This commit does several things that improve the customizability of the CLI `outcrop` command:
1. When outcropping an image you can now add a `--new_prompt` option, to specify a new prompt to be applied to the outpainted region instead of the prompt used to generate the image.
2. Similarly you can provide a new seed using `--seed` (or `-S`). A seed less than zero will pick one randomly.
3. The metadata written into the outcropped file is now more informative about what was previously stored.
4. This PR also fixes the crash that happened when trying to outcrop an image that does not contain InvokeAI metadata.
Other changes:
- add error checking suggested by @Kyle0654
- add special case in invoke.py to allow -1 to be passed as seed.
This now only occurs for postprocessing commands. Previously, -1
caused previous seed to be used, and this still applies to generate
operations.
- When outcropping an image you can now add a `--new_prompt` option, to specify
a new prompt to be used instead of the original one used to generate the image.
- Similarly you can provide a new seed using `--seed` (or `-S`). A seed of zero
will pick one randomly.
- This PR also fixes the crash that happened when trying to outcrop an image
that does not contain InvokeAI metadata.
- Works best with runwayML inpainting model
- Numerous code changes required to propagate seed to final metadata.
Original code predicated on the image being generated within InvokeAI.
- Works best with runwayML inpainting model
- Numerous code changes required to propagate seed to final metadata.
Original code predicated on the image being generated within InvokeAI.
- Place preferred startup command switches in a file named
"invokeai.init". The file can consist of a single line of switches
such as "--web --steps=28", a series of switches on each
line, or any combination of the two.
Example:
```
--web
--host=0.0.0.0
--steps=28
--grid
-f 0.6 -C 11.0 -A k_euler_a
```
- The following options, which were previously only available within
the CLI, are now available on the command line as well:
--steps
--strength
--cfg_scale
--width
--height
--fit
- Due to misuse of rebase command, main was transiently
in an inconsistent state.
- This repairs the damage, and adds a few post-release
patches that ensure stable conda installs on Mac and Windows.
Complete re-write of the prompt parsing logic to be more readable and
logical, and therefore also hopefully easier to debug, maintain, and
augment.
In the process it has also become more robust to badly-formed prompts.
Squashed commit of the following:
commit 8fcfa88a16e1390d41717e940d72aed64712171c
Author: Damian at mba <damian@frey.NOSPAMco.nz>
Date: Sun Oct 30 17:05:57 2022 +0100
further cleanup
commit 1a1fd78bcfeb49d072e3e6d5808aa8df15441629
Author: Damian at mba <damian@frey.NOSPAMco.nz>
Date: Sun Oct 30 16:07:57 2022 +0100
cleanup and document
commit 099c9659fa8b8135876f9a5a50fe80b20bc0635c
Author: Damian at mba <damian@frey.NOSPAMco.nz>
Date: Sun Oct 30 15:54:58 2022 +0100
works fully
commit 5e6887ea8c25a1e21438ff6defb381fd027d25fd
Author: Damian at mba <damian@frey.NOSPAMco.nz>
Date: Sun Oct 30 15:24:31 2022 +0100
further...
commit 492fda120844d9bc1ad4ec7dd408a3374762d0ff
Author: Damian at mba <damian@frey.NOSPAMco.nz>
Date: Sun Oct 30 14:08:57 2022 +0100
getting there...
commit c6aab05a8450cc3c95c8691daf38fdc64c74f52d
Author: Damian at mba <damian@frey.NOSPAMco.nz>
Date: Fri Oct 28 14:29:03 2022 +0200
wip doesn't compile
commit 5e533f731cfd20cd435330eeb0012e5689e87e81
Author: Damian at mba <damian@frey.NOSPAMco.nz>
Date: Fri Oct 28 13:21:43 2022 +0200
working with CrossAttentionCtonrol but no Attention support yet
commit 9678348773431e500e110e8aede99086bb7b5955
Author: Damian at mba <damian@frey.NOSPAMco.nz>
Date: Fri Oct 28 13:04:52 2022 +0200
wip rebuiling prompt parser
- ldm.generate.Generator() now takes an argument named `max_load_models`.
This is an integer that limits the model cache size. When the cache
reaches the limit, it will start purging older models from cache.
- CLI takes an argument --max_load_models, default to 2. This will keep
one model in GPU and the other in CPU and switch back and forth
quickly.
- To not cache models at all, pass --max_load_models=1
- ldm.generate.Generator() now takes an argument named `max_load_models`.
This is an integer that limits the model cache size. When the cache
reaches the limit, it will start purging older models from cache.
- CLI takes an argument --max_load_models, default to 2. This will keep
one model in GPU and the other in CPU and switch back and forth
quickly.
- To not cache models at all, pass --max_load_models=1
- user can select which weight files to download using huggingface cache
- user must log in to huggingface, generate an access token, and accept
license terms the very first time this is run. After that, everything
works automatically.
- added placeholder for docs for installing models
- also got rid of unused config files. hopefully they weren't needed
for textual inversion, but I don't think so.
The Args object would crap out when trying to retrieve metadata from
an image file that did not contain InvokeAI-generated metadata, such
as a JPG. This corrects that and returns dummy values (seed of zero,
prompt of '') to avoid downstream breakage.
The k_samplers come with a "karras" noise schedule which performs
very well at low step counts but becomes noisy at higher ones.
This commit introduces a threshold (currently 30 steps) at which the
k samplers will switch over from using karras to the older model
noise schedule.
- This sets a step switchover point at which the k-samplers stop using the
Karras noise schedule and start using the LatentDiffusion noise schedule.
The advantage of this is that the Karras schedule produces excellent
results at low step counts but starts to become unstable at high
steps.
- A new command argument --karras_max, lets the user set where the
switchover occurs. Default is 29 steps (1-29 steps Karras),
(30 or greater LDM)
- Tildebyte, sorry to do a fast forward three-way merge for this
but rebasing was just too painful due to extensive recent
changes to the diffuser code.
