diff --git a/modules/extras.py b/modules/extras.py index 0057bf9c..6021a024 100644 --- a/modules/extras.py +++ b/modules/extras.py @@ -1,6 +1,8 @@ from __future__ import annotations import math import os +import sys +import traceback import numpy as np from PIL import Image @@ -12,7 +14,7 @@ from typing import Callable, List, OrderedDict, Tuple from functools import partial from dataclasses import dataclass -from modules import processing, shared, images, devices, sd_models +from modules import processing, shared, images, devices, sd_models, sd_samplers from modules.shared import opts import modules.gfpgan_model from modules.ui import plaintext_to_html @@ -22,7 +24,6 @@ import piexif.helper import gradio as gr import safetensors.torch - class LruCache(OrderedDict): @dataclass(frozen=True) class Key: @@ -214,39 +215,8 @@ def run_pnginfo(image): if image is None: return '', '', '' - items = image.info - geninfo = '' - - if "exif" in image.info: - exif = piexif.load(image.info["exif"]) - exif_comment = (exif or {}).get("Exif", {}).get(piexif.ExifIFD.UserComment, b'') - try: - exif_comment = piexif.helper.UserComment.load(exif_comment) - except ValueError: - exif_comment = exif_comment.decode('utf8', errors="ignore") - - items['exif comment'] = exif_comment - geninfo = exif_comment - - for field in ['jfif', 'jfif_version', 'jfif_unit', 'jfif_density', 'dpi', 'exif', - 'loop', 'background', 'timestamp', 'duration']: - items.pop(field, None) - - geninfo = items.get('parameters', geninfo) - - # nai prompt - if "Software" in items.keys() and items["Software"] == "NovelAI": - import json - json_info = json.loads(items["Comment"]) - geninfo = f'{items["Description"]}\r\nNegative prompt: {json_info["uc"]}\r\n' - sampler = "Euler a" - if json_info["sampler"] == "k_euler_ancestral": - sampler = "Euler a" - elif json_info["sampler"] == "k_euler": - sampler = "Euler" - model_hash = '925997e9' # assuming this is the correct model hash - # not sure with noise and strength parameter - geninfo += f'Steps: {json_info["steps"]}, Sampler: {sampler}, CFG scale: {json_info["scale"]}, Seed: {json_info["seed"]}, Size: {image.width}x{image.height}, Model hash: {model_hash}' # , Denoising strength: {json_info["noise"]}' + geninfo, items = images.read_info_from_image(image) + items = {**{'parameters': geninfo}, **items} info = '' for key, text in items.items(): diff --git a/modules/generation_parameters_copypaste.py b/modules/generation_parameters_copypaste.py index 1408ea05..0973c695 100644 --- a/modules/generation_parameters_copypaste.py +++ b/modules/generation_parameters_copypaste.py @@ -75,6 +75,7 @@ def integrate_settings_paste_fields(component_dict): 'CLIP_stop_at_last_layers': 'Clip skip', 'inpainting_mask_weight': 'Conditional mask weight', 'sd_model_checkpoint': 'Model hash', + 'eta_noise_seed_delta': 'ENSD', } settings_paste_fields = [ (component_dict[k], lambda d, k=k, v=v: ui.apply_setting(k, d.get(v, None))) diff --git a/modules/images.py b/modules/images.py index b968d6a6..08a72e67 100644 --- a/modules/images.py +++ b/modules/images.py @@ -15,6 +15,7 @@ import piexif.helper from PIL import Image, ImageFont, ImageDraw, PngImagePlugin from fonts.ttf import Roboto import string +import json from modules import sd_samplers, shared, script_callbacks from modules.shared import opts, cmd_opts @@ -553,10 +554,45 @@ def save_image(image, path, basename, seed=None, prompt=None, extension='png', i return fullfn, txt_fullfn +def read_info_from_image(image): + items = image.info or {} + + geninfo = items.pop('parameters', None) + + if "exif" in items: + exif = piexif.load(items["exif"]) + exif_comment = (exif or {}).get("Exif", {}).get(piexif.ExifIFD.UserComment, b'') + try: + exif_comment = piexif.helper.UserComment.load(exif_comment) + except ValueError: + exif_comment = exif_comment.decode('utf8', errors="ignore") + + items['exif comment'] = exif_comment + geninfo = exif_comment + + for field in ['jfif', 'jfif_version', 'jfif_unit', 'jfif_density', 'dpi', 'exif', + 'loop', 'background', 'timestamp', 'duration']: + items.pop(field, None) + + if items.get("Software", None) == "NovelAI": + try: + json_info = json.loads(items["Comment"]) + sampler = sd_samplers.samplers_map.get(json_info["sampler"], "Euler a") + + geninfo = f"""{items["Description"]} +Negative prompt: {json_info["uc"]} +Steps: {json_info["steps"]}, Sampler: {sampler}, CFG scale: {json_info["scale"]}, Seed: {json_info["seed"]}, Size: {image.width}x{image.height}, Clip skip: 2, ENSD: 31337""" + except Exception: + print(f"Error parsing NovelAI iamge generation parameters:", file=sys.stderr) + print(traceback.format_exc(), file=sys.stderr) + + return geninfo, items + + def image_data(data): try: image = Image.open(io.BytesIO(data)) - textinfo = image.text["parameters"] + textinfo, _ = read_info_from_image(image) return textinfo, None except Exception: pass diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py index 2ca17d8b..5fefb227 100644 --- a/modules/sd_samplers.py +++ b/modules/sd_samplers.py @@ -18,7 +18,7 @@ from modules.script_callbacks import CFGDenoiserParams, cfg_denoiser_callback SamplerData = namedtuple('SamplerData', ['name', 'constructor', 'aliases', 'options']) samplers_k_diffusion = [ - ('Euler a', 'sample_euler_ancestral', ['k_euler_a'], {}), + ('Euler a', 'sample_euler_ancestral', ['k_euler_a', 'k_euler_ancestral'], {}), ('Euler', 'sample_euler', ['k_euler'], {}), ('LMS', 'sample_lms', ['k_lms'], {}), ('Heun', 'sample_heun', ['k_heun'], {}),