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finished CLI, IMG2IMG and WEB updates

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Lincoln Stein
2023-02-08 12:45:56 -05:00
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@@ -6,38 +6,51 @@ title: Command-Line Interface
## **Interactive Command Line Interface**
The `invoke.py` script, located in `scripts/`, provides an interactive interface
to image generation similar to the "invoke mothership" bot that Stable AI
provided on its Discord server.
The InvokeAI command line interface (CLI) provides scriptable access
to InvokeAI's features.Some advanced features are only available
through the CLI, though they eventually find their way into the WebUI.
Unlike the `txt2img.py` and `img2img.py` scripts provided in the original
[CompVis/stable-diffusion](https://github.com/CompVis/stable-diffusion) source
code repository, the time-consuming initialization of the AI model
initialization only happens once. After that image generation from the
command-line interface is very fast.
The CLI is accessible from the `invoke.sh`/`invoke.bat` launcher by
selecting option (1). Alternatively, it can be launched directly from
the command line by activating the InvokeAI environment and giving the
command:
```bash
invokeai
```
After some startup messages, you will be presented with the `invoke> `
prompt. Here you can type prompts to generate images and issue other
commands to load and manipulate generative models. The CLI has a large
number of command-line options that control its behavior. To get a
concise summary of the options, call `invokeai` with the `--help` argument:
```bash
invokeai --help
```
The script uses the readline library to allow for in-line editing, command
history (++up++ and ++down++), autocompletion, and more. To help keep track of
which prompts generated which images, the script writes a log file of image
names and prompts to the selected output directory.
In addition, as of version 1.02, it also writes the prompt into the PNG file's
metadata where it can be retrieved using `scripts/images2prompt.py`
The script is confirmed to work on Linux, Windows and Mac systems.
!!! note
This script runs from the command-line or can be used as a Web application. The Web GUI is
currently rudimentary, but a much better replacement is on its way.
Here is a typical session
```bash
(invokeai) ~/stable-diffusion$ python3 ./scripts/invoke.py
PS1:C:\Users\fred> invokeai
* Initializing, be patient...
Loading model from models/ldm/text2img-large/model.ckpt
(...more initialization messages...)
* Initialization done! Awaiting your command...
* Initializing, be patient...
>> Initialization file /home/lstein/invokeai/invokeai.init found. Loading...
>> Internet connectivity is True
>> InvokeAI, version 2.3.0-rc5
>> InvokeAI runtime directory is "/home/lstein/invokeai"
>> GFPGAN Initialized
>> CodeFormer Initialized
>> ESRGAN Initialized
>> Using device_type cuda
>> xformers memory-efficient attention is available and enabled
(...more initialization messages...)
* Initialization done! Awaiting your command (-h for help, 'q' to quit)
invoke> ashley judd riding a camel -n2 -s150
Outputs:
outputs/img-samples/00009.png: "ashley judd riding a camel" -n2 -s150 -S 416354203
@@ -47,27 +60,15 @@ invoke> "there's a fly in my soup" -n6 -g
outputs/img-samples/00011.png: "there's a fly in my soup" -n6 -g -S 2685670268
seeds for individual rows: [2685670268, 1216708065, 2335773498, 822223658, 714542046, 3395302430]
invoke> q
# this shows how to retrieve the prompt stored in the saved image's metadata
(invokeai) ~/stable-diffusion$ python ./scripts/images2prompt.py outputs/img_samples/*.png
00009.png: "ashley judd riding a camel" -s150 -S 416354203
00010.png: "ashley judd riding a camel" -s150 -S 1362479620
00011.png: "there's a fly in my soup" -n6 -g -S 2685670268
```
![invoke-py-demo](../assets/dream-py-demo.png)
The `invoke>` prompt's arguments are pretty much identical to those used in the
Discord bot, except you don't need to type `!invoke` (it doesn't hurt if you
do). A significant change is that creation of individual images is now the
default unless `--grid` (`-g`) is given. A full list is given in
[List of prompt arguments](#list-of-prompt-arguments).
## Arguments
The script itself also recognizes a series of command-line switches that will
change important global defaults, such as the directory for image outputs and
the location of the model weight files.
The script recognizes a series of command-line switches that will
change important global defaults, such as the directory for image
outputs and the location of the model weight files.
### List of arguments recognized at the command line
@@ -82,10 +83,14 @@ overridden on a per-prompt basis (see
| `--outdir <path>` | `-o<path>` | `outputs/img_samples` | Location for generated images. |
| `--prompt_as_dir` | `-p` | `False` | Name output directories using the prompt text. |
| `--from_file <path>` | | `None` | Read list of prompts from a file. Use `-` to read from standard input |
| `--model <modelname>` | | `stable-diffusion-1.4` | Loads model specified in configs/models.yaml. Currently one of "stable-diffusion-1.4" or "laion400m" |
| `--full_precision` | `-F` | `False` | Run in slower full-precision mode. Needed for Macintosh M1/M2 hardware and some older video cards. |
| `--model <modelname>` | | `stable-diffusion-1.5` | Loads the initial model specified in configs/models.yaml. |
| `--ckpt_convert ` | | `False` | If provided both .ckpt and .safetensors files will be auto-converted into diffusers format in memory |
| `--autoconvert <path>` | | `None` | On startup, scan the indicated directory for new .ckpt/.safetensor files and automatically convert and import them |
| `--precision` | | `fp16` | Provide `fp32` for full precision mode, `fp16` for half-precision. `fp32` needed for Macintoshes and some NVidia cards. |
| `--png_compression <0-9>` | `-z<0-9>` | `6` | Select level of compression for output files, from 0 (no compression) to 9 (max compression) |
| `--safety-checker` | | `False` | Activate safety checker for NSFW and other potentially disturbing imagery |
| `--patchmatch`, `--no-patchmatch` | | `--patchmatch` | Load/Don't load the PatchMatch inpainting extension |
| `--xformers`, `--no-xformers` | | `--xformers` | Load/Don't load the Xformers memory-efficient attention module (CUDA only) |
| `--web` | | `False` | Start in web server mode |
| `--host <ip addr>` | | `localhost` | Which network interface web server should listen on. Set to 0.0.0.0 to listen on any. |
| `--port <port>` | | `9090` | Which port web server should listen for requests on. |
@@ -109,6 +114,7 @@ overridden on a per-prompt basis (see
| Argument | Shortcut | Default | Description |
|--------------------|------------|---------------------|--------------|
| `--full_precision` | | `False` | Same as `--precision=fp32`|
| `--weights <path>` | | `None` | Path to weights file; use `--model stable-diffusion-1.4` instead |
| `--laion400m` | `-l` | `False` | Use older LAION400m weights; use `--model=laion400m` instead |
@@ -336,8 +342,10 @@ useful for debugging the text masking process prior to inpainting with the
### Model selection and importation
The CLI allows you to add new models on the fly, as well as to switch among them
rapidly without leaving the script.
The CLI allows you to add new models on the fly, as well as to switch
among them rapidly without leaving the script. There are several
different model formats, each described in the [Model Installation
Guide](050_INSTALLING_MODELS.md).
#### `!models`
@@ -347,9 +355,9 @@ model is bold-faced
Example:
<pre>
laion400m not loaded <no description>
<b>stable-diffusion-1.4 active Stable Diffusion v1.4</b>
waifu-diffusion not loaded Waifu Diffusion v1.3
inpainting-1.5 not loaded Stable Diffusion inpainting model
<b>stable-diffusion-1.5 active Stable Diffusion v1.5</b>
waifu-diffusion not loaded Waifu Diffusion v1.4
</pre>
#### `!switch <model>`
@@ -361,43 +369,30 @@ Note how the second column of the `!models` table changes to `cached` after a
model is first loaded, and that the long initialization step is not needed when
loading a cached model.
<pre>
invoke> !models
laion400m not loaded <no description>
<b>stable-diffusion-1.4 cached Stable Diffusion v1.4</b>
waifu-diffusion active Waifu Diffusion v1.3
#### `!import_model <hugging_face_repo_ID>`
invoke> !switch waifu-diffusion
>> Caching model stable-diffusion-1.4 in system RAM
>> Loading waifu-diffusion from models/ldm/stable-diffusion-v1/model-epoch08-float16.ckpt
| LatentDiffusion: Running in eps-prediction mode
| DiffusionWrapper has 859.52 M params.
| Making attention of type 'vanilla' with 512 in_channels
| Working with z of shape (1, 4, 32, 32) = 4096 dimensions.
| Making attention of type 'vanilla' with 512 in_channels
| Using faster float16 precision
>> Model loaded in 18.24s
>> Max VRAM used to load the model: 2.17G
>> Current VRAM usage:2.17G
>> Setting Sampler to k_lms
This imports and installs a `diffusers`-style model that is stored on
the [HuggingFace Web Site](https://huggingface.co). You can look up
any [Stable Diffusion diffusers
model](https://huggingface.co/models?library=diffusers) and install it
with a command like the following:
invoke> !models
laion400m not loaded <no description>
stable-diffusion-1.4 cached Stable Diffusion v1.4
<b>waifu-diffusion active Waifu Diffusion v1.3</b>
```bash
!import_model prompthero/openjourney
```
invoke> !switch stable-diffusion-1.4
>> Caching model waifu-diffusion in system RAM
>> Retrieving model stable-diffusion-1.4 from system RAM cache
>> Setting Sampler to k_lms
#### `!import_model <path/to/diffusers/directory>`
invoke> !models
laion400m not loaded <no description>
<b>stable-diffusion-1.4 active Stable Diffusion v1.4</b>
waifu-diffusion cached Waifu Diffusion v1.3
</pre>
If you have a copy of a `diffusers`-style model saved to disk, you can
import it by passing the path to model's top-level directory.
#### `!import_model <path/to/model/weights>`
#### `!import_model <url>`
For a `.ckpt` or `.safetensors` file, if you have a direct download
URL for the file, you can provide it to `!import_model` and the file
will be downloaded and installed for you.
#### `!import_model <path/to/model/weights.ckpt>`
This command imports a new model weights file into InvokeAI, makes it available
for image generation within the script, and writes out the configuration for the
@@ -417,35 +412,12 @@ below, the bold-faced text shows what the user typed in with the exception of
the width, height and configuration file paths, which were filled in
automatically.
Example:
#### `!import_model <path/to/directory_of_models>`
<pre>
invoke> <b>!import_model models/ldm/stable-diffusion-v1/model-epoch08-float16.ckpt</b>
>> Model import in process. Please enter the values needed to configure this model:
Name for this model: <b>waifu-diffusion</b>
Description of this model: <b>Waifu Diffusion v1.3</b>
Configuration file for this model: <b>configs/stable-diffusion/v1-inference.yaml</b>
Default image width: <b>512</b>
Default image height: <b>512</b>
>> New configuration:
waifu-diffusion:
config: configs/stable-diffusion/v1-inference.yaml
description: Waifu Diffusion v1.3
height: 512
weights: models/ldm/stable-diffusion-v1/model-epoch08-float16.ckpt
width: 512
OK to import [n]? <b>y</b>
>> Caching model stable-diffusion-1.4 in system RAM
>> Loading waifu-diffusion from models/ldm/stable-diffusion-v1/model-epoch08-float16.ckpt
| LatentDiffusion: Running in eps-prediction mode
| DiffusionWrapper has 859.52 M params.
| Making attention of type 'vanilla' with 512 in_channels
| Working with z of shape (1, 4, 32, 32) = 4096 dimensions.
| Making attention of type 'vanilla' with 512 in_channels
| Using faster float16 precision
invoke>
</pre>
If you provide the path of a directory that contains one or more
`.ckpt` or `.safetensors` files, the CLI will scan the directory and
interactively offer to import the models it finds there. Also see the
`--autoconvert` command-line option.
#### `!edit_model <name_of_model>`
@@ -479,11 +451,6 @@ OK to import [n]? y
...
</pre>
======= invoke> !fix 000017.4829112.gfpgan-00.png --embiggen 3 ...lots of
text... Outputs: [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 ```
### History processing
The CLI provides a series of convenient commands for reviewing previous actions,