cpp` as a backend for their image generatio
|
||||
- [Jellybox](https://jellybox.com)
|
||||
- [Stable Diffusion GUI](https://github.com/fszontagh/sd.cpp.gui.wx)
|
||||
- [Stable Diffusion CLI-GUI](https://github.com/piallai/stable-diffusion.cpp)
|
||||
- [Local Diffusion](https://github.com/rmatif/Local-Diffusion)
|
||||
|
||||
## Contributors
|
||||
|
||||
|
||||
@@ -459,8 +459,8 @@ struct FrozenCLIPEmbedderWithCustomWords : public Conditioner {
|
||||
if (sd_version_is_sdxl(version)) {
|
||||
text_model2->compute(n_threads,
|
||||
input_ids2,
|
||||
0,
|
||||
NULL,
|
||||
num_custom_embeddings,
|
||||
token_embed_custom.data(),
|
||||
max_token_idx,
|
||||
false,
|
||||
&chunk_hidden_states2, work_ctx);
|
||||
@@ -470,8 +470,8 @@ struct FrozenCLIPEmbedderWithCustomWords : public Conditioner {
|
||||
if (chunk_idx == 0) {
|
||||
text_model2->compute(n_threads,
|
||||
input_ids2,
|
||||
0,
|
||||
NULL,
|
||||
num_custom_embeddings,
|
||||
token_embed_custom.data(),
|
||||
max_token_idx,
|
||||
true,
|
||||
&pooled,
|
||||
|
||||
@@ -181,7 +181,7 @@ struct AYSSchedule : SigmaSchedule {
|
||||
LOG_INFO("AYS using SVD noise levels");
|
||||
inputs = noise_levels[2];
|
||||
} else {
|
||||
LOG_ERROR("Version not compatable with AYS scheduler");
|
||||
LOG_ERROR("Version not compatible with AYS scheduler");
|
||||
return results;
|
||||
}
|
||||
|
||||
|
||||
@@ -60,6 +60,7 @@ const char* modes_str[] = {
|
||||
"edit",
|
||||
"convert",
|
||||
};
|
||||
#define SD_ALL_MODES_STR "txt2img, img2img, edit, convert"
|
||||
|
||||
enum SDMode {
|
||||
TXT2IMG,
|
||||
@@ -199,14 +200,18 @@ void print_usage(int argc, const char* argv[]) {
|
||||
printf("\n");
|
||||
printf("arguments:\n");
|
||||
printf(" -h, --help show this help message and exit\n");
|
||||
printf(" -M, --mode [MODEL] run mode (txt2img or img2img or convert, default: txt2img)\n");
|
||||
printf(" -M, --mode [MODE] run mode, one of:\n");
|
||||
printf(" txt2img: generate an image from a text prompt (default)\n");
|
||||
printf(" img2img: generate an image from a text prompt and an initial image (--init-img)\n");
|
||||
printf(" edit: modify an image (--ref-image) based on text instructions\n");
|
||||
printf(" convert: convert a model file to gguf format, optionally with quantization\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 full model\n");
|
||||
printf(" --diffusion-model path to the standalone diffusion model\n");
|
||||
printf(" --clip_l path to the clip-l text encoder\n");
|
||||
printf(" --clip_g path to the clip-g text encoder\n");
|
||||
printf(" --t5xxl path to the the t5xxl text encoder\n");
|
||||
printf(" --t5xxl path to the t5xxl text encoder\n");
|
||||
printf(" --vae [VAE] path to vae\n");
|
||||
printf(" --taesd [TAESD_PATH] path to taesd. Using Tiny AutoEncoder for fast decoding (low quality)\n");
|
||||
printf(" --control-net [CONTROL_PATH] path to control net model\n");
|
||||
@@ -222,7 +227,7 @@ void print_usage(int argc, const char* argv[]) {
|
||||
printf(" -i, --init-img [IMAGE] path to the input image, required by img2img\n");
|
||||
printf(" --mask [MASK] path to the mask image, required by img2img with mask\n");
|
||||
printf(" --control-image [IMAGE] path to image condition, control net\n");
|
||||
printf(" -r, --ref_image [PATH] reference image for Flux Kontext models (can be used multiple times) \n");
|
||||
printf(" -r, --ref-image [PATH] reference image for Flux Kontext models (can be used multiple times) \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");
|
||||
@@ -291,8 +296,8 @@ void parse_args(int argc, const char** argv, SDParams& params) {
|
||||
}
|
||||
if (mode_found == -1) {
|
||||
fprintf(stderr,
|
||||
"error: invalid mode %s, must be one of [txt2img, img2img, img2vid, convert]\n",
|
||||
mode_selected);
|
||||
"error: invalid mode %s, must be one of [%s]\n",
|
||||
mode_selected, SD_ALL_MODES_STR);
|
||||
exit(1);
|
||||
}
|
||||
params.mode = (SDMode)mode_found;
|
||||
@@ -1218,4 +1223,4 @@ int main(int argc, const char* argv[]) {
|
||||
free(input_image_buffer);
|
||||
|
||||
return 0;
|
||||
}
|
||||
}
|
||||
|
||||
18
model.cpp
18
model.cpp
@@ -1539,6 +1539,15 @@ bool ModelLoader::init_from_ckpt_file(const std::string& file_path, const std::s
|
||||
return true;
|
||||
}
|
||||
|
||||
bool ModelLoader::model_is_unet() {
|
||||
for (auto& tensor_storage : tensor_storages) {
|
||||
if (tensor_storage.name.find("model.diffusion_model.input_blocks.") != std::string::npos) {
|
||||
return true;
|
||||
}
|
||||
}
|
||||
return false;
|
||||
}
|
||||
|
||||
SDVersion ModelLoader::get_sd_version() {
|
||||
TensorStorage token_embedding_weight, input_block_weight;
|
||||
bool input_block_checked = false;
|
||||
@@ -1841,6 +1850,7 @@ bool ModelLoader::load_tensors(on_new_tensor_cb_t on_new_tensor_cb, ggml_backend
|
||||
};
|
||||
int tensor_count = 0;
|
||||
int64_t t1 = ggml_time_ms();
|
||||
bool partial = false;
|
||||
for (auto& tensor_storage : processed_tensor_storages) {
|
||||
if (tensor_storage.file_index != file_index) {
|
||||
++tensor_count;
|
||||
@@ -1922,15 +1932,21 @@ bool ModelLoader::load_tensors(on_new_tensor_cb_t on_new_tensor_cb, ggml_backend
|
||||
ggml_backend_tensor_set(dst_tensor, convert_buffer.data(), 0, ggml_nbytes(dst_tensor));
|
||||
}
|
||||
}
|
||||
size_t tensor_max = processed_tensor_storages.size();
|
||||
int64_t t2 = ggml_time_ms();
|
||||
pretty_progress(++tensor_count, processed_tensor_storages.size(), (t2 - t1) / 1000.0f);
|
||||
pretty_progress(++tensor_count, tensor_max, (t2 - t1) / 1000.0f);
|
||||
t1 = t2;
|
||||
partial = tensor_count != tensor_max;
|
||||
}
|
||||
|
||||
if (zip != NULL) {
|
||||
zip_close(zip);
|
||||
}
|
||||
|
||||
if (partial) {
|
||||
printf("\n");
|
||||
}
|
||||
|
||||
if (!success) {
|
||||
break;
|
||||
}
|
||||
|
||||
1
model.h
1
model.h
@@ -210,6 +210,7 @@ public:
|
||||
std::map<std::string, enum ggml_type> tensor_storages_types;
|
||||
|
||||
bool init_from_file(const std::string& file_path, const std::string& prefix = "");
|
||||
bool model_is_unet();
|
||||
SDVersion get_sd_version();
|
||||
ggml_type get_sd_wtype();
|
||||
ggml_type get_conditioner_wtype();
|
||||
|
||||
@@ -213,16 +213,25 @@ public:
|
||||
}
|
||||
}
|
||||
|
||||
if (diffusion_model_path.size() > 0) {
|
||||
LOG_INFO("loading diffusion model from '%s'", diffusion_model_path.c_str());
|
||||
if (!model_loader.init_from_file(diffusion_model_path, "model.diffusion_model.")) {
|
||||
LOG_WARN("loading diffusion model from '%s' failed", diffusion_model_path.c_str());
|
||||
}
|
||||
}
|
||||
|
||||
bool is_unet = model_loader.model_is_unet();
|
||||
|
||||
if (clip_l_path.size() > 0) {
|
||||
LOG_INFO("loading clip_l from '%s'", clip_l_path.c_str());
|
||||
if (!model_loader.init_from_file(clip_l_path, "text_encoders.clip_l.transformer.")) {
|
||||
if (!model_loader.init_from_file(clip_l_path, is_unet ? "cond_stage_model.transformer." : "text_encoders.clip_l.transformer.")) {
|
||||
LOG_WARN("loading clip_l from '%s' failed", clip_l_path.c_str());
|
||||
}
|
||||
}
|
||||
|
||||
if (clip_g_path.size() > 0) {
|
||||
LOG_INFO("loading clip_g from '%s'", clip_g_path.c_str());
|
||||
if (!model_loader.init_from_file(clip_g_path, "text_encoders.clip_g.transformer.")) {
|
||||
if (!model_loader.init_from_file(clip_g_path, is_unet ? "cond_stage_model.1.transformer." : "text_encoders.clip_g.transformer.")) {
|
||||
LOG_WARN("loading clip_g from '%s' failed", clip_g_path.c_str());
|
||||
}
|
||||
}
|
||||
@@ -234,13 +243,6 @@ public:
|
||||
}
|
||||
}
|
||||
|
||||
if (diffusion_model_path.size() > 0) {
|
||||
LOG_INFO("loading diffusion model from '%s'", diffusion_model_path.c_str());
|
||||
if (!model_loader.init_from_file(diffusion_model_path, "model.diffusion_model.")) {
|
||||
LOG_WARN("loading diffusion model from '%s' failed", diffusion_model_path.c_str());
|
||||
}
|
||||
}
|
||||
|
||||
if (vae_path.size() > 0) {
|
||||
LOG_INFO("loading vae from '%s'", vae_path.c_str());
|
||||
if (!model_loader.init_from_file(vae_path, "vae.")) {
|
||||
|
||||
Reference in New Issue
Block a user