diff --git a/fooocus_version.py b/fooocus_version.py
index e6638147..37962c77 100644
--- a/fooocus_version.py
+++ b/fooocus_version.py
@@ -1 +1 @@
-version = '1.0.67'
+version = '2.0.0'
diff --git a/modules/async_worker.py b/modules/async_worker.py
index 9fe4cd4f..57818a3e 100644
--- a/modules/async_worker.py
+++ b/modules/async_worker.py
@@ -11,14 +11,15 @@ def worker():
import time
import shared
import random
+ import copy
import modules.default_pipeline as pipeline
import modules.path
import modules.patch
- from modules.sdxl_styles import apply_style_negative, apply_style_positive, aspect_ratios
+ from modules.sdxl_styles import apply_style, aspect_ratios, fooocus_expansion
from modules.private_logger import log
from modules.expansion import safe_str
- from modules.util import join_prompts
+ from modules.util import join_prompts, remove_empty_str
try:
async_gradio_app = shared.gradio_root
@@ -29,20 +30,42 @@ def worker():
except Exception as e:
print(e)
+ def progressbar(number, text):
+ outputs.append(['preview', (number, text, None)])
+
def handler(task):
- prompt, negative_prompt, style_selction, performance_selction, \
- aspect_ratios_selction, image_number, image_seed, sharpness, raw_mode, \
+ prompt, negative_prompt, style_selections, performance_selction, \
+ aspect_ratios_selction, image_number, image_seed, sharpness, \
base_model_name, refiner_model_name, \
l1, w1, l2, w2, l3, w3, l4, w4, l5, w5 = task
loras = [(l1, w1), (l2, w2), (l3, w3), (l4, w4), (l5, w5)]
+ raw_style_selections = copy.deepcopy(style_selections)
+
+ if fooocus_expansion in style_selections:
+ use_expansion = True
+ style_selections.remove(fooocus_expansion)
+ else:
+ use_expansion = False
+
+ use_style = len(style_selections) > 0
+
modules.patch.sharpness = sharpness
- outputs.append(['preview', (1, 'Initializing ...', None)])
+ progressbar(1, 'Initializing ...')
- prompt = safe_str(prompt)
- negative_prompt = safe_str(negative_prompt)
+ raw_prompt = prompt
+ raw_negative_prompt = negative_prompt
+
+ prompts = remove_empty_str([safe_str(p) for p in prompt.split('\n')], default='')
+ negative_prompts = remove_empty_str([safe_str(p) for p in negative_prompt.split('\n')], default='')
+
+ prompt = prompts[0]
+ negative_prompt = negative_prompts[0]
+
+ extra_positive_prompts = prompts[1:] if len(prompts) > 1 else []
+ extra_negative_prompts = negative_prompts[1:] if len(negative_prompts) > 1 else []
seed = image_seed
max_seed = int(1024 * 1024 * 1024)
@@ -52,63 +75,74 @@ def worker():
seed = - seed
seed = seed % max_seed
- outputs.append(['preview', (3, 'Load models ...', None)])
+ progressbar(3, 'Loading models ...')
pipeline.refresh_base_model(base_model_name)
pipeline.refresh_refiner_model(refiner_model_name)
pipeline.refresh_loras(loras)
+ pipeline.clear_all_caches()
- tasks = []
- if raw_mode:
- outputs.append(['preview', (5, 'Encoding negative text ...', None)])
- n_txt = apply_style_negative(style_selction, negative_prompt)
- n_cond = pipeline.process_prompt(n_txt)
- outputs.append(['preview', (9, 'Encoding positive text ...', None)])
- p_txt = apply_style_positive(style_selction, prompt)
- p_cond = pipeline.process_prompt(p_txt)
+ progressbar(3, 'Processing prompts ...')
- for i in range(image_number):
- tasks.append(dict(
- prompt=prompt,
- negative_prompt=negative_prompt,
- seed=seed + i,
- n_cond=n_cond,
- p_cond=p_cond,
- real_positive_prompt=p_txt,
- real_negative_prompt=n_txt
- ))
+ positive_basic_workloads = []
+ negative_basic_workloads = []
+
+ if use_style:
+ for s in style_selections:
+ p, n = apply_style(s, positive=prompt)
+ positive_basic_workloads.append(p)
+ negative_basic_workloads.append(n)
else:
- for i in range(image_number):
- outputs.append(['preview', (5, f'Preparing positive text #{i + 1} ...', None)])
- current_seed = seed + i
+ positive_basic_workloads.append(prompt)
- expansion_weight = 0.1
+ negative_basic_workloads.append(negative_prompt) # Always use independent workload for negative.
- suffix = pipeline.expansion(prompt, current_seed)
- suffix = f'({suffix}:{expansion_weight})'
- print(f'[Prompt Expansion] New suffix: {suffix}')
+ positive_basic_workloads = positive_basic_workloads + extra_positive_prompts
+ negative_basic_workloads = negative_basic_workloads + extra_negative_prompts
- p_txt = apply_style_positive(style_selction, prompt)
- p_txt = safe_str(p_txt)
+ positive_basic_workloads = remove_empty_str(positive_basic_workloads, default=prompt)
+ negative_basic_workloads = remove_empty_str(negative_basic_workloads, default=negative_prompt)
- p_txt = join_prompts(p_txt, suffix)
+ positive_top_k = len(positive_basic_workloads)
+ negative_top_k = len(negative_basic_workloads)
- tasks.append(dict(
- prompt=prompt,
- negative_prompt=negative_prompt,
- seed=current_seed,
- real_positive_prompt=p_txt,
- ))
+ tasks = [dict(
+ task_seed=seed + i,
+ positive=positive_basic_workloads,
+ negative=negative_basic_workloads,
+ expansion='',
+ c=[None, None],
+ uc=[None, None],
+ ) for i in range(image_number)]
- outputs.append(['preview', (9, 'Encoding negative text ...', None)])
- n_txt = apply_style_negative(style_selction, negative_prompt)
- n_cond = pipeline.process_prompt(n_txt)
+ if use_expansion:
+ for i, t in enumerate(tasks):
+ progressbar(5, f'Preparing Fooocus text #{i + 1} ...')
+ expansion = pipeline.expansion(prompt, t['task_seed'])
+ print(f'[Prompt Expansion] New suffix: {expansion}')
+ t['expansion'] = expansion
+ t['positive'] = copy.deepcopy(t['positive']) + [join_prompts(prompt, expansion)] # Deep copy.
+
+ for i, t in enumerate(tasks):
+ progressbar(7, f'Encoding base positive #{i + 1} ...')
+ t['c'][0] = pipeline.clip_encode(sd=pipeline.xl_base_patched, texts=t['positive'],
+ pool_top_k=positive_top_k)
+
+ for i, t in enumerate(tasks):
+ progressbar(9, f'Encoding base negative #{i + 1} ...')
+ t['uc'][0] = pipeline.clip_encode(sd=pipeline.xl_base_patched, texts=t['negative'],
+ pool_top_k=negative_top_k)
+
+ if pipeline.xl_refiner is not None:
+ for i, t in enumerate(tasks):
+ progressbar(11, f'Encoding refiner positive #{i + 1} ...')
+ t['c'][1] = pipeline.clip_encode(sd=pipeline.xl_refiner, texts=t['positive'],
+ pool_top_k=positive_top_k)
for i, t in enumerate(tasks):
- outputs.append(['preview', (12, f'Encoding positive text #{i + 1} ...', None)])
- t['p_cond'] = pipeline.process_prompt(t['real_positive_prompt'])
- t['real_negative_prompt'] = n_txt
- t['n_cond'] = n_cond
+ progressbar(13, f'Encoding refiner negative #{i + 1} ...')
+ t['uc'][1] = pipeline.clip_encode(sd=pipeline.xl_refiner, texts=t['negative'],
+ pool_top_k=negative_top_k)
if performance_selction == 'Speed':
steps = 30
@@ -117,6 +151,7 @@ def worker():
steps = 60
switch = 40
+ pipeline.clear_all_caches() # save memory
width, height = aspect_ratios[aspect_ratios_selction]
results = []
@@ -132,34 +167,32 @@ def worker():
outputs.append(['preview', (13, 'Starting tasks ...', None)])
for current_task_id, task in enumerate(tasks):
imgs = pipeline.process_diffusion(
- positive_cond=task['p_cond'],
- negative_cond=task['n_cond'],
+ positive_cond=task['c'],
+ negative_cond=task['uc'],
steps=steps,
switch=switch,
width=width,
height=height,
- image_seed=task['seed'],
+ image_seed=task['task_seed'],
callback=callback)
for x in imgs:
d = [
- ('Prompt', task['prompt']),
- ('Negative Prompt', task['negative_prompt']),
- ('Real Positive Prompt', task['real_positive_prompt']),
- ('Real Negative Prompt', task['real_negative_prompt']),
- ('Raw Mode', str(raw_mode)),
- ('Style', style_selction),
+ ('Prompt', raw_prompt),
+ ('Negative Prompt', raw_negative_prompt),
+ ('Fooocus V2 Expansion', task['expansion']),
+ ('Styles', str(raw_style_selections)),
('Performance', performance_selction),
('Resolution', str((width, height))),
('Sharpness', sharpness),
('Base Model', base_model_name),
('Refiner Model', refiner_model_name),
- ('Seed', task['seed'])
+ ('Seed', task['task_seed'])
]
for n, w in loras:
if n != 'None':
d.append((f'LoRA [{n}] weight', w))
- log(x, d)
+ log(x, d, single_line_number=3)
results += imgs
diff --git a/modules/default_pipeline.py b/modules/default_pipeline.py
index 22333215..52d81fe2 100644
--- a/modules/default_pipeline.py
+++ b/modules/default_pipeline.py
@@ -106,13 +106,55 @@ refresh_loras([(modules.path.default_lora_name, 0.5), ('None', 0.5), ('None', 0.
expansion = FooocusExpansion()
-def process_prompt(text):
- base_cond = core.encode_prompt_condition(clip=xl_base_patched.clip, prompt=text)
- if xl_refiner is not None:
- refiner_cond = core.encode_prompt_condition(clip=xl_refiner.clip, prompt=text)
- else:
- refiner_cond = None
- return base_cond, refiner_cond
+def clip_encode_single(clip, text, verbose=False):
+ cached = clip.fcs_cond_cache.get(text, None)
+ if cached is not None:
+ if verbose:
+ print(f'[CLIP Cached] {text}')
+ return cached
+ tokens = clip.tokenize(text)
+ result = clip.encode_from_tokens(tokens, return_pooled=True)
+ clip.fcs_cond_cache[text] = result
+ if verbose:
+ print(f'[CLIP Encoded] {text}')
+ return result
+
+
+def clip_encode(sd, texts, pool_top_k=1):
+ if sd is None:
+ return None
+ if sd.clip is None:
+ return None
+ if not isinstance(texts, list):
+ return None
+ if len(texts) == 0:
+ return None
+
+ clip = sd.clip
+ cond_list = []
+ pooled_acc = 0
+
+ for i, text in enumerate(texts):
+ cond, pooled = clip_encode_single(clip, text)
+ cond_list.append(cond)
+ if i < pool_top_k:
+ pooled_acc += pooled
+
+ return [[torch.cat(cond_list, dim=1), {"pooled_output": pooled_acc}]]
+
+
+def clear_sd_cond_cache(sd):
+ if sd is None:
+ return None
+ if sd.clip is None:
+ return None
+ sd.clip.fcs_cond_cache = {}
+ return
+
+
+def clear_all_caches():
+ clear_sd_cond_cache(xl_base_patched)
+ clear_sd_cond_cache(xl_refiner)
@torch.no_grad()
diff --git a/modules/expansion.py b/modules/expansion.py
index de361e31..e424994a 100644
--- a/modules/expansion.py
+++ b/modules/expansion.py
@@ -5,7 +5,6 @@ from modules.path import fooocus_expansion_path
fooocus_magic_split = [
', extremely',
- ', trending',
', intricate,',
]
dangrous_patterns = '[]【】()（）|:：'
diff --git a/modules/private_logger.py b/modules/private_logger.py
index 200d2fa0..25fc34b7 100644
--- a/modules/private_logger.py
+++ b/modules/private_logger.py
@@ -5,7 +5,7 @@ from PIL import Image
from modules.util import generate_temp_filename
-def log(img, dic):
+def log(img, dic, single_line_number=3):
date_string, local_temp_filename, only_name = generate_temp_filename(folder=modules.path.temp_outputs_path, extension='png')
os.makedirs(os.path.dirname(local_temp_filename), exist_ok=True)
Image.fromarray(img).save(local_temp_filename)
@@ -22,10 +22,10 @@ def log(img, dic):
f.write(f"{only_name}
\n")
i = 0
for k, v in dic:
- if i < 4:
+ if i < single_line_number:
f.write(f"{k}: {v}
\n")
else:
- if i % 2 == 0:
+ if (i - single_line_number) % 2 == 0:
f.write(f"{k}: {v}, ")
else:
f.write(f"{k}: {v}
\n")
diff --git a/modules/sdxl_styles.py b/modules/sdxl_styles.py
index a2e439eb..614f9856 100644
--- a/modules/sdxl_styles.py
+++ b/modules/sdxl_styles.py
@@ -1,16 +1,14 @@
from modules.util import join_prompts
+fooocus_expansion = "Fooocus V2"
+default_styles = ["Default (Slightly Cinematic)"]
+
# https://github.com/twri/sdxl_prompt_styler/blob/main/sdxl_styles.json
styles = [
{
- "name": "None",
- "prompt": "{prompt}",
- "negative_prompt": ""
- },
- {
- "name": "cinematic-default",
+ "name": "Default (Slightly Cinematic)",
"prompt": "cinematic still {prompt} . emotional, harmonious, vignette, highly detailed, high budget, bokeh, cinemascope, moody, epic, gorgeous, film grain, grainy",
"negative_prompt": "anime, cartoon, graphic, text, painting, crayon, graphite, abstract, glitch, deformed, mutated, ugly, disfigured"
},
@@ -926,8 +924,20 @@ styles = [
}
]
-styles = {k['name']: (k['prompt'], k['negative_prompt']) for k in styles}
-default_style = styles['None']
+
+def normalize_key(k):
+ k = k.replace('-', ' ')
+ words = k.split(' ')
+ words = [w[:1].upper() + w[1:].lower() for w in words]
+ k = ' '.join(words)
+ k = k.replace('3d', '3D')
+ k = k.replace('Sai', 'SAI')
+ k = k.replace('(s', '(S')
+ return k
+
+
+default_styles = [normalize_key(x) for x in default_styles]
+styles = {normalize_key(k['name']): (k['prompt'], k['negative_prompt']) for k in styles}
style_keys = list(styles.keys())
SD_XL_BASE_RATIOS = {
@@ -962,11 +972,6 @@ SD_XL_BASE_RATIOS = {
aspect_ratios = {str(v[0]) + '×' + str(v[1]): v for k, v in SD_XL_BASE_RATIOS.items()}
-def apply_style_positive(style, txt):
- p, n = styles.get(style, default_style)
- return p.replace('{prompt}', txt)
-
-
-def apply_style_negative(style, txt):
- p, n = styles.get(style, default_style)
- return join_prompts(n, txt)
+def apply_style(style, positive):
+ p, n = styles[style]
+ return p.replace('{prompt}', positive), n
diff --git a/modules/util.py b/modules/util.py
index 9fd56667..a173cf21 100644
--- a/modules/util.py
+++ b/modules/util.py
@@ -3,6 +3,13 @@ import random
import os
+def remove_empty_str(items, default=None):
+ items = [x for x in items if x != ""]
+ if len(items) == 0 and default is not None:
+ return [default]
+ return items
+
+
def join_prompts(*args, **kwargs):
prompts = [str(x) for x in args if str(x) != ""]
if len(prompts) == 0:
diff --git a/update_log.md b/update_log.md
index e171856d..1c96796f 100644
--- a/update_log.md
+++ b/update_log.md
@@ -1,3 +1,13 @@
+### 2.0.0
+
+* V2 released.
+* completely rewrite text processing pipeline (higher image quality and prompt understanding).
+* support multi-style.
+* In 100 tests (prompts written by ChatGPT), V2 default results outperform V1 default results in 87 cases, evaluated by two human.
+* In 100 tests (prompts written by ChatGPT), V2 prompt understanding outperform V1 prompt understanding in 81 cases, evaluated by two human, in both default setting and multi/single style mode.
+* Because the above number is above 80%, we view this as a major update and directly jump to 2.0.0.
+* Some other things are renamed.
+
### 1.0.67
* Use dynamic weighting and lower weights for prompt expansion.
diff --git a/webui.py b/webui.py
index b7dd9b46..a4eb0424 100644
--- a/webui.py
+++ b/webui.py
@@ -8,7 +8,7 @@ import fooocus_version
import modules.html
import modules.async_worker as worker
-from modules.sdxl_styles import style_keys, aspect_ratios
+from modules.sdxl_styles import style_keys, aspect_ratios, fooocus_expansion, default_styles
def generate_clicked(*args):
@@ -76,11 +76,10 @@ with shared.gradio_root:
seed_random.change(random_checked, inputs=[seed_random], outputs=[image_seed])
with gr.Tab(label='Style'):
- raw_mode_check = gr.Checkbox(label='Raw Mode', value=False,
- info='Similar to Midjourney\'s \"raw\" mode.')
- style_selction = gr.Radio(show_label=True, container=True,
- choices=style_keys, value='cinematic-default', label='Image Style',
- info='Similar to Midjourney\'s \"--style\".')
+ style_selections = gr.CheckboxGroup(show_label=False, container=False,
+ choices=[fooocus_expansion] + style_keys,
+ value=[fooocus_expansion] + default_styles,
+ label='Image Style')
with gr.Tab(label='Advanced'):
with gr.Row():
base_model = gr.Dropdown(label='SDXL Base Model', choices=modules.path.model_filenames, value=modules.path.default_base_model_name, show_label=True)
@@ -110,8 +109,8 @@ with shared.gradio_root:
advanced_checkbox.change(lambda x: gr.update(visible=x), advanced_checkbox, right_col)
ctrls = [
- prompt, negative_prompt, style_selction,
- performance_selction, aspect_ratios_selction, image_number, image_seed, sharpness, raw_mode_check
+ prompt, negative_prompt, style_selections,
+ performance_selction, aspect_ratios_selction, image_number, image_seed, sharpness
]
ctrls += [base_model, refiner_model] + lora_ctrls
run_button.click(fn=refresh_seed, inputs=[seed_random, image_seed], outputs=image_seed)\