mirror of
https://github.com/invoke-ai/InvokeAI
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Global replace [ \t]+$, add "GB" (#1751)
* "GB" * Replace [ \t]+$ global Co-authored-by: Lincoln Stein <lincoln.stein@gmail.com>
This commit is contained in:
Scott Lahteine
GitHub
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7d8d4bcafb
@ -1,4 +1,4 @@
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<img src="docs/assets/invoke_ai_banner.png" align="center">
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<img src="docs/assets/invoke_ai_banner.png" align="center">
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Invoke-AI is a community of software developers, researchers, and user
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interface experts who have come together on a voluntary basis to build
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@ -31,7 +31,7 @@ stable-diffusion-1.4:
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width: 512
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height: 512
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waifu-diffusion-1.3:
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description: Stable Diffusion 1.4 fine tuned on anime-styled images (4.27)
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description: Stable Diffusion 1.4 fine tuned on anime-styled images (4.27 GB)
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repo_id: hakurei/waifu-diffusion-v1-3
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config: v1-inference.yaml
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file: model-epoch09-float32.ckpt
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@ -100,7 +100,7 @@ directory
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The original Stable Diffusion version 1.4 weight file (4.27 GB)
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Download? [n] n
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[4] waifu-diffusion-1.3:
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Stable Diffusion 1.4 fine tuned on anime-styled images (4.27)
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Stable Diffusion 1.4 fine tuned on anime-styled images (4.27 GB)
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Download? [n] y
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[5] ft-mse-improved-autoencoder-840000:
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StabilityAI improved autoencoder fine-tuned for human faces (recommended; 335 MB) (recommended)
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@ -1 +0,0 @@
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020_INSTALL_MANUAL.md
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429
docs/installation/INSTALL_MANUAL.md
Normal file
429
docs/installation/INSTALL_MANUAL.md
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@ -0,0 +1,429 @@
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---
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title: Manual Installation
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---
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<figure markdown>
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# :fontawesome-brands-linux: Linux | :fontawesome-brands-apple: macOS | :fontawesome-brands-windows: Windows
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</figure>
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!!! warning "This is for advanced Users"
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who are already experienced with using conda or pip
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## Introduction
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You have two choices for manual installation, the [first one](#Conda_method)
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based on the Anaconda3 package manager (`conda`), and
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[a second one](#PIP_method) which uses basic Python virtual environment (`venv`)
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commands and the PIP package manager. Both methods require you to enter commands
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on the terminal, also known as the "console".
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On Windows systems you are encouraged to install and use the
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[Powershell](https://learn.microsoft.com/en-us/powershell/scripting/install/installing-powershell-on-windows?view=powershell-7.3),
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which provides compatibility with Linux and Mac shells and nice features such as
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command-line completion.
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### Conda method
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1. Check that your system meets the
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[hardware requirements](index.md#Hardware_Requirements) and has the
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appropriate GPU drivers installed. In particular, if you are a Linux user
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with an AMD GPU installed, you may need to install the
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[ROCm driver](https://rocmdocs.amd.com/en/latest/Installation_Guide/Installation-Guide.html).
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InvokeAI does not yet support Windows machines with AMD GPUs due to the lack
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of ROCm driver support on this platform.
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To confirm that the appropriate drivers are installed, run `nvidia-smi` on
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NVIDIA/CUDA systems, and `rocm-smi` on AMD systems. These should return
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information about the installed video card.
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Macintosh users with MPS acceleration, or anybody with a CPU-only system,
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can skip this step.
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2. You will need to install Anaconda3 and Git if they are not already
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available. Use your operating system's preferred package manager, or
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download the installers manually. You can find them here:
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- [Anaconda3](https://www.anaconda.com/)
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- [git](https://git-scm.com/downloads)
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3. Clone the [InvokeAI](https://github.com/invoke-ai/InvokeAI) source code from
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GitHub:
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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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This will create InvokeAI folder where you will follow the rest of the
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steps.
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4. Enter the newly-created InvokeAI folder:
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```bash
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cd InvokeAI
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```
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From this step forward make sure that you are working in the InvokeAI
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directory!
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5. Select the appropriate environment file:
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We have created a series of environment files suited for different operating
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systems and GPU hardware. They are located in the
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`environments-and-requirements` directory:
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<figure markdown>
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| filename | OS |
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| :----------------------: | :----------------------------: |
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| environment-lin-amd.yml | Linux with an AMD (ROCm) GPU |
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| environment-lin-cuda.yml | Linux with an NVIDIA CUDA GPU |
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| environment-mac.yml | Macintosh |
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| environment-win-cuda.yml | Windows with an NVIDA CUDA GPU |
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</figure>
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Choose the appropriate environment file for your system and link or copy it
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to `environment.yml` in InvokeAI's top-level directory. To do so, run
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following command from the repository-root:
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!!! Example ""
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=== "Macintosh and Linux"
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!!! todo "Replace `xxx` and `yyy` with the appropriate OS and GPU codes as seen in the table above"
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```bash
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ln -sf environments-and-requirements/environment-xxx-yyy.yml environment.yml
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```
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When this is done, confirm that a file `environment.yml` has been linked in
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the InvokeAI root directory and that it points to the correct file in the
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`environments-and-requirements`.
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```bash
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ls -la
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```
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=== "Windows"
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!!! todo " Since it requires admin privileges to create links, we will use the copy command to create your `environment.yml`"
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```cmd
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copy environments-and-requirements\environment-win-cuda.yml environment.yml
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```
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Afterwards verify that the file `environment.yml` has been created, either via the
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explorer or by using the command `dir` from the terminal
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```cmd
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dir
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```
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!!! warning "Do not try to run conda on directly on the subdirectory environments file. This won't work. Instead, copy or link it to the top-level directory as shown."
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6. Create the conda environment:
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```bash
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conda env update
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```
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This will create a new environment named `invokeai` and install all InvokeAI
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dependencies into it. If something goes wrong you should take a look at
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[troubleshooting](#troubleshooting).
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7. Activate the `invokeai` environment:
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In order to use the newly created environment you will first need to
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activate it
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```bash
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conda activate invokeai
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```
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Your command-line prompt should change to indicate that `invokeai` is active
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by prepending `(invokeai)`.
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8. Pre-Load the model weights files:
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!!! tip
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If you have already downloaded the weights file(s) for another Stable
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Diffusion distribution, you may skip this step (by selecting "skip" when
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prompted) and configure InvokeAI to use the previously-downloaded files. The
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process for this is described in [here](INSTALLING_MODELS.md).
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```bash
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python scripts/configure_invokeai.py
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```
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The script `configure_invokeai.py` will interactively guide you through the
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process of downloading and installing the weights files needed for InvokeAI.
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Note that the main Stable Diffusion weights file is protected by a license
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agreement that you have to agree to. The script will list the steps you need
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to take to create an account on the site that hosts the weights files,
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accept the agreement, and provide an access token that allows InvokeAI to
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legally download and install the weights files.
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If you get an error message about a module not being installed, check that
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the `invokeai` environment is active and if not, repeat step 5.
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9. Run the command-line- or the web- interface:
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!!! example ""
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!!! warning "Make sure that the conda environment is activated, which should create `(invokeai)` in front of your prompt!"
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=== "CLI"
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```bash
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python scripts/invoke.py
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```
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=== "local Webserver"
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```bash
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python scripts/invoke.py --web
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```
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=== "Public Webserver"
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```bash
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python scripts/invoke.py --web --host 0.0.0.0
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```
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If you choose the run the web interface, point your browser at
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http://localhost:9090 in order to load the GUI.
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10. Render away!
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Browse the [features](../features/CLI.md) section to learn about all the things you
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can do with InvokeAI.
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Note that some GPUs are slow to warm up. In particular, when using an AMD
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card with the ROCm driver, you may have to wait for over a minute the first
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time you try to generate an image. Fortunately, after the warm up period
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rendering will be fast.
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11. Subsequently, to relaunch the script, be sure to run "conda activate
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invokeai", enter the `InvokeAI` directory, and then launch the invoke
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script. If you forget to activate the 'invokeai' environment, the script
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will fail with multiple `ModuleNotFound` errors.
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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
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(step 5) to download the InvokeAI directory, then to update to the latest and
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greatest version, launch the Anaconda window, enter `InvokeAI` and type:
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```bash
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git pull
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conda env update
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python scripts/configure_invokeai.py --no-interactive #optional
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```
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This will bring your local copy into sync with the remote one. The last step may
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be needed to take advantage of new features or released models. The
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`--no-interactive` flag will prevent the script from prompting you to download
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the big Stable Diffusion weights files.
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## pip Install
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To install InvokeAI with only the PIP package manager, please follow these
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steps:
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1. Make sure you are using Python 3.9 or higher. The rest of the install
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procedure depends on this:
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```bash
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python -V
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```
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2. Install the `virtualenv` tool if you don't have it already:
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```bash
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pip install virtualenv
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```
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3. From within the InvokeAI top-level directory, create and activate a virtual
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environment named `invokeai`:
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```bash
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virtualenv invokeai
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source invokeai/bin/activate
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```
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4. Pick the correct `requirements*.txt` file for your hardware and operating
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system.
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We have created a series of environment files suited for different operating
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systems and GPU hardware. They are located in the
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`environments-and-requirements` directory:
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<figure markdown>
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| filename | OS |
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| :---------------------------------: | :-------------------------------------------------------------: |
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| requirements-lin-amd.txt | Linux with an AMD (ROCm) GPU |
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| requirements-lin-arm64.txt | Linux running on arm64 systems |
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| requirements-lin-cuda.txt | Linux with an NVIDIA (CUDA) GPU |
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| requirements-mac-mps-cpu.txt | Macintoshes with MPS acceleration |
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| requirements-lin-win-colab-cuda.txt | Windows with an NVIDA (CUDA) GPU<br>(supports Google Colab too) |
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</figure>
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Select the appropriate requirements file, and make a link to it from
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`requirements.txt` in the top-level InvokeAI directory. The command to do
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this from the top-level directory is:
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!!! example ""
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=== "Macintosh and Linux"
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!!! info "Replace `xxx` and `yyy` with the appropriate OS and GPU codes."
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```bash
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ln -sf environments-and-requirements/requirements-xxx-yyy.txt requirements.txt
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```
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=== "Windows"
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!!! info "on Windows, admin privileges are required to make links, so we use the copy command instead"
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```cmd
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copy environments-and-requirements\requirements-lin-win-colab-cuda.txt requirements.txt
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```
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!!! warning
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Please do not link or copy `environments-and-requirements/requirements-base.txt`.
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This is a base requirements file that does not have the platform-specific
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libraries. Also, be sure to link or copy the platform-specific file to
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a top-level file named `requirements.txt` as shown here. Running pip on
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a requirements file in a subdirectory will not work as expected.
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When this is done, confirm that a file named `requirements.txt` has been
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created in the InvokeAI root directory and that it points to the correct
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file in `environments-and-requirements`.
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5. Run PIP
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Be sure that the `invokeai` environment is active before doing this:
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```bash
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pip install --prefer-binary -r requirements.txt
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```
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---
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## Troubleshooting
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Here are some common issues and their suggested solutions.
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### Conda
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#### Conda fails before completing `conda update`
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The usual source of these errors is a package incompatibility. While we have
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tried to minimize these, over time packages get updated and sometimes introduce
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incompatibilities.
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We suggest that you search
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[Issues](https://github.com/invoke-ai/InvokeAI/issues) or the "bugs-and-support"
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channel of the [InvokeAI Discord](https://discord.gg/ZmtBAhwWhy).
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You may also try to install the broken packages manually using PIP. To do this,
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activate the `invokeai` environment, and run `pip install` with the name and
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version of the package that is causing the incompatibility. For example:
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```bash
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pip install test-tube==0.7.5
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```
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You can keep doing this until all requirements are satisfied and the `invoke.py`
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script runs without errors. Please report to
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[Issues](https://github.com/invoke-ai/InvokeAI/issues) what you were able to do
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to work around the problem so that others can benefit from your investigation.
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### Create Conda Environment fails on MacOS
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If conda create environment fails with lmdb error, this is most likely caused by Clang.
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Run brew config to see which Clang is installed on your Mac. If Clang isn't installed, that's causing the error.
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Start by installing additional XCode command line tools, followed by brew install llvm.
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```bash
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xcode-select --install
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brew install llvm
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```
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If brew config has Clang installed, update to the latest llvm and try creating the environment again.
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#### `configure_invokeai.py` or `invoke.py` crashes at an early stage
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This is usually due to an incomplete or corrupted Conda install. Make sure you
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have linked to the correct environment file and run `conda update` again.
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If the problem persists, a more extreme measure is to clear Conda's caches and
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remove the `invokeai` environment:
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```bash
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conda deactivate
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conda env remove -n invokeai
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conda clean -a
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conda update
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```
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This removes all cached library files, including ones that may have been
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corrupted somehow. (This is not supposed to happen, but does anyway).
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#### `invoke.py` crashes at a later stage
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If the CLI or web site had been working ok, but something unexpected happens
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later on during the session, you've encountered a code bug that is probably
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unrelated to an install issue. Please search
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[Issues](https://github.com/invoke-ai/InvokeAI/issues), file a bug report, or
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ask for help on [Discord](https://discord.gg/ZmtBAhwWhy)
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#### My renders are running very slowly
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You may have installed the wrong torch (machine learning) package, and the
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system is running on CPU rather than the GPU. To check, look at the log messages
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that appear when `invoke.py` is first starting up. One of the earlier lines
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should say `Using device type cuda`. On AMD systems, it will also say "cuda",
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and on Macintoshes, it should say "mps". If instead the message says it is
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running on "cpu", then you may need to install the correct torch library.
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You may be able to fix this by installing a different torch library. Here are
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the magic incantations for Conda and PIP.
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!!! todo "For CUDA systems"
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- conda
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```bash
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conda install pytorch torchvision torchaudio pytorch-cuda=11.6 -c pytorch -c nvidia
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```
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- pip
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```bash
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pip3 install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu116
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```
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!!! todo "For AMD systems"
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- conda
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```bash
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conda activate invokeai
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pip3 install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/rocm5.2/
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```
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- pip
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```bash
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pip3 install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/rocm5.2/
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```
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More information and troubleshooting tips can be found at https://pytorch.org.
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1
frontend/dist/index.html
vendored
1
frontend/dist/index.html
vendored
@ -15,7 +15,6 @@
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|
||||
<body>
|
||||
<div id="root"></div>
|
||||
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||||
<script nomodule>!function(){var e=document,t=e.createElement("script");if(!("noModule"in t)&&"onbeforeload"in t){var n=!1;e.addEventListener("beforeload",(function(e){if(e.target===t)n=!0;else if(!e.target.hasAttribute("nomodule")||!n)return;e.preventDefault()}),!0),t.type="module",t.src=".",e.head.appendChild(t),t.remove()}}();</script>
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<script nomodule crossorigin id="vite-legacy-polyfill" src="./assets/polyfills-legacy-dde3a68a.js"></script>
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<script nomodule crossorigin id="vite-legacy-entry" data-src="./assets/index-legacy-b98e060c.js">System.import(document.getElementById('vite-legacy-entry').getAttribute('data-src'))</script>
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