Build the base generator in same place and way as other generators to reduce the chance of missed arguments in the future.
Fixes crash with display in-progress images, though note the feature still doesn't work for other reasons.
1. Add ldm/dream/restoration/__init__.py file that was inadvertently not
committed earlier.
2. Add '.' to sys.path to address weird mac problem reported in #723
- Adapted from PR #489, author Dominic Letz [https://github.com/dominicletz]
- Too many upstream changes to merge, so frankensteined it in.
- Added support for !fix syntax
- Added documentation
- The seed printed needs to be the one generated prior to the
initial noising operation. To do this, I added a new "first_seed"
argument to the image callback in dream.py.
- Closes#641
- modify strength of embiggen to reduce tiling ghosts
- normalize naming of postprocessed files (could improve more to avoid
name collisions)
- move restoration modules under ldm.dream
- supports gfpgan, esrgan, codeformer and embiggen
- To use:
dream> !fix ./outputs/img-samples/000056.292144555.png -ft gfpgan -U2 -G0.8
dream> !fix ./outputs/img-samples/000056.292144555.png -ft codeformer -G 0.8
dream> !fix ./outputs/img-samples/000056.29214455.png -U4
dream> !fix ./outputs/img-samples/000056.292144555.png -embiggen 1.5
The first example invokes gfpgan to fix faces and esrgan to upscale.
The second example invokes codeformer to fix faces, no upscaling
The third example uses esrgan to upscale 4X
The four example runs embiggen to enlarge 1.5X
- This is very preliminary work. There are some anomalies to note:
1. The syntax is non-obvious. I would prefer something like:
!fix esrgan,gfpgan
!fix esrgan
!fix embiggen,codeformer
However, this will require refactoring the gfpgan and embiggen
code.
2. Images generated using gfpgan, esrgan or codeformer all are named
"xxxxxx.xxxxxx.postprocessed.png" and the original is saved.
However, the prefix is a new one that is not related to the
original.
3. Images generated using embiggen are named "xxxxx.xxxxxxx.png",
and once again the prefix is new. I'm not sure whether the
prefix should be aligned with the original file's prefix or not.
Probably not, but opinions welcome.
Allowed values are 'auto', 'float32', 'autocast', 'float16'. If not specified or 'auto' a working precision is automatically selected based on the torch device.
Context: #526
Deprecated --full_precision / -F
Tested on both cuda and cpu by calling scripts/dream.py without arguments and checked the auto configuration worked. With --precision=auto/float32/autocast/float16 it performs as expected, either working or failing with a reasonable error. Also checked Img2Img.
- modify strength of embiggen to reduce tiling ghosts
- normalize naming of postprocessed files (could improve more to avoid
name collisions)
- move restoration modules under ldm.dream
- supports gfpgan, esrgan, codeformer and embiggen
- To use:
dream> !fix ./outputs/img-samples/000056.292144555.png -ft gfpgan -U2 -G0.8
dream> !fix ./outputs/img-samples/000056.292144555.png -ft codeformer -G 0.8
dream> !fix ./outputs/img-samples/000056.29214455.png -U4
dream> !fix ./outputs/img-samples/000056.292144555.png -embiggen 1.5
The first example invokes gfpgan to fix faces and esrgan to upscale.
The second example invokes codeformer to fix faces, no upscaling
The third example uses esrgan to upscale 4X
The four example runs embiggen to enlarge 1.5X
- This is very preliminary work. There are some anomalies to note:
1. The syntax is non-obvious. I would prefer something like:
!fix esrgan,gfpgan
!fix esrgan
!fix embiggen,codeformer
However, this will require refactoring the gfpgan and embiggen
code.
2. Images generated using gfpgan, esrgan or codeformer all are named
"xxxxxx.xxxxxx.postprocessed.png" and the original is saved.
However, the prefix is a new one that is not related to the
original.
3. Images generated using embiggen are named "xxxxx.xxxxxxx.png",
and once again the prefix is new. I'm not sure whether the
prefix should be aligned with the original file's prefix or not.
Probably not, but opinions welcome.
* Support color correction for img2img and inpainting, avoiding the shift to magenta seen when running images through img2img repeatedly.
* Fix docs for color correction
* add --init_color to prompt reconstruction
* For best results, the --init_color option should point to the *very first* image used in the sequence of img2img operations. Otherwise color correction will skew towards cyan.
Co-authored-by: Lincoln Stein <lincoln.stein@gmail.com>
Fixes:
File "stable-diffusion/ldm/modules/diffusionmodules/model.py", line 37, in nonlinearity
return x*torch.sigmoid(x)
RuntimeError: CUDA out of memory. Tried to allocate 1.56 GiB [..]
Now up to 1536x1280 is possible on 8GB VRAM.
Also remove unused SiLU class.
