From 904121fecc0a1f11db76a73ca8649fb21e05ac5b Mon Sep 17 00:00:00 2001 From: Nandaka Date: Thu, 24 Nov 2022 02:39:09 +0000 Subject: Support NAI exif for PNG Info --- modules/extras.py | 14 ++++++++++++++ 1 file changed, 14 insertions(+) (limited to 'modules/extras.py') diff --git a/modules/extras.py b/modules/extras.py index 71b93a06..af4cd97d 100644 --- a/modules/extras.py +++ b/modules/extras.py @@ -233,6 +233,20 @@ def run_pnginfo(image): 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"]}' + info = '' for key, text in items.items(): info += f""" -- cgit v1.2.1 From dac9b6f15de5e675053d9490a20e0457dcd1a23e Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sun, 27 Nov 2022 15:51:29 +0300 Subject: add safetensors support for model merging #4869 --- modules/extras.py | 26 ++++++++++++++------------ 1 file changed, 14 insertions(+), 12 deletions(-) (limited to 'modules/extras.py') diff --git a/modules/extras.py b/modules/extras.py index 71b93a06..3d65d90a 100644 --- a/modules/extras.py +++ b/modules/extras.py @@ -20,6 +20,7 @@ import modules.codeformer_model import piexif import piexif.helper import gradio as gr +import safetensors.torch class LruCache(OrderedDict): @@ -249,7 +250,7 @@ def run_pnginfo(image): return '', geninfo, info -def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_name, interp_method, multiplier, save_as_half, custom_name): +def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_name, interp_method, multiplier, save_as_half, custom_name, checkpoint_format): def weighted_sum(theta0, theta1, alpha): return ((1 - alpha) * theta0) + (alpha * theta1) @@ -264,19 +265,15 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam teritary_model_info = sd_models.checkpoints_list.get(teritary_model_name, None) print(f"Loading {primary_model_info.filename}...") - primary_model = torch.load(primary_model_info.filename, map_location='cpu') - theta_0 = sd_models.get_state_dict_from_checkpoint(primary_model) + theta_0 = sd_models.read_state_dict(primary_model_info.filename, map_location='cpu') print(f"Loading {secondary_model_info.filename}...") - secondary_model = torch.load(secondary_model_info.filename, map_location='cpu') - theta_1 = sd_models.get_state_dict_from_checkpoint(secondary_model) + theta_1 = sd_models.read_state_dict(secondary_model_info.filename, map_location='cpu') if teritary_model_info is not None: print(f"Loading {teritary_model_info.filename}...") - teritary_model = torch.load(teritary_model_info.filename, map_location='cpu') - theta_2 = sd_models.get_state_dict_from_checkpoint(teritary_model) + theta_2 = sd_models.read_state_dict(teritary_model_info.filename, map_location='cpu') else: - teritary_model = None theta_2 = None theta_funcs = { @@ -295,7 +292,7 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam theta_1[key] = theta_func1(theta_1[key], t2) else: theta_1[key] = torch.zeros_like(theta_1[key]) - del theta_2, teritary_model + del theta_2 for key in tqdm.tqdm(theta_0.keys()): if 'model' in key and key in theta_1: @@ -314,12 +311,17 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam ckpt_dir = shared.cmd_opts.ckpt_dir or sd_models.model_path - filename = primary_model_info.model_name + '_' + str(round(1-multiplier, 2)) + '-' + secondary_model_info.model_name + '_' + str(round(multiplier, 2)) + '-' + interp_method.replace(" ", "_") + '-merged.ckpt' - filename = filename if custom_name == '' else (custom_name + '.ckpt') + filename = primary_model_info.model_name + '_' + str(round(1-multiplier, 2)) + '-' + secondary_model_info.model_name + '_' + str(round(multiplier, 2)) + '-' + interp_method.replace(" ", "_") + '-merged.' + checkpoint_format + filename = filename if custom_name == '' else (custom_name + '.' + checkpoint_format) output_modelname = os.path.join(ckpt_dir, filename) print(f"Saving to {output_modelname}...") - torch.save(primary_model, output_modelname) + + _, extension = os.path.splitext(output_modelname) + if extension.lower() == ".safetensors": + safetensors.torch.save_file(theta_0, output_modelname, metadata={"format": "pt"}) + else: + torch.save(theta_0, output_modelname) sd_models.list_models() -- cgit v1.2.1 From 506d529d19f135f57e142371271f84d4971b456f Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sun, 27 Nov 2022 16:28:32 +0300 Subject: rework #5012 to also work for pictures dragged into the prompt and also add Clip skip + ENSD to parameters --- modules/extras.py | 40 +++++----------------------------------- 1 file changed, 5 insertions(+), 35 deletions(-) (limited to 'modules/extras.py') 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(): -- cgit v1.2.1 From 44c46f0ed395967cd3830dd481a2db759fda5b3b Mon Sep 17 00:00:00 2001 From: AUTOMATIC <16777216c@gmail.com> Date: Sun, 4 Dec 2022 12:30:44 +0300 Subject: make it possible to merge inpainting model with non-inpainting one --- modules/extras.py | 27 +++++++++++++++++++++++++-- 1 file changed, 25 insertions(+), 2 deletions(-) (limited to 'modules/extras.py') diff --git a/modules/extras.py b/modules/extras.py index 6021a024..bc349d5e 100644 --- a/modules/extras.py +++ b/modules/extras.py @@ -247,6 +247,7 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam primary_model_info = sd_models.checkpoints_list[primary_model_name] secondary_model_info = sd_models.checkpoints_list[secondary_model_name] teritary_model_info = sd_models.checkpoints_list.get(teritary_model_name, None) + result_is_inpainting_model = False print(f"Loading {primary_model_info.filename}...") theta_0 = sd_models.read_state_dict(primary_model_info.filename, map_location='cpu') @@ -280,8 +281,22 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam for key in tqdm.tqdm(theta_0.keys()): if 'model' in key and key in theta_1: + a = theta_0[key] + b = theta_1[key] - theta_0[key] = theta_func2(theta_0[key], theta_1[key], multiplier) + # this enables merging an inpainting model (A) with another one (B); + # where normal model would have 4 channels, for latenst space, inpainting model would + # have another 4 channels for unmasked picture's latent space, plus one channel for mask, for a total of 9 + if a.shape != b.shape and a.shape[0:1] + a.shape[2:] == b.shape[0:1] + b.shape[2:]: + if a.shape[1] == 4 and b.shape[1] == 9: + raise RuntimeError("When merging inpainting model with a normal one, A must be the inpainting model.") + + assert a.shape[1] == 9 and b.shape[1] == 4, f"Bad dimensions for merged layer {key}: A={a.shape}, B={b.shape}" + + theta_0[key][:, 0:4, :, :] = theta_func2(a[:, 0:4, :, :], b, multiplier) + result_is_inpainting_model = True + else: + theta_0[key] = theta_func2(a, b, multiplier) if save_as_half: theta_0[key] = theta_0[key].half() @@ -295,8 +310,16 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam ckpt_dir = shared.cmd_opts.ckpt_dir or sd_models.model_path - filename = primary_model_info.model_name + '_' + str(round(1-multiplier, 2)) + '-' + secondary_model_info.model_name + '_' + str(round(multiplier, 2)) + '-' + interp_method.replace(" ", "_") + '-merged.' + checkpoint_format + filename = \ + primary_model_info.model_name + '_' + str(round(1-multiplier, 2)) + '-' + \ + secondary_model_info.model_name + '_' + str(round(multiplier, 2)) + '-' + \ + interp_method.replace(" ", "_") + \ + '-merged.' + \ + ("inpainting." if result_is_inpainting_model else "") + \ + checkpoint_format + filename = filename if custom_name == '' else (custom_name + '.' + checkpoint_format) + output_modelname = os.path.join(ckpt_dir, filename) print(f"Saving to {output_modelname}...") -- cgit v1.2.1 From 681c450ecd8f0999cbaf562c5e734c7105320ad9 Mon Sep 17 00:00:00 2001 From: Mackerel Date: Sun, 4 Dec 2022 01:13:36 -0500 Subject: extras.py: use as little RAM as possible, misc fixes maximum of 2 models loaded at once. delete unneeded model before next step. fix 'teritary' -> 'tertiary'. gracefully fail when "add difference" is selected without a tertiary model --- modules/extras.py | 37 +++++++++++++++++++------------------ 1 file changed, 19 insertions(+), 18 deletions(-) (limited to 'modules/extras.py') diff --git a/modules/extras.py b/modules/extras.py index bc349d5e..0ad8deec 100644 --- a/modules/extras.py +++ b/modules/extras.py @@ -62,7 +62,7 @@ def run_extras(extras_mode, resize_mode, image, image_folder, input_dir, output_ # Also keep track of original file names imageNameArr = [] outputs = [] - + if extras_mode == 1: #convert file to pillow image for img in image_folder: @@ -234,7 +234,7 @@ def run_pnginfo(image): return '', geninfo, info -def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_name, interp_method, multiplier, save_as_half, custom_name, checkpoint_format): +def run_modelmerger(primary_model_name, secondary_model_name, tertiary_model_name, interp_method, multiplier, save_as_half, custom_name, checkpoint_format): def weighted_sum(theta0, theta1, alpha): return ((1 - alpha) * theta0) + (alpha * theta1) @@ -246,30 +246,25 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam primary_model_info = sd_models.checkpoints_list[primary_model_name] secondary_model_info = sd_models.checkpoints_list[secondary_model_name] - teritary_model_info = sd_models.checkpoints_list.get(teritary_model_name, None) + tertiary_model_info = sd_models.checkpoints_list.get(tertiary_model_name, None) result_is_inpainting_model = False - print(f"Loading {primary_model_info.filename}...") - theta_0 = sd_models.read_state_dict(primary_model_info.filename, map_location='cpu') - - print(f"Loading {secondary_model_info.filename}...") - theta_1 = sd_models.read_state_dict(secondary_model_info.filename, map_location='cpu') - - if teritary_model_info is not None: - print(f"Loading {teritary_model_info.filename}...") - theta_2 = sd_models.read_state_dict(teritary_model_info.filename, map_location='cpu') - else: - theta_2 = None - theta_funcs = { "Weighted sum": (None, weighted_sum), "Add difference": (get_difference, add_difference), } theta_func1, theta_func2 = theta_funcs[interp_method] - print(f"Merging...") + if theta_func1 and not tertiary_model_info: + return ["Failed: Interpolation method requires a tertiary model."] + [gr.Dropdown.update(choices=sd_models.checkpoint_tiles()) for _ in range(4)] + + print(f"Loading {secondary_model_info.filename}...") + theta_1 = sd_models.read_state_dict(secondary_model_info.filename, map_location='cpu') if theta_func1: + print(f"Loading {tertiary_model_info.filename}...") + theta_2 = sd_models.read_state_dict(tertiary_model_info.filename, map_location='cpu') + for key in tqdm.tqdm(theta_1.keys()): if 'model' in key: if key in theta_2: @@ -277,7 +272,12 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam theta_1[key] = theta_func1(theta_1[key], t2) else: theta_1[key] = torch.zeros_like(theta_1[key]) - del theta_2 + del theta_2 + + print(f"Loading {primary_model_info.filename}...") + theta_0 = sd_models.read_state_dict(primary_model_info.filename, map_location='cpu') + + print("Merging...") for key in tqdm.tqdm(theta_0.keys()): if 'model' in key and key in theta_1: @@ -307,6 +307,7 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam theta_0[key] = theta_1[key] if save_as_half: theta_0[key] = theta_0[key].half() + del theta_1 ckpt_dir = shared.cmd_opts.ckpt_dir or sd_models.model_path @@ -332,5 +333,5 @@ def run_modelmerger(primary_model_name, secondary_model_name, teritary_model_nam sd_models.list_models() - print(f"Checkpoint saved.") + print("Checkpoint saved.") return ["Checkpoint saved to " + output_modelname] + [gr.Dropdown.update(choices=sd_models.checkpoint_tiles()) for _ in range(4)] -- cgit v1.2.1