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https://github.com/invoke-ai/InvokeAI
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Merge branch 'development' into development
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Lincoln Stein
GitHub
@ -205,6 +205,85 @@ well as the --mask (-M) argument:
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| --init_mask <path> | -M<path> | None |Path to an image the same size as the initial_image, with areas for inpainting made transparent.|
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# Convenience commands
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In addition to the standard image generation arguments, there are a
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series of convenience commands that begin with !:
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## !fix
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This command runs a post-processor on a previously-generated image. It
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takes a PNG filename or path and applies your choice of the -U, -G, or
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--embiggen switches in order to fix faces or upscale. If you provide a
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filename, the script will look for it in the current output
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directory. Otherwise you can provide a full or partial path to the
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desired file.
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Some examples:
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Upscale to 4X its original size and fix faces using codeformer:
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~~~
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dream> !fix 0000045.4829112.png -G1 -U4 -ft codeformer
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~~~
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Use the GFPGAN algorithm to fix faces, then upscale to 3X using --embiggen:
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~~~
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dream> !fix 0000045.4829112.png -G0.8 -ft gfpgan
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>> fixing outputs/img-samples/0000045.4829112.png
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>> retrieved seed 4829112 and prompt "boy enjoying a banana split"
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>> GFPGAN - Restoring Faces for image seed:4829112
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Outputs:
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[1] outputs/img-samples/000017.4829112.gfpgan-00.png: !fix "outputs/img-samples/0000045.4829112.png" -s 50 -S -W 512 -H 512 -C 7.5 -A k_lms -G 0.8
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dream> !fix 000017.4829112.gfpgan-00.png --embiggen 3
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...lots of text...
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Outputs:
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[2] outputs/img-samples/000018.2273800735.embiggen-00.png: !fix "outputs/img-samples/000017.243781548.gfpgan-00.png" -s 50 -S 2273800735 -W 512 -H 512 -C 7.5 -A k_lms --embiggen 3.0 0.75 0.25
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~~~
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## !fetch
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This command retrieves the generation parameters from a previously
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generated image and either loads them into the command line
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(Linux|Mac), or prints them out in a comment for copy-and-paste
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(Windows). You may provide either the name of a file in the current
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output directory, or a full file path.
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~~~
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dream> !fetch 0000015.8929913.png
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# the script returns the next line, ready for editing and running:
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dream> a fantastic alien landscape -W 576 -H 512 -s 60 -A plms -C 7.5
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~~~
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Note that this command may behave unexpectedly if given a PNG file that
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was not generated by InvokeAI.
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## !history
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The dream script keeps track of all the commands you issue during a
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session, allowing you to re-run them. On Mac and Linux systems, it
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also writes the command-line history out to disk, giving you access to
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the most recent 1000 commands issued.
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The `!history` command will return a numbered list of all the commands
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issued during the session (Windows), or the most recent 1000 commands
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(Mac|Linux). You can then repeat a command by using the command !NNN,
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where "NNN" is the history line number. For example:
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~~~
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dream> !history
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...
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[14] happy woman sitting under tree wearing broad hat and flowing garment
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[15] beautiful woman sitting under tree wearing broad hat and flowing garment
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[18] beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6
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[20] watercolor of beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6 -S2878767194
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[21] surrealist painting of beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6 -S2878767194
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...
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dream> !20
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dream> watercolor of beautiful woman sitting under tree wearing broad hat and flowing garment -v0.2 -n6 -S2878767194
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~~~
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# Command-line editing and completion
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If you are on a Macintosh or Linux machine, the command-line offers
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@ -87,7 +87,6 @@ Usually this will be sufficient, but if you start to see errors about
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missing or incorrect modules, use the command `pip install -e .`
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and/or `conda env update` (These commands won't break anything.)
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`pip install -e .` and/or
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`conda env update -f environment.yaml`
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@ -118,16 +118,17 @@ ln -s "$PATH_TO_CKPT/sd-v1-4.ckpt" \
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```bash
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PIP_EXISTS_ACTION=w CONDA_SUBDIR=osx-arm64 \
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conda env create \
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-f environment-mac.yaml \
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-f environment-mac.yml \
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&& conda activate ldm
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```
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=== "Intel x86_64"
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```bash
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PIP_EXISTS_ACTION=w CONDA_SUBDIR=osx-64 \
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conda env create \
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-f environment-mac.yaml \
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-f environment-mac.yml \
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&& conda activate ldm
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```
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@ -147,16 +148,9 @@ python scripts/orig_scripts/txt2img.py \
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--plms
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```
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## Notes
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1. half-precision requires autocast which is unfortunately incompatible with the
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implementation of pytorch on the M1 architecture. On Macs, --full-precision will
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default to True.
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2. `export PIP_EXISTS_ACTION=w` in the commands above, is a precaution to fix `conda env
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Note, `export PIP_EXISTS_ACTION=w` is a precaution to fix `conda env
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create -f environment-mac.yml` never finishing in some situations. So
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it isn't required but wont hurt.
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---
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## Common problems
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@ -196,14 +190,15 @@ conda install \
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-n ldm
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```
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If it takes forever to run `conda env create -f environment-mac.yml` you could try to run:
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```bash
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git clean -f
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conda clean \
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--yes \
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--all
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```
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If it takes forever to run `conda env create -f environment-mac.yml`, try this:
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```bash
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git clean -f
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conda clean \
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--yes \
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--all
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```
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Or you could try to completley reset Anaconda:
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@ -384,7 +379,7 @@ python scripts/preload_models.py
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```
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This fork already includes a fix for this in
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[environment-mac.yaml](https://github.com/invoke-ai/InvokeAI/blob/main/environment-mac.yml).
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[environment-mac.yml](https://github.com/invoke-ai/InvokeAI/blob/main/environment-mac.yml).
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### "Could not build wheels for tokenizers"
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@ -39,7 +39,7 @@ in the wiki
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4. Run the command:
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```batch
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```bash
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git clone https://github.com/invoke-ai/InvokeAI.git
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```
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@ -48,17 +48,16 @@ in the wiki
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5. Enter the newly-created InvokeAI folder. From this step forward make sure that you are working in the InvokeAI directory!
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```batch
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cd InvokeAI
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```
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```
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cd InvokeAI
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```
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6. Run the following two commands:
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```batch
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conda env create (step 6a)
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conda activate ldm (step 6b)
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```
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```
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conda env create (step 6a)
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conda activate ldm (step 6b)
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```
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This will install all python requirements and activate the "ldm" environment
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which sets PATH and other environment variables properly.
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@ -68,7 +67,7 @@ in the wiki
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7. Run the command:
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```batch
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```bash
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python scripts\preload_models.py
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```
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@ -90,17 +89,17 @@ in the wiki
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Now run the following commands from **within the InvokeAI directory** to copy the weights file to the right place:
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```batch
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mkdir -p models\ldm\stable-diffusion-v1
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copy C:\path\to\sd-v1-4.ckpt models\ldm\stable-diffusion-v1\model.ckpt
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```
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```
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mkdir -p models\ldm\stable-diffusion-v1
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copy C:\path\to\sd-v1-4.ckpt models\ldm\stable-diffusion-v1\model.ckpt
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```
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Please replace `C:\path\to\sd-v1.4.ckpt` with the correct path to wherever you stashed this file. If you prefer not to copy or move the .ckpt file,
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you may instead create a shortcut to it from within `models\ldm\stable-diffusion-v1\`.
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9. Start generating images!
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```batch
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```bash
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# for the pre-release weights
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python scripts\dream.py -l
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@ -117,16 +116,16 @@ you may instead create a shortcut to it from within `models\ldm\stable-diffusion
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---
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## Updating to newer versions of the script
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This distribution is changing rapidly. If you used the `git clone` method (step 5) to download the InvokeAI directory, then to update to the latest and greatest version, launch the Anaconda window, enter `InvokeAI`, and type:
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This distribution is changing rapidly. If you used the `git clone` method
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(step 5) to download the stable-diffusion directory, then to update to the
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latest and greatest version, launch the Anaconda window, enter
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`stable-diffusion`, and type:
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```batch
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git pull
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conda env update
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```
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```bash
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git pull
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conda env update
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```
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This will bring your local copy into sync with the remote one.
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@ -40,7 +40,7 @@ A suitable [conda](https://conda.io/) environment named `ldm` can be created and
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activated with:
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```
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conda env create -f environment.yml
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conda env create
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conda activate ldm
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```
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