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Merge branch 'feature/add-metadata-to-files'

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# Conflicts:
#	args_manager.py
#	modules/async_worker.py
#	modules/config.py
#	modules/private_logger.py
#	modules/util.py
This commit is contained in:
Manuel Schmid
2024-01-16 00:50:46 +01:00
parent 3e9d66c5f6 ba5d0b6eaf
commit addd5ef3bd
8 changed files with 193 additions and 8 deletions
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modules/async_worker.py
+116 -3
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@@ -15,8 +15,11 @@ async_tasks = []
def worker():
global async_tasks
import os
import traceback
import math
import json
import numpy as np
import torch
import time
@@ -36,6 +39,7 @@ def worker():
import extras.ip_adapter as ip_adapter
import extras.face_crop
import fooocus_version
import args_manager
from modules.censor import censor_batch
@@ -43,7 +47,7 @@ def worker():
from modules.private_logger import log
from extras.expansion import safe_str
from modules.util import remove_empty_str, HWC3, resize_image, \
get_image_shape_ceil, set_image_shape_ceil, get_shape_ceil, resample_image, erode_or_dilate
get_image_shape_ceil, set_image_shape_ceil, get_shape_ceil, resample_image, erode_or_dilate, calculate_sha256, quote
from modules.upscaler import perform_upscale
try:
@@ -150,6 +154,8 @@ def worker():
inpaint_input_image = args.pop()
inpaint_additional_prompt = args.pop()
inpaint_mask_image_upload = args.pop()
save_metadata_to_images = args.pop() if not args_manager.args.disable_metadata else False
metadata_scheme = args.pop() if not args_manager.args.disable_metadata else 'fooocus'
cn_tasks = {x: [] for x in flags.ip_list}
for _ in range(4):
@@ -212,6 +218,17 @@ def worker():
prompt = translate2en(prompt, 'prompt')
negative_prompt = translate2en(negative_prompt, 'negative prompt')
if not args_manager.args.disable_metadata:
base_model_path = os.path.join(modules.config.path_checkpoints, base_model_name)
base_model_hash = calculate_sha256(base_model_path)[0:10]
lora_hashes = []
for (n, w) in loras:
if n != 'None':
lora_path = os.path.join(modules.config.path_loras, n)
lora_hashes.append(f'{n.split(".")[0]}: {calculate_sha256(lora_path)[0:10]}')
lora_hashes_string = ", ".join(lora_hashes)
modules.patch.adaptive_cfg = advanced_parameters.adaptive_cfg
print(f'[Parameters] Adaptive CFG = {modules.patch.adaptive_cfg}')
@@ -369,6 +386,9 @@ def worker():
progressbar(async_task, 1, 'Initializing ...')
raw_prompt = prompt
raw_negative_prompt = negative_prompt
if not skip_prompt_processing:
prompts = remove_empty_str([safe_str(p) for p in prompt.splitlines()], default='')
@@ -527,7 +547,7 @@ def worker():
if direct_return:
d = [('Upscale (Fast)', '2x')]
uov_input_image_path = log(uov_input_image, d, image_file_extension)
uov_input_image_path = log(uov_input_image, d, image_file_extension=image_file_extension)
yield_result(async_task, uov_input_image_path, do_not_show_finished_images=True)
return
@@ -793,6 +813,99 @@ def worker():
imgs = [inpaint_worker.current_task.post_process(x) for x in imgs]
img_paths = []
metadata_string = ''
if save_metadata_to_images and metadata_scheme == 'fooocus':
metadata = {
'prompt': raw_prompt, 'negative_prompt': raw_negative_prompt, 'styles': str(raw_style_selections),
'real_prompt': task['log_positive_prompt'], 'real_negative_prompt': task['log_negative_prompt'],
'seed': task['task_seed'], 'width': width, 'height': height,
'sampler': sampler_name, 'scheduler': scheduler_name, 'performance': performance_selection,
'steps': steps, 'refiner_switch': refiner_switch, 'sharpness': sharpness, 'cfg': cfg_scale,
'base_model': base_model_name, 'refiner_model': refiner_model_name,
'denoising_strength': denoising_strength,
'freeu': advanced_parameters.freeu_enabled,
'img2img': input_image_checkbox,
'prompt_expansion': task['expansion']
}
if advanced_parameters.freeu_enabled:
metadata |= {
'freeu_b1': advanced_parameters.freeu_b1, 'freeu_b2': advanced_parameters.freeu_b2, 'freeu_s1': advanced_parameters.freeu_s1, 'freeu_s2': advanced_parameters.freeu_s2
}
if 'vary' in goals:
metadata |= {
'uov_method': uov_method
}
if 'upscale' in goals:
metadata |= {
'uov_method': uov_method, 'scale': f
}
if 'inpaint' in goals:
if len(outpaint_selections) > 0:
metadata |= {
'outpaint_selections': outpaint_selections
}
else:
metadata |= {
'inpaint_additional_prompt': inpaint_additional_prompt, 'inpaint_mask_upload': advanced_parameters.inpaint_mask_upload_checkbox, 'invert_mask': advanced_parameters.invert_mask_checkbox,
'inpaint_disable_initial_latent': advanced_parameters.inpaint_disable_initial_latent, 'inpaint_engine': advanced_parameters.inpaint_engine,
'inpaint_strength': advanced_parameters.inpaint_strength, 'inpaint_respective_field': advanced_parameters.inpaint_respective_field,
}
if 'cn' in goals:
metadata |= {
'canny_low_threshold': advanced_parameters.canny_low_threshold, 'canny_high_threshold': advanced_parameters.canny_high_threshold,
}
ip_list = {x: [] for x in flags.ip_list}
cn_task_index = 1
for cn_type in ip_list:
for cn_task in cn_tasks[cn_type]:
cn_img, cn_stop, cn_weight = cn_task
metadata |= {
f'image_prompt_{cn_task_index}': {
'cn_type': cn_type, 'cn_stop': cn_stop, 'cn_weight': cn_weight,
}
}
cn_task_index += 1
metadata |= {
'software': f'Fooocus v{fooocus_version.version}',
}
if modules.config.metadata_created_by != 'None':
metadata |= {
'created_by': modules.config.metadata_created_by
}
metadata_string = json.dumps(metadata, ensure_ascii=False)
elif save_metadata_to_images and metadata_scheme == 'a1111':
generation_params = {
"Steps": steps,
"Sampler": sampler_name,
"CFG scale": cfg_scale,
"Seed": task['task_seed'],
"Size": f"{width}x{height}",
"Model hash": base_model_hash,
"Model": base_model_name.split('.')[0],
"Lora hashes": lora_hashes_string,
"Denoising strength": denoising_strength,
"Version": f'Fooocus v{fooocus_version.version}'
}
if modules.config.metadata_created_by != 'None':
generation_params |= {
'Created By': f'{modules.config.metadata_created_by}'
}
generation_params_text = ", ".join([k if k == v else f'{k}: {quote(v)}' for k, v in generation_params.items() if v is not None])
positive_prompt_resolved = ', '.join(task['positive'])
negative_prompt_resolved = ', '.join(task['negative'])
negative_prompt_text = f"\nNegative prompt: {negative_prompt_resolved}" if negative_prompt_resolved else ""
metadata_string = f"{positive_prompt_resolved}{negative_prompt_text}\n{generation_params_text}".strip()
for x in imgs:
d = [
('Prompt', task['log_positive_prompt']),
@@ -819,7 +932,7 @@ def worker():
if n != 'None':
d.append((f'LoRA {li + 1}', f'{n} : {w}'))
d.append(('Version', 'v' + fooocus_version.version))
img_paths.append(log(x, d, image_file_extension))
img_paths.append(log(x, d, metadata_string, save_metadata_to_images, image_file_extension))
yield_result(async_task, img_paths, do_not_show_finished_images=len(tasks) == 1, progressbar_index=int(15.0 + 85.0 * float((current_task_id + 1) * steps) / float(all_steps)))
except ldm_patched.modules.model_management.InterruptProcessingException as e: