add job info to modules (192ddc04) · Commits · github_fork / Stable Diffusion Webui

modules/extras.py

+13 −4

Original line number	Diff line number	Diff line
		@@ -58,6 +58,9 @@ cached_images: LruCache = LruCache(max_size=5)
		def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_dir, show_extras_results, gfpgan_visibility, codeformer_visibility, codeformer_weight, upscaling_resize, upscaling_resize_w, upscaling_resize_h, upscaling_crop, extras_upscaler_1, extras_upscaler_2, extras_upscaler_2_visibility, upscale_first: bool, save_output: bool = True):
		devices.torch_gc()

		shared.state.begin()
		shared.state.job = 'extras'

		imageArr = []
		# Also keep track of original file names
		imageNameArr = []
		@@ -94,6 +97,7 @@ def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_
		# Extra operation definitions

		def run_gfpgan(image: Image.Image, info: str) -> Tuple[Image.Image, str]:
		shared.state.job = 'extras-gfpgan'
		restored_img = modules.gfpgan_model.gfpgan_fix_faces(np.array(image, dtype=np.uint8))
		res = Image.fromarray(restored_img)

		@@ -104,6 +108,7 @@ def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_
		return (res, info)

		def run_codeformer(image: Image.Image, info: str) -> Tuple[Image.Image, str]:
		shared.state.job = 'extras-codeformer'
		restored_img = modules.codeformer_model.codeformer.restore(np.array(image, dtype=np.uint8), w=codeformer_weight)
		res = Image.fromarray(restored_img)

		@@ -114,6 +119,7 @@ def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_
		return (res, info)

		def upscale(image, scaler_index, resize, mode, resize_w, resize_h, crop):
		shared.state.job = 'extras-upscale'
		upscaler = shared.sd_upscalers[scaler_index]
		res = upscaler.scaler.upscale(image, resize, upscaler.data_path)
		if mode == 1 and crop:
		@@ -180,6 +186,9 @@ def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_
		for image, image_name in zip(imageArr, imageNameArr):
		if image is None:
		return outputs, "Please select an input image.", ''

		shared.state.textinfo = f'Processing image {image_name}'

		existing_pnginfo = image.info or {}

		image = image.convert("RGB")
		@@ -193,6 +202,10 @@ def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_
		else:
		basename = ''

		if opts.enable_pnginfo: # append info before save
		image.info = existing_pnginfo
		image.info["extras"] = info

		if save_output:
		# Add upscaler name as a suffix.
		suffix = f"-{shared.sd_upscalers[extras_upscaler_1].name}" if shared.opts.use_upscaler_name_as_suffix else ""
		@@ -203,10 +216,6 @@ def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_
		images.save_image(image, path=outpath, basename=basename, seed=None, prompt=None, extension=opts.samples_format, info=info, short_filename=True,
		no_prompt=True, grid=False, pnginfo_section_name="extras", existing_info=existing_pnginfo, forced_filename=None, suffix=suffix)

		if opts.enable_pnginfo:
		image.info = existing_pnginfo
		image.info["extras"] = info

		if extras_mode != 2 or show_extras_results :
		outputs.append(image)

modules/hypernetworks/hypernetwork.py

+1 −0

Original line number	Diff line number	Diff line
		@@ -417,6 +417,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, gradient_step,
		shared.loaded_hypernetwork = Hypernetwork()
		shared.loaded_hypernetwork.load(path)

		shared.state.job = "train-hypernetwork"
		shared.state.textinfo = "Initializing hypernetwork training..."
		shared.state.job_count = steps

modules/textual_inversion/preprocess.py

+1 −0

Original line number	Diff line number	Diff line
		@@ -124,6 +124,7 @@ def preprocess_work(process_src, process_dst, process_width, process_height, pre

		files = listfiles(src)

		shared.state.job = "preprocess"
		shared.state.textinfo = "Preprocessing..."
		shared.state.job_count = len(files)

modules/textual_inversion/textual_inversion.py

+1 −0

Original line number	Diff line number	Diff line
		@@ -245,6 +245,7 @@ def train_embedding(embedding_name, learn_rate, batch_size, gradient_step, data_
		create_image_every = create_image_every or 0
		validate_train_inputs(embedding_name, learn_rate, batch_size, gradient_step, data_root, template_file, steps, save_embedding_every, create_image_every, log_directory, name="embedding")

		shared.state.job = "train-embedding"
		shared.state.textinfo = "Initializing textual inversion training..."
		shared.state.job_count = steps

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