mirror of
https://github.com/AUTOMATIC1111/stable-diffusion-webui.git
synced 2025-08-03 10:50:23 +00:00
add images.read to automatically fix all jpeg/png weirdness
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@@ -6,7 +6,7 @@ import numpy as np
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from PIL import Image, ImageOps, ImageFilter, ImageEnhance, UnidentifiedImageError
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import gradio as gr
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from modules import images as imgutil
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from modules import images
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from modules.infotext_utils import create_override_settings_dict, parse_generation_parameters
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from modules.processing import Processed, StableDiffusionProcessingImg2Img, process_images
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from modules.shared import opts, state
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@@ -21,7 +21,7 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args, to_scale=Fal
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output_dir = output_dir.strip()
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processing.fix_seed(p)
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images = list(shared.walk_files(input_dir, allowed_extensions=(".png", ".jpg", ".jpeg", ".webp", ".tif", ".tiff")))
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batch_images = list(shared.walk_files(input_dir, allowed_extensions=(".png", ".jpg", ".jpeg", ".webp", ".tif", ".tiff")))
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is_inpaint_batch = False
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if inpaint_mask_dir:
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@@ -31,9 +31,9 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args, to_scale=Fal
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if is_inpaint_batch:
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print(f"\nInpaint batch is enabled. {len(inpaint_masks)} masks found.")
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print(f"Will process {len(images)} images, creating {p.n_iter * p.batch_size} new images for each.")
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print(f"Will process {len(batch_images)} images, creating {p.n_iter * p.batch_size} new images for each.")
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state.job_count = len(images) * p.n_iter
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state.job_count = len(batch_images) * p.n_iter
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# extract "default" params to use in case getting png info fails
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prompt = p.prompt
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@@ -46,8 +46,8 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args, to_scale=Fal
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sd_model_checkpoint_override = get_closet_checkpoint_match(override_settings.get("sd_model_checkpoint", None))
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batch_results = None
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discard_further_results = False
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for i, image in enumerate(images):
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state.job = f"{i+1} out of {len(images)}"
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for i, image in enumerate(batch_images):
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state.job = f"{i+1} out of {len(batch_images)}"
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if state.skipped:
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state.skipped = False
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@@ -55,7 +55,7 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args, to_scale=Fal
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break
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try:
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img = Image.open(image)
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img = images.read(image)
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except UnidentifiedImageError as e:
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print(e)
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continue
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@@ -86,7 +86,7 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args, to_scale=Fal
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# otherwise user has many masks with the same name but different extensions
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mask_image_path = masks_found[0]
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mask_image = Image.open(mask_image_path)
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mask_image = images.read(mask_image_path)
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p.image_mask = mask_image
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if use_png_info:
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@@ -94,8 +94,8 @@ def process_batch(p, input_dir, output_dir, inpaint_mask_dir, args, to_scale=Fal
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info_img = img
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if png_info_dir:
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info_img_path = os.path.join(png_info_dir, os.path.basename(image))
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info_img = Image.open(info_img_path)
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geninfo, _ = imgutil.read_info_from_image(info_img)
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info_img = images.read(info_img_path)
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geninfo, _ = images.read_info_from_image(info_img)
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parsed_parameters = parse_generation_parameters(geninfo)
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parsed_parameters = {k: v for k, v in parsed_parameters.items() if k in (png_info_props or {})}
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except Exception:
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@@ -175,9 +175,8 @@ def img2img(id_task: str, mode: int, prompt: str, negative_prompt: str, prompt_s
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image = None
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mask = None
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# Use the EXIF orientation of photos taken by smartphones.
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if image is not None:
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image = ImageOps.exif_transpose(image)
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image = images.fix_image(image)
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mask = images.fix_image(mask)
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if selected_scale_tab == 1 and not is_batch:
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assert image, "Can't scale by because no image is selected"
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