Merge branch 'master' into patch-1 (6165f07e) · Commits · github_fork / Stable Diffusion Webui

javascript/generationParams.js

0 → 100644

+33 −0

Original line number	Diff line number	Diff line
		// attaches listeners to the txt2img and img2img galleries to update displayed generation param text when the image changes

		let txt2img_gallery, img2img_gallery, modal = undefined;
		onUiUpdate(function(){
		if (!txt2img_gallery) {
		txt2img_gallery = attachGalleryListeners("txt2img")
		}
		if (!img2img_gallery) {
		img2img_gallery = attachGalleryListeners("img2img")
		}
		if (!modal) {
		modal = gradioApp().getElementById('lightboxModal')
		modalObserver.observe(modal, { attributes : true, attributeFilter : ['style'] });
		}
		});

		let modalObserver = new MutationObserver(function(mutations) {
		mutations.forEach(function(mutationRecord) {
		let selectedTab = gradioApp().querySelector('#tabs div button.bg-white')?.innerText
		if (mutationRecord.target.style.display === 'none' && selectedTab === 'txt2img' \|\| selectedTab === 'img2img')
		gradioApp().getElementById(selectedTab+"_generation_info_button").click()
		});
		});

		function attachGalleryListeners(tab_name) {
		gallery = gradioApp().querySelector('#'+tab_name+'_gallery')
		gallery?.addEventListener('click', () => gradioApp().getElementById(tab_name+"_generation_info_button").click());
		gallery?.addEventListener('keydown', (e) => {
		if (e.keyCode == 37 \|\| e.keyCode == 39) // left or right arrow
		gradioApp().getElementById(tab_name+"_generation_info_button").click()
		});
		return gallery;
		}

modules/api/api.py

+14 −2

Original line number	Diff line number	Diff line
		@@ -15,6 +15,9 @@ from modules.sd_models import checkpoints_list
		from modules.realesrgan_model import get_realesrgan_models
		from typing import List

		if shared.cmd_opts.deepdanbooru:
		from modules.deepbooru import get_deepbooru_tags

		def upscaler_to_index(name: str):
		try:
		return [x.name.lower() for x in shared.sd_upscalers].index(name.lower())
		@@ -220,11 +223,20 @@ class Api:
		if image_b64 is None:
		raise HTTPException(status_code=404, detail="Image not found")

		img = self.__base64_to_image(image_b64)
		img = decode_base64_to_image(image_b64)
		img = img.convert('RGB')

		# Override object param
		with self.queue_lock:
		if interrogatereq.model == "clip":
		processed = shared.interrogator.interrogate(img)
		elif interrogatereq.model == "deepdanbooru":
		if shared.cmd_opts.deepdanbooru:
		processed = get_deepbooru_tags(img)
		else:
		raise HTTPException(status_code=404, detail="Model not found. Add --deepdanbooru when launching for using the model.")
		else:
		raise HTTPException(status_code=404, detail="Model not found")

		return InterrogateResponse(caption=processed)

modules/api/models.py

+1 −0

Original line number	Diff line number	Diff line
		@@ -170,6 +170,7 @@ class ProgressResponse(BaseModel):

		class InterrogateRequest(BaseModel):
		image: str = Field(default="", title="Image", description="Image to work on, must be a Base64 string containing the image's data.")
		model: str = Field(default="clip", title="Model", description="The interrogate model used.")

		class InterrogateResponse(BaseModel):
		caption: str = Field(default=None, title="Caption", description="The generated caption for the image.")

modules/ngrok.py

+11 −2

Original line number	Diff line number	Diff line
		from pyngrok import ngrok, conf, exception


		def connect(token, port, region):
		account = None
		if token == None:
		token = 'None'
		else:
		if ':' in token:
		# token = authtoken:username:password
		account = token.split(':')[1] + ':' + token.split(':')[-1]
		token = token.split(':')[0]

		config = conf.PyngrokConfig(
		auth_token=token, region=region
		)
		try:
		if account == None:
		public_url = ngrok.connect(port, pyngrok_config=config, bind_tls=True).public_url
		else:
		public_url = ngrok.connect(port, pyngrok_config=config, bind_tls=True, auth=account).public_url
		except exception.PyngrokNgrokError:
		print(f'Invalid ngrok authtoken, ngrok connection aborted.\n'
		f'Your token: {token}, get the right one on https://dashboard.ngrok.com/get-started/your-authtoken')

modules/sd_models.py

+18 −11

Original line number	Diff line number	Diff line
		@@ -163,13 +163,21 @@ def load_model_weights(model, checkpoint_info, vae_file="auto"):
		checkpoint_file = checkpoint_info.filename
		sd_model_hash = checkpoint_info.hash

		if shared.opts.sd_checkpoint_cache > 0 and hasattr(model, "sd_checkpoint_info"):
		cache_enabled = shared.opts.sd_checkpoint_cache > 0

		if cache_enabled:
		sd_vae.restore_base_vae(model)
		checkpoints_loaded[model.sd_checkpoint_info] = model.state_dict().copy()

		vae_file = sd_vae.resolve_vae(checkpoint_file, vae_file=vae_file)

		if checkpoint_info not in checkpoints_loaded:
		if cache_enabled and checkpoint_info in checkpoints_loaded:
		# use checkpoint cache
		vae_name = sd_vae.get_filename(vae_file) if vae_file else None
		vae_message = f" with {vae_name} VAE" if vae_name else ""
		print(f"Loading weights [{sd_model_hash}]{vae_message} from cache")
		model.load_state_dict(checkpoints_loaded[checkpoint_info])
		else:
		# load from file
		print(f"Loading weights [{sd_model_hash}] from {checkpoint_file}")

		pl_sd = torch.load(checkpoint_file, map_location=shared.weight_load_location)
		@@ -181,6 +189,10 @@ def load_model_weights(model, checkpoint_info, vae_file="auto"):
		model.load_state_dict(sd, strict=False)
		del sd

		if cache_enabled:
		# cache newly loaded model
		checkpoints_loaded[checkpoint_info] = model.state_dict().copy()

		if shared.cmd_opts.opt_channelslast:
		model.to(memory_format=torch.channels_last)

		@@ -199,14 +211,9 @@ def load_model_weights(model, checkpoint_info, vae_file="auto"):

		model.first_stage_model.to(devices.dtype_vae)

		else:
		vae_name = sd_vae.get_filename(vae_file) if vae_file else None
		vae_message = f" with {vae_name} VAE" if vae_name else ""
		print(f"Loading weights [{sd_model_hash}]{vae_message} from cache")
		model.load_state_dict(checkpoints_loaded[checkpoint_info])

		if shared.opts.sd_checkpoint_cache > 0:
		while len(checkpoints_loaded) > shared.opts.sd_checkpoint_cache:
		# clean up cache if limit is reached
		if cache_enabled:
		while len(checkpoints_loaded) > shared.opts.sd_checkpoint_cache + 1: # we need to count the current model
		checkpoints_loaded.popitem(last=False) # LRU

		model.sd_model_hash = sd_model_hash

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