readme extras for VRAM for

added missing packages to requirements for #74
add support for negative numbers in X/Y plot (plus ranges) #73
changed progressbar to work properly with custom modes
This commit is contained in:
AUTOMATIC 2022-09-06 10:11:25 +03:00
parent beece7d85c
commit 395f170597
7 changed files with 45 additions and 11 deletions

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@ -149,9 +149,9 @@ Open the URL in browser, and you are good to go.
### What options to use for low VRAM videocards?
- If you have 4GB VRAM and want to make 512x512 (or maybe up to 640x640) images, use `--medvram`.
- If you have 4GB VRAM and want to make 512x512 images, but you get an out of memory error with `--medvram`, use `--medvram --opt-split-attention` instead.
- If you have 4GB VRAM and want to make 512x512 images, and you still get an out of memory error, use `--lowvram --always-batch-cond-uncond` instead.
- If you have 4GB VRAM and want to make images larger than you can with `--medvram`, use `--lowvram`.
- If you have more VRAM and want to make larger images than you can usually make, use `--medvram`. You can use `--lowvram`
- If you have 4GB VRAM and want to make 512x512 images, and you still get an out of memory error, use `--lowvram --always-batch-cond-uncond --opt-split-attention` instead.
- If you have 4GB VRAM and want to make images larger than you can with `--medvram`, use `--lowvram --opt-split-attention`.
- If you have more VRAM and want to make larger images than you can usually make, use `--medvram --opt-split-attention`. You can use `--lowvram`
also but the effect will likely be barely noticeable.
- Otherwise, do not use any of those.
@ -159,6 +159,26 @@ Extra: if you get a green screen instead of generated pictures, you have a card
precision floating point numbers. You must use `--precision full --no-half` in addition to other flags,
and the model will take much more space in VRAM.
### How to change UI defaults?
After running once, a `ui-config.json` file appears in webui directory:
```json
{
"txt2img/Sampling Steps/value": 20,
"txt2img/Sampling Steps/minimum": 1,
"txt2img/Sampling Steps/maximum": 150,
"txt2img/Sampling Steps/step": 1,
"txt2img/Batch count/value": 1,
"txt2img/Batch count/minimum": 1,
"txt2img/Batch count/maximum": 32,
"txt2img/Batch count/step": 1,
"txt2img/Batch size/value": 1,
"txt2img/Batch size/minimum": 1,
```
Edit values to your liking and the next time you launch the program they will be applied.
## Credits
- Stable Diffusion - https://github.com/CompVis/stable-diffusion, https://github.com/CompVis/taming-transformers
- k-diffusion - https://github.com/crowsonkb/k-diffusion.git

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@ -153,6 +153,7 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
with torch.no_grad(), precision_scope("cuda"), ema_scope():
p.init()
if state.job_count == -1:
state.job_count = p.n_iter
for n in range(p.n_iter):

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@ -54,6 +54,7 @@ class State:
self.job_no += 1
self.sampling_step = 0
state = State()
artist_db = modules.artists.ArtistsDatabase(os.path.join(script_path, 'artists.csv'))

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@ -140,7 +140,10 @@ def check_progress_call():
if shared.state.job_count == 0:
return ""
progress = shared.state.job_no / shared.state.job_count
progress = 0
if shared.state.job_count > 0:
progress += shared.state.job_no / shared.state.job_count
if shared.state.sampling_steps > 0:
progress += 1 / shared.state.job_count * shared.state.sampling_step / shared.state.sampling_steps

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@ -8,3 +8,7 @@ torch
transformers
omegaconf
pytorch_lightning
diffusers
invisible-watermark
git+https://github.com/crowsonkb/k-diffusion.git
git+https://github.com/TencentARC/GFPGAN.git

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@ -9,6 +9,7 @@ from modules import images
from modules.processing import process_images, Processed
from modules.shared import opts, cmd_opts, state
import modules.sd_samplers
import re
def apply_field(field):
@ -89,6 +90,8 @@ def draw_xy_grid(xs, ys, x_label, y_label, cell):
return first_pocessed
re_range = re.compile(r"\s*([+-]?\s*\d+)\s*-\s*([+-]?\s*\d+)(?:\s*\(([+-]\d+)\s*\))?\s*")
class Script(scripts.Script):
def title(self):
return "X/Y plot"
@ -118,11 +121,13 @@ class Script(scripts.Script):
valslist_ext = []
for val in valslist:
if "-" in val:
s = val.split("-")
start = int(s[0])
end = int(s[1])+1
step = 1 if len(s) < 3 else int(s[2])
m = re_range.fullmatch(val)
if m is not None:
start = int(m.group(1))
end = int(m.group(2))+1
step = int(m.group(3)) if m.group(3) is not None else 1
valslist_ext += list(range(start, end, step))
else:
valslist_ext.append(val)

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@ -123,7 +123,7 @@ queue_lock = threading.Lock()
def wrap_gradio_gpu_call(func):
def f(*args, **kwargs):
shared.state.sampling_step = 0
shared.state.job_count = 1
shared.state.job_count = -1
shared.state.job_no = 0