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Support an arbitrary number of custom models, placed in the models/stable-diffusion folder. Shows an option in the UI to select which model to use

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cmdr2
2022-10-06 14:28:02 +05:30
parent 703f987825
commit 201a053025
7 changed files with 165 additions and 15 deletions
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21
ui/sd_internal/runtime.py
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@ -208,6 +208,7 @@ def mk_img(req: Request):
})
def do_mk_img(req: Request):
global ckpt_file
global model, modelCS, modelFS, device
global model_gfpgan, model_real_esrgan
global stop_processing
@ -220,6 +221,15 @@ def do_mk_img(req: Request):
temp_images.clear()
# custom model support:
# the req.use_stable_diffusion_model needs to be a valid path
# to the ckpt file (without the extension).
needs_model_reload = False
if ckpt_file != req.use_stable_diffusion_model:
ckpt_file = req.use_stable_diffusion_model
needs_model_reload = True
model.turbo = req.turbo
if req.use_cpu:
if device != 'cpu':
@ -228,6 +238,7 @@ def do_mk_img(req: Request):
if model_is_half:
del model, modelCS, modelFS
load_model_ckpt(ckpt_file, device)
needs_model_reload = False
load_model_gfpgan(gfpgan_file)
load_model_real_esrgan(real_esrgan_file)
@ -243,11 +254,15 @@ def do_mk_img(req: Request):
del model, modelCS, modelFS
load_model_ckpt(ckpt_file, device, req.turbo, unet_bs, ('full' if req.use_full_precision else 'autocast'), half_model_fs=(req.init_image is not None and not req.use_full_precision))
needs_model_reload = False
if prev_device != device:
load_model_gfpgan(gfpgan_file)
load_model_real_esrgan(real_esrgan_file)
if needs_model_reload:
load_model_ckpt(ckpt_file, device, req.turbo, unet_bs, precision, model_fs_is_half)
if req.use_face_correction != gfpgan_file:
load_model_gfpgan(req.use_face_correction)
@ -444,7 +459,7 @@ def do_mk_img(req: Request):
if return_orig_img:
save_image(img, img_out_path)
save_metadata(meta_out_path, prompts, opt_seed, opt_W, opt_H, opt_ddim_steps, opt_scale, opt_strength, opt_use_face_correction, opt_use_upscale, opt_sampler_name, req.negative_prompt)
save_metadata(meta_out_path, prompts, opt_seed, opt_W, opt_H, opt_ddim_steps, opt_scale, opt_strength, opt_use_face_correction, opt_use_upscale, opt_sampler_name, req.negative_prompt, ckpt_file)
if return_orig_img:
img_data = img_to_base64_str(img)
@ -505,8 +520,8 @@ def save_image(img, img_out_path):
except:
print('could not save the file', traceback.format_exc())
def save_metadata(meta_out_path, prompts, opt_seed, opt_W, opt_H, opt_ddim_steps, opt_scale, opt_prompt_strength, opt_correct_face, opt_upscale, sampler_name, negative_prompt):
metadata = f"{prompts[0]}\nWidth: {opt_W}\nHeight: {opt_H}\nSeed: {opt_seed}\nSteps: {opt_ddim_steps}\nGuidance Scale: {opt_scale}\nPrompt Strength: {opt_prompt_strength}\nUse Face Correction: {opt_correct_face}\nUse Upscaling: {opt_upscale}\nSampler: {sampler_name}\nNegative Prompt: {negative_prompt}"
def save_metadata(meta_out_path, prompts, opt_seed, opt_W, opt_H, opt_ddim_steps, opt_scale, opt_prompt_strength, opt_correct_face, opt_upscale, sampler_name, negative_prompt, ckpt_file):
metadata = f"{prompts[0]}\nWidth: {opt_W}\nHeight: {opt_H}\nSeed: {opt_seed}\nSteps: {opt_ddim_steps}\nGuidance Scale: {opt_scale}\nPrompt Strength: {opt_prompt_strength}\nUse Face Correction: {opt_correct_face}\nUse Upscaling: {opt_upscale}\nSampler: {sampler_name}\nNegative Prompt: {negative_prompt}\nStable Diffusion Model: {ckpt_file + '.ckpt'}"
try:
with open(meta_out_path, 'w') as f: