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Merge branch 'beta' into mdiller_ui_reorganize

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This commit is contained in:
Malcolm Diller 2022-11-08 21:22:22 -08:00
commit 69c7f22053
13 changed files with 772 additions and 214 deletions
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18
scripts/on_sd_start.bat
View File

@ -191,7 +191,9 @@ call WHERE uvicorn > .tmp
if not exist "..\models\stable-diffusion" mkdir "..\models\stable-diffusion" if not exist "..\models\stable-diffusion" mkdir "..\models\stable-diffusion"
if not exist "..\models\vae" mkdir "..\models\vae"
echo. > "..\models\stable-diffusion\Put your custom ckpt files here.txt" echo. > "..\models\stable-diffusion\Put your custom ckpt files here.txt"
echo. > "..\models\vae\Put your VAE files here.txt"
@if exist "sd-v1-4.ckpt" ( @if exist "sd-v1-4.ckpt" (
for %%I in ("sd-v1-4.ckpt") do if "%%~zI" EQU "4265380512" ( for %%I in ("sd-v1-4.ckpt") do if "%%~zI" EQU "4265380512" (
@ -321,22 +323,22 @@ echo. > "..\models\stable-diffusion\Put your custom ckpt files here.txt"
@if exist "..\models\stable-diffusion\vae-ft-mse-840000-ema-pruned.vae.pt" ( @if exist "..\models\vae\vae-ft-mse-840000-ema-pruned.ckpt" (
for %%I in ("..\models\stable-diffusion\vae-ft-mse-840000-ema-pruned.vae.pt") do if "%%~zI" EQU "334695179" ( for %%I in ("..\models\vae\vae-ft-mse-840000-ema-pruned.ckpt") do if "%%~zI" EQU "334695179" (
echo "Data files (weights) necessary for the default VAE (sd-vae-ft-mse-original) were already downloaded" echo "Data files (weights) necessary for the default VAE (sd-vae-ft-mse-original) were already downloaded"
) else ( ) else (
echo. & echo "The default VAE (sd-vae-ft-mse-original) file present at models\stable-diffusion\vae-ft-mse-840000-ema-pruned.vae.pt is invalid. It is only %%~zI bytes in size. Re-downloading.." & echo. echo. & echo "The default VAE (sd-vae-ft-mse-original) file present at models\vae\vae-ft-mse-840000-ema-pruned.ckpt is invalid. It is only %%~zI bytes in size. Re-downloading.." & echo.
del "..\models\stable-diffusion\vae-ft-mse-840000-ema-pruned.vae.pt" del "..\models\vae\vae-ft-mse-840000-ema-pruned.ckpt"
) )
) )
@if not exist "..\models\stable-diffusion\vae-ft-mse-840000-ema-pruned.vae.pt" ( @if not exist "..\models\vae\vae-ft-mse-840000-ema-pruned.ckpt" (
@echo. & echo "Downloading data files (weights) for the default VAE (sd-vae-ft-mse-original).." & echo. @echo. & echo "Downloading data files (weights) for the default VAE (sd-vae-ft-mse-original).." & echo.
@call curl -L -k https://huggingface.co/stabilityai/sd-vae-ft-mse-original/resolve/main/vae-ft-mse-840000-ema-pruned.ckpt > ..\models\stable-diffusion\vae-ft-mse-840000-ema-pruned.vae.pt @call curl -L -k https://huggingface.co/stabilityai/sd-vae-ft-mse-original/resolve/main/vae-ft-mse-840000-ema-pruned.ckpt > ..\models\vae\vae-ft-mse-840000-ema-pruned.ckpt
@if exist "..\models\stable-diffusion\vae-ft-mse-840000-ema-pruned.vae.pt" ( @if exist "..\models\vae\vae-ft-mse-840000-ema-pruned.ckpt" (
for %%I in ("..\models\stable-diffusion\vae-ft-mse-840000-ema-pruned.vae.pt") do if "%%~zI" NEQ "334695179" ( for %%I in ("..\models\vae\vae-ft-mse-840000-ema-pruned.ckpt") do if "%%~zI" NEQ "334695179" (
echo. & echo "Error: The downloaded default VAE (sd-vae-ft-mse-original) file was invalid! Bytes downloaded: %%~zI" & echo. echo. & echo "Error: The downloaded default VAE (sd-vae-ft-mse-original) file was invalid! Bytes downloaded: %%~zI" & echo.
echo. & echo "Error downloading the data files (weights) for the default VAE (sd-vae-ft-mse-original). Sorry about that, please try to:" & echo " 1. Run this installer again." & echo " 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting" & echo " 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo " 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo. echo. & echo "Error downloading the data files (weights) for the default VAE (sd-vae-ft-mse-original). Sorry about that, please try to:" & echo " 1. Run this installer again." & echo " 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting" & echo " 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB" & echo " 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues" & echo "Thanks!" & echo.
pause pause

18
scripts/on_sd_start.sh
View File

@ -170,7 +170,9 @@ fi
mkdir -p "../models/stable-diffusion" mkdir -p "../models/stable-diffusion"
mkdir -p "../models/vae"
echo "" > "../models/stable-diffusion/Put your custom ckpt files here.txt" echo "" > "../models/stable-diffusion/Put your custom ckpt files here.txt"
echo "" > "../models/vae/Put your VAE files here.txt"
if [ -f "sd-v1-4.ckpt" ]; then if [ -f "sd-v1-4.ckpt" ]; then
model_size=`find "sd-v1-4.ckpt" -printf "%s"` model_size=`find "sd-v1-4.ckpt" -printf "%s"`
@ -300,24 +302,24 @@ if [ ! -f "RealESRGAN_x4plus_anime_6B.pth" ]; then
fi fi
if [ -f "../models/stable-diffusion/vae-ft-mse-840000-ema-pruned.vae.pt" ]; then if [ -f "../models/vae/vae-ft-mse-840000-ema-pruned.ckpt" ]; then
model_size=`find ../models/stable-diffusion/vae-ft-mse-840000-ema-pruned.vae.pt -printf "%s"` model_size=`find ../models/vae/vae-ft-mse-840000-ema-pruned.ckpt -printf "%s"`
if [ "$model_size" -eq "334695179" ]; then if [ "$model_size" -eq "334695179" ]; then
echo "Data files (weights) necessary for the default VAE (sd-vae-ft-mse-original) were already downloaded" echo "Data files (weights) necessary for the default VAE (sd-vae-ft-mse-original) were already downloaded"
else else
printf "\n\nThe model file present at models/stable-diffusion/vae-ft-mse-840000-ema-pruned.vae.pt is invalid. It is only $model_size bytes in size. Re-downloading.." printf "\n\nThe model file present at models/vae/vae-ft-mse-840000-ema-pruned.ckpt is invalid. It is only $model_size bytes in size. Re-downloading.."
rm ../models/stable-diffusion/vae-ft-mse-840000-ema-pruned.vae.pt rm ../models/vae/vae-ft-mse-840000-ema-pruned.ckpt
fi fi
fi fi
if [ ! -f "../models/stable-diffusion/vae-ft-mse-840000-ema-pruned.vae.pt" ]; then if [ ! -f "../models/vae/vae-ft-mse-840000-ema-pruned.ckpt" ]; then
echo "Downloading data files (weights) for the default VAE (sd-vae-ft-mse-original).." echo "Downloading data files (weights) for the default VAE (sd-vae-ft-mse-original).."
curl -L -k https://huggingface.co/stabilityai/sd-vae-ft-mse-original/resolve/main/vae-ft-mse-840000-ema-pruned.ckpt > ../models/stable-diffusion/vae-ft-mse-840000-ema-pruned.vae.pt curl -L -k https://huggingface.co/stabilityai/sd-vae-ft-mse-original/resolve/main/vae-ft-mse-840000-ema-pruned.ckpt > ../models/vae/vae-ft-mse-840000-ema-pruned.ckpt
if [ -f "../models/stable-diffusion/vae-ft-mse-840000-ema-pruned.vae.pt" ]; then if [ -f "../models/vae/vae-ft-mse-840000-ema-pruned.ckpt" ]; then
model_size=`find ../models/stable-diffusion/vae-ft-mse-840000-ema-pruned.vae.pt -printf "%s"` model_size=`find ../models/vae/vae-ft-mse-840000-ema-pruned.ckpt -printf "%s"`
if [ ! "$model_size" -eq "334695179" ]; then if [ ! "$model_size" -eq "334695179" ]; then
printf "\n\nError: The downloaded default VAE (sd-vae-ft-mse-original) file was invalid! Bytes downloaded: $model_size\n\n" printf "\n\nError: The downloaded default VAE (sd-vae-ft-mse-original) file was invalid! Bytes downloaded: $model_size\n\n"
printf "\n\nError downloading the data files (weights) for the default VAE (sd-vae-ft-mse-original). Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n" printf "\n\nError downloading the data files (weights) for the default VAE (sd-vae-ft-mse-original). Sorry about that, please try to:\n 1. Run this installer again.\n 2. If that doesn't fix it, please try the common troubleshooting steps at https://github.com/cmdr2/stable-diffusion-ui/wiki/Troubleshooting\n 3. If those steps don't help, please copy *all* the error messages in this window, and ask the community at https://discord.com/invite/u9yhsFmEkB\n 4. If that doesn't solve the problem, please file an issue at https://github.com/cmdr2/stable-diffusion-ui/issues\nThanks!\n\n"

46
ui/index.html
View File

@ -7,7 +7,7 @@
<link rel="icon" type="image/png" href="/media/images/favicon-32x32.png" sizes="32x32"> <link rel="icon" type="image/png" href="/media/images/favicon-32x32.png" sizes="32x32">
<link rel="stylesheet" href="/media/css/fonts.css?v=1"> <link rel="stylesheet" href="/media/css/fonts.css?v=1">
<link rel="stylesheet" href="/media/css/themes.css?v=1"> <link rel="stylesheet" href="/media/css/themes.css?v=1">
<link rel="stylesheet" href="/media/css/main.css?v=4"> <link rel="stylesheet" href="/media/css/main.css?v=6">
<link rel="stylesheet" href="/media/css/auto-save.css?v=3"> <link rel="stylesheet" href="/media/css/auto-save.css?v=3">
<link rel="stylesheet" href="/media/css/modifier-thumbnails.css?v=3"> <link rel="stylesheet" href="/media/css/modifier-thumbnails.css?v=3">
<link rel="stylesheet" href="/media/css/fontawesome-all.min.css?v=1"> <link rel="stylesheet" href="/media/css/fontawesome-all.min.css?v=1">
@ -19,7 +19,7 @@
<div id="container"> <div id="container">
<div id="top-nav"> <div id="top-nav">
<div id="logo"> <div id="logo">
<h1>Stable Diffusion UI <small>v2.3.9 <span id="updateBranchLabel"></span></small></h1> <h1>Stable Diffusion UI <small>v2.3.10 <span id="updateBranchLabel"></span></small></h1>
</div> </div>
<div id="server-status"> <div id="server-status">
<div id="server-status-color">●</div> <div id="server-status-color">●</div>
@ -47,7 +47,11 @@
<textarea id="prompt" class="col-free">a photograph of an astronaut riding a horse</textarea> <textarea id="prompt" class="col-free">a photograph of an astronaut riding a horse</textarea>
<input id="prompt_from_file" name="prompt_from_file" type="file" /> <!-- hidden --> <input id="prompt_from_file" name="prompt_from_file" type="file" /> <!-- hidden -->
<label for="negative_prompt" class="collapsible" id="negative_prompt_handle">Negative Prompt <small>(optional)</small></label> <label for="negative_prompt" class="collapsible" id="negative_prompt_handle">
Negative Prompt
<a href="https://github.com/cmdr2/stable-diffusion-ui/wiki/Writing-prompts#negative-prompts" target="_blank"><i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip right">Click to learn more about Negative Prompts</span></i></a>
<small>(optional)</small>
</label>
<div class="collapsible-content"> <div class="collapsible-content">
<input id="negative_prompt" name="negative_prompt" placeholder="list the things to remove from the image (e.g. fog, green)"> <input id="negative_prompt" name="negative_prompt" placeholder="list the things to remove from the image (e.g. fog, green)">
</div> </div>
@ -64,7 +68,12 @@
</div> </div>
<br/> <br/>
<input id="enable_mask" name="enable_mask" type="checkbox"> <label for="enable_mask">In-Painting (beta) <small>(select the area which the AI will paint into)</small></label> <input id="enable_mask" name="enable_mask" type="checkbox">
<label for="enable_mask">
In-Painting (beta)
<a href="https://github.com/cmdr2/stable-diffusion-ui/wiki/Inpainting" target="_blank"><i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip right">Click to learn more about InPainting</span></i></a>
<small>(select the area which the AI will paint into)</small>
</label>
<div id="inpaintingEditor"></div> <div id="inpaintingEditor"></div>
</div> </div>
</div> </div>
@ -92,12 +101,19 @@
<div id="editor-settings-entries" class="collapsible-content"> <div id="editor-settings-entries" class="collapsible-content">
<div><table> <div><table>
<tr><b class="settings-subheader">Image Settings</b></tr> <tr><b class="settings-subheader">Image Settings</b></tr>
<tr class="pl-5"><td><label for="seed">Seed:</label></td><td><input id="seed" name="seed" size="10" value="30000"> <input id="random_seed" name="random_seed" type="checkbox" checked><label for="random_seed">Random</label></td></tr> <tr class="pl-5"><td><label for="seed">Seed:</label></td><td><input id="seed" name="seed" size="10" value="30000" onkeypress="preventNonNumericalInput(event)"> <input id="random_seed" name="random_seed" type="checkbox" checked><label for="random_seed">Random</label></td></tr>
<tr class="pl-5"><td><label for="num_outputs_total">Number of Images:</label></td><td><input id="num_outputs_total" name="num_outputs_total" value="1" size="1"> <label><small>(total)</small></label> <input id="num_outputs_parallel" name="num_outputs_parallel" value="1" size="1"> <label for="num_outputs_parallel"><small>(in parallel)</small></label></td></tr> <tr class="pl-5"><td><label for="num_outputs_total">Number of Images:</label></td><td><input id="num_outputs_total" name="num_outputs_total" value="1" size="1" onkeypress="preventNonNumericalInput(event)"> <label><small>(total)</small></label> <input id="num_outputs_parallel" name="num_outputs_parallel" value="1" size="1" onkeypress="preventNonNumericalInput(event)"> <label for="num_outputs_parallel"><small>(in parallel)</small></label></td></tr>
<tr class="pl-5"><td><label for="stable_diffusion_model">Model:</label></td><td> <tr class="pl-5"><td><label for="stable_diffusion_model">Model:</label></td><td>
<select id="stable_diffusion_model" name="stable_diffusion_model"> <select id="stable_diffusion_model" name="stable_diffusion_model">
<!-- <option value="sd-v1-4" selected>sd-v1-4</option> --> <!-- <option value="sd-v1-4" selected>sd-v1-4</option> -->
</select> </select>
<a href="https://github.com/cmdr2/stable-diffusion-ui/wiki/Custom-Models" target="_blank"><i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip right">Click to learn more about custom models</span></i></a>
</td></tr>
<tr class="pl-5"><td><label for="vae_model">Custom VAE:</i></label></td><td>
<select id="vae_model" name="vae_model">
<!-- <option value="" selected>None</option> -->
</select>
<a href="https://github.com/cmdr2/stable-diffusion-ui/wiki/VAE-Variational-Auto-Encoder" target="_blank"><i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip right">Click to learn more about VAEs</span></i></a>
</td></tr> </td></tr>
<tr id="samplerSelection" class="pl-5"><td><label for="sampler">Sampler:</label></td><td> <tr id="samplerSelection" class="pl-5"><td><label for="sampler">Sampler:</label></td><td>
<select id="sampler" name="sampler"> <select id="sampler" name="sampler">
@ -110,6 +126,7 @@
<option value="dpm2_a">dpm2_a</option> <option value="dpm2_a">dpm2_a</option>
<option value="lms">lms</option> <option value="lms">lms</option>
</select> </select>
<a href="https://github.com/cmdr2/stable-diffusion-ui/wiki/How-to-Use#samplers" target="_blank"><i class="fa-solid fa-circle-question help-btn"><span class="simple-tooltip right">Click to learn more about samplers</span></i></a>
</td></tr> </td></tr>
<tr class="pl-5"><td><label>Image Size: </label></td><td> <tr class="pl-5"><td><label>Image Size: </label></td><td>
<select id="width" name="width" value="512"> <select id="width" name="width" value="512">
@ -157,9 +174,9 @@
</select> </select>
<label for="height"><small>(height)</small></label> <label for="height"><small>(height)</small></label>
</td></tr> </td></tr>
<tr class="pl-5"><td><label for="num_inference_steps">Inference Steps:</label></td><td> <input id="num_inference_steps" name="num_inference_steps" size="4" value="25"></td></tr> <tr class="pl-5"><td><label for="num_inference_steps">Inference Steps:</label></td><td> <input id="num_inference_steps" name="num_inference_steps" size="4" value="25" onkeypress="preventNonNumericalInput(event)"></td></tr>
<tr class="pl-5"><td><label for="guidance_scale_slider">Guidance Scale:</label></td><td> <input id="guidance_scale_slider" name="guidance_scale_slider" class="editor-slider" value="75" type="range" min="10" max="500"> <input id="guidance_scale" name="guidance_scale" size="4"></td></tr> <tr class="pl-5"><td><label for="guidance_scale_slider">Guidance Scale:</label></td><td> <input id="guidance_scale_slider" name="guidance_scale_slider" class="editor-slider" value="75" type="range" min="10" max="500"> <input id="guidance_scale" name="guidance_scale" size="4" pattern="^[0-9\.]+$" onkeypress="preventNonNumericalInput(event)"></td></tr>
<tr id="prompt_strength_container" class="pl-5"><td><label for="prompt_strength_slider">Prompt Strength:</label></td><td> <input id="prompt_strength_slider" name="prompt_strength_slider" class="editor-slider" value="80" type="range" min="0" max="99"> <input id="prompt_strength" name="prompt_strength" size="4"><br/></td></tr></span> <tr id="prompt_strength_container" class="pl-5"><td><label for="prompt_strength_slider">Prompt Strength:</label></td><td> <input id="prompt_strength_slider" name="prompt_strength_slider" class="editor-slider" value="80" type="range" min="0" max="99"> <input id="prompt_strength" name="prompt_strength" size="4" pattern="^[0-9\.]+$" onkeypress="preventNonNumericalInput(event)"><br/></td></tr></span>
<tr class="pl-5"><td><label for="output_format">Output Format:</label></td><td> <tr class="pl-5"><td><label for="output_format">Output Format:</label></td><td>
<select id="output_format" name="output_format"> <select id="output_format" name="output_format">
<option value="jpeg" selected>jpeg</option> <option value="jpeg" selected>jpeg</option>
@ -170,7 +187,7 @@
<div><ul> <div><ul>
<li><b class="settings-subheader">Render Settings</b></li> <li><b class="settings-subheader">Render Settings</b></li>
<li class="pl-5"><input id="stream_image_progress" name="stream_image_progress" type="checkbox"> <label for="stream_image_progress">Show a live preview <small>(uses more VRAM, slightly slower image creation)</small></label></li> <li class="pl-5"><input id="stream_image_progress" name="stream_image_progress" type="checkbox"> <label for="stream_image_progress">Show a live preview <small>(uses more VRAM, and slower image creation)</small></label></li>
<li class="pl-5"><input id="use_face_correction" name="use_face_correction" type="checkbox" checked> <label for="use_face_correction">Fix incorrect faces and eyes <small>(uses GFPGAN)</small></label></li> <li class="pl-5"><input id="use_face_correction" name="use_face_correction" type="checkbox" checked> <label for="use_face_correction">Fix incorrect faces and eyes <small>(uses GFPGAN)</small></label></li>
<li class="pl-5"> <li class="pl-5">
<input id="use_upscale" name="use_upscale" type="checkbox"> <label for="use_upscale">Upscale image by 4x with </label> <input id="use_upscale" name="use_upscale" type="checkbox"> <label for="use_upscale">Upscale image by 4x with </label>
@ -274,14 +291,15 @@
</div> </div>
</body> </body>
<script src="media/js/parameters.js?v=1"></script> <script src="media/js/parameters.js?v=2"></script>
<script src="media/js/plugins.js?v=1"></script> <script src="media/js/plugins.js?v=1"></script>
<script src="media/js/utils.js?v=4"></script> <script src="media/js/utils.js?v=5"></script>
<script src="media/js/inpainting-editor.js?v=1"></script> <script src="media/js/inpainting-editor.js?v=1"></script>
<script src="media/js/image-modifiers.js?v=4"></script> <script src="media/js/image-modifiers.js?v=4"></script>
<script src="media/js/auto-save.js?v=3"></script> <script src="media/js/auto-save.js?v=4"></script>
<script src="media/js/main.js?v=7"></script> <script src="media/js/main.js?v=8"></script>
<script src="media/js/themes.js?v=3"></script> <script src="media/js/themes.js?v=3"></script>
<script src="media/js/dnd.js?v=6"></script>
<script> <script>
async function init() { async function init() {
await initSettings() await initSettings()

77
ui/media/css/main.css
View File

@ -593,13 +593,38 @@ input::file-selector-button {
#server-status { #server-status {
top: 66%; top: 66%;
} }
.popup > div {
padding-left: 5px !important;
padding-right: 5px !important;
}
.popup > div input, .popup > div select {
max-width: 40vw;
}
.popup .close-button {
padding: 0px !important;
margin: 24px !important;
}
.simple-tooltip.right {
right: initial;
left: 0px;
top: 50%;
transform: translate(calc(-100% + 15%), -50%);
}
:hover > .simple-tooltip.right {
transform: translate(100%, -50%);
}
} }
@media (min-width: 700px) { @media (min-width: 700px) {
#editor { #editor {
max-width: 500px; max-width: 500px;
} }
} }
.help-btn {
position: relative;
}
#promptsFromFileBtn { #promptsFromFileBtn {
font-size: 9pt; font-size: 9pt;
} }
@ -608,6 +633,20 @@ input::file-selector-button {
position: relative; position: relative;
transform: translateY(-13%); transform: translateY(-13%);
} }
#copy-image-settings {
position: relative;
cursor: pointer;
padding: 8px;
opacity: 1;
transition: opacity 0.2;
}
.collapsible:not(.active) #copy-image-settings {
display: none;
}
#copy-image-settings.hidden {
opacity: 0;
pointer-events: none;
}
.section-button { .section-button {
cursor: pointer; cursor: pointer;
@ -633,7 +672,7 @@ input::file-selector-button {
.simple-tooltip { .simple-tooltip {
border-radius: 3px; border-radius: 3px;
font-weight: bold; font-weight: bold;
font-size: 16px; font-size: 12px;
background-color: var(--background-color3); background-color: var(--background-color3);
visibility: hidden; visibility: hidden;
@ -744,6 +783,12 @@ input::file-selector-button {
transition: 0s visibility, 0.3s opacity; transition: 0s visibility, 0.3s opacity;
} }
@media only screen and (min-height: 1050px) {
.popup {
position: fixed;
}
}
.popup > div { .popup > div {
position: relative; position: relative;
background: var(--background-color2); background: var(--background-color2);
@ -806,33 +851,3 @@ input::file-selector-button {
} }
/* FLOATING FIXED STUFF */
/*
@media (min-width: 700px) {
#editor {
max-width: 500px;
}
#tab-content {
flex-direction: column;
}
#editor {
flex-direction: row;
max-width: none;
max-height: 500px;
}
#editor .line-separator {
height: inherit;
flex-basis: 8px;
flex-grow: 0;
flex-shrink: 0;
margin: 0px 16px;
}
#editor-settings-entries {
flex-direction: row;
}
}
*/

1
ui/media/js/auto-save.js
View File

@ -13,6 +13,7 @@ const SETTINGS_IDS_LIST = [
"num_outputs_total", "num_outputs_total",
"num_outputs_parallel", "num_outputs_parallel",
"stable_diffusion_model", "stable_diffusion_model",
"vae_model",
"sampler", "sampler",
"width", "width",
"height", "height",

417
ui/media/js/dnd.js Normal file
View File

@ -0,0 +1,417 @@
"use strict" // Opt in to a restricted variant of JavaScript
function parseBoolean(stringValue) {
if (typeof stringValue === 'boolean') {
return stringValue
}
if (typeof stringValue === 'number') {
return stringValue !== 0
}
if (typeof stringValue !== 'string') {
return false
}
switch(stringValue?.toLowerCase()?.trim()) {
case "true":
case "yes":
case "on":
case "1":
return true;
case "false":
case "no":
case "off":
case "0":
case null:
case undefined:
return false;
}
try {
return Boolean(JSON.parse(stringValue));
} catch {
return Boolean(stringValue)
}
}
const TASK_MAPPING = {
prompt: { name: 'Prompt',
setUI: (prompt) => {
promptField.value = prompt
},
readUI: () => promptField.value,
parse: (val) => val
},
negative_prompt: { name: 'Negative Prompt',
setUI: (negative_prompt) => {
negativePromptField.value = negative_prompt
},
readUI: () => negativePromptField.value,
parse: (val) => val
},
width: { name: 'Width',
setUI: (width) => {
const oldVal = widthField.value
widthField.value = width
if (!widthField.value) {
widthField.value = oldVal
}
},
readUI: () => parseInt(widthField.value),
parse: (val) => parseInt(val)
},
height: { name: 'Height',
setUI: (height) => {
const oldVal = heightField.value
heightField.value = height
if (!heightField.value) {
heightField.value = oldVal
}
},
readUI: () => parseInt(heightField.value),
parse: (val) => parseInt(val)
},
seed: { name: 'Seed',
setUI: (seed) => {
if (!seed) {
randomSeedField.checked = true
seedField.disabled = true
return
}
randomSeedField.checked = false
seedField.disabled = false
seedField.value = seed
},
readUI: () => (randomSeedField.checked ? Math.floor(Math.random() * 10000000) : parseInt(seedField.value)),
parse: (val) => parseInt(val)
},
num_inference_steps: { name: 'Steps',
setUI: (num_inference_steps) => {
numInferenceStepsField.value = num_inference_steps
},
readUI: () => parseInt(numInferenceStepsField.value),
parse: (val) => parseInt(val)
},
guidance_scale: { name: 'Guidance Scale',
setUI: (guidance_scale) => {
guidanceScaleField.value = guidance_scale
updateGuidanceScaleSlider()
},
readUI: () => parseFloat(guidanceScaleField.value),
parse: (val) => parseFloat(val)
},
prompt_strength: { name: 'Prompt Strength',
setUI: (prompt_strength) => {
promptStrengthField.value = prompt_strength
updatePromptStrengthSlider()
},
readUI: () => parseFloat(promptStrengthField.value),
parse: (val) => parseFloat(val)
},
init_image: { name: 'Initial Image',
setUI: (init_image) => {
initImagePreview.src = init_image
},
readUI: () => initImagePreview.src,
parse: (val) => val
},
mask: { name: 'Mask',
setUI: (mask) => {
inpaintingEditor.setImg(mask)
maskSetting.checked = Boolean(mask)
},
readUI: () => (maskSetting.checked ? inpaintingEditor.getImg() : undefined),
parse: (val) => val
},
use_face_correction: { name: 'Use Face Correction',
setUI: (use_face_correction) => {
useFaceCorrectionField.checked = parseBoolean(use_face_correction)
},
readUI: () => useFaceCorrectionField.checked,
parse: (val) => parseBoolean(val)
},
use_upscale: { name: 'Use Upscaling',
setUI: (use_upscale) => {
const oldVal = upscaleModelField.value
upscaleModelField.value = use_upscale
if (upscaleModelField.value) { // Is a valid value for the field.
useUpscalingField.checked = true
upscaleModelField.disabled = false
} else { // Not a valid value, restore the old value and disable the filter.
upscaleModelField.disabled = true
upscaleModelField.value = oldVal
useUpscalingField.checked = false
}
},
readUI: () => (useUpscalingField.checked ? upscaleModelField.value : undefined),
parse: (val) => val
},
sampler: { name: 'Sampler',
setUI: (sampler) => {
samplerField.value = sampler
},
readUI: () => samplerField.value,
parse: (val) => val
},
use_stable_diffusion_model: { name: 'Stable Diffusion model',
setUI: (use_stable_diffusion_model) => {
const oldVal = stableDiffusionModelField.value
let pathIdx = use_stable_diffusion_model.lastIndexOf('/') // Linux, Mac paths
if (pathIdx < 0) {
pathIdx = use_stable_diffusion_model.lastIndexOf('\\') // Windows paths.
}
if (pathIdx >= 0) {
use_stable_diffusion_model = use_stable_diffusion_model.slice(pathIdx + 1)
}
const modelExt = '.ckpt'
if (use_stable_diffusion_model.endsWith(modelExt)) {
use_stable_diffusion_model = use_stable_diffusion_model.slice(0, use_stable_diffusion_model.length - modelExt.length)
}
stableDiffusionModelField.value = use_stable_diffusion_model
if (!stableDiffusionModelField.value) {
stableDiffusionModelField.value = oldVal
}
},
readUI: () => stableDiffusionModelField.value,
parse: (val) => val
},
numOutputsParallel: { name: 'Parallel Images',
setUI: (numOutputsParallel) => {
numOutputsParallelField.value = numOutputsParallel
},
readUI: () => parseInt(numOutputsParallelField.value),
parse: (val) => val
},
use_cpu: { name: 'Use CPU',
setUI: (use_cpu) => {
useCPUField.checked = use_cpu
},
readUI: () => useCPUField.checked,
parse: (val) => val
},
turbo: { name: 'Turbo',
setUI: (turbo) => {
turboField.checked = turbo
},
readUI: () => turboField.checked,
parse: (val) => Boolean(val)
},
use_full_precision: { name: 'Use Full Precision',
setUI: (use_full_precision) => {
useFullPrecisionField.checked = use_full_precision
},
readUI: () => useFullPrecisionField.checked,
parse: (val) => Boolean(val)
},
stream_image_progress: { name: 'Stream Image Progress',
setUI: (stream_image_progress) => {
streamImageProgressField.checked = (parseInt(numOutputsTotalField.value) > 50 ? false : stream_image_progress)
},
readUI: () => streamImageProgressField.checked,
parse: (val) => Boolean(val)
},
show_only_filtered_image: { name: 'Show only the corrected/upscaled image',
setUI: (show_only_filtered_image) => {
showOnlyFilteredImageField.checked = show_only_filtered_image
},
readUI: () => showOnlyFilteredImageField.checked,
parse: (val) => Boolean(val)
},
output_format: { name: 'Output Format',
setUI: (output_format) => {
outputFormatField.value = output_format
},
readUI: () => outputFormatField.value,
parse: (val) => val
},
save_to_disk_path: { name: 'Save to disk path',
setUI: (save_to_disk_path) => {
saveToDiskField.checked = Boolean(save_to_disk_path)
diskPathField.value = save_to_disk_path
},
readUI: () => diskPathField.value,
parse: (val) => val
}
}
function restoreTaskToUI(task) {
if ('numOutputsTotal' in task) {
numOutputsTotalField.value = task.numOutputsTotal
}
if ('seed' in task) {
randomSeedField.checked = false
seedField.value = task.seed
}
if (!('reqBody' in task)) {
return
}
for (const key in TASK_MAPPING) {
if (key in task.reqBody) {
TASK_MAPPING[key].setUI(task.reqBody[key])
}
}
}
function readUI() {
const reqBody = {}
for (const key in TASK_MAPPING) {
reqBody[key] = TASK_MAPPING[key].readUI()
}
return {
'numOutputsTotal': parseInt(numOutputsTotalField.value),
'seed': TASK_MAPPING['seed'].readUI(),
'reqBody': reqBody
}
}
const TASK_TEXT_MAPPING = {
width: 'Width',
height: 'Height',
seed: 'Seed',
num_inference_steps: 'Steps',
guidance_scale: 'Guidance Scale',
prompt_strength: 'Prompt Strength',
use_face_correction: 'Use Face Correction',
use_upscale: 'Use Upscaling',
sampler: 'Sampler',
negative_prompt: 'Negative Prompt',
use_stable_diffusion_model: 'Stable Diffusion model'
}
const afterPromptRe = /^\s*Width\s*:\s*\d+\s*(?:\r\n|\r|\n)+\s*Height\s*:\s*\d+\s*(\r\n|\r|\n)+Seed\s*:\s*\d+\s*$/igm
function parseTaskFromText(str) {
const taskReqBody = {}
// Prompt
afterPromptRe.lastIndex = 0
const match = afterPromptRe.exec(str)
if (match) {
let prompt = str.slice(0, match.index)
str = str.slice(prompt.length)
taskReqBody.prompt = prompt.trim()
console.log('Prompt:', taskReqBody.prompt)
}
for (const key in TASK_TEXT_MAPPING) {
const name = TASK_TEXT_MAPPING[key];
let val = undefined
const reName = new RegExp(`${name}\\ *:\\ *(.*)(?:\\r\\n|\\r|\\n)*`, 'igm')
const match = reName.exec(str);
if (match) {
console.log(match)
str = str.slice(0, match.index) + str.slice(match.index + match[0].length)
val = match[1]
}
if (val !== undefined) {
taskReqBody[key] = TASK_MAPPING[key].parse(val.trim())
console.log(TASK_MAPPING[key].name + ':', taskReqBody[key])
if (!str) {
break
}
}
}
if (Object.keys(taskReqBody).length <= 0) {
return undefined
}
const task = { reqBody: taskReqBody }
if ('seed' in taskReqBody) {
task.seed = taskReqBody.seed
}
return task
}
async function readFile(file, i) {
const fileContent = (await file.text()).trim()
// JSON File.
if (fileContent.startsWith('{') && fileContent.endsWith('}')) {
try {
const task = JSON.parse(fileContent)
restoreTaskToUI(task)
} catch (e) {
console.warn(`file[${i}]:${file.name} - File couldn't be parsed.`, e)
}
return
}
// Normal txt file.
const task = parseTaskFromText(fileContent)
if (task) {
restoreTaskToUI(task)
} else {
console.warn(`file[${i}]:${file.name} - File couldn't be parsed.`)
}
}
function dropHandler(ev) {
console.log('Content dropped...')
let items = []
if (ev?.dataTransfer?.items) { // Use DataTransferItemList interface
items = Array.from(ev.dataTransfer.items)
items = items.filter(item => item.kind === 'file')
items = items.map(item => item.getAsFile())
} else if (ev?.dataTransfer?.files) { // Use DataTransfer interface
items = Array.from(ev.dataTransfer.files)
}
items = items.filter(item => item.name.toLowerCase().endsWith('.txt') || item.name.toLowerCase().endsWith('.json'))
if (items.length > 0) {
ev.preventDefault() // Prevent default behavior (Prevent file/content from being opened)
items.forEach(readFile)
}
}
function dragOverHandler(ev) {
console.log('Content in drop zone')
// Prevent default behavior (Prevent file/content from being opened)
ev.preventDefault()
ev.dataTransfer.dropEffect = "copy"
let img = new Image()
img.src = location.host + '/media/images/favicon-32x32.png'
ev.dataTransfer.setDragImage(img, 16, 16)
}
document.addEventListener("drop", dropHandler)
document.addEventListener("dragover", dragOverHandler)
const TASK_REQ_NO_EXPORT = [
"use_cpu",
"turbo",
"use_full_precision",
"save_to_disk_path"
]
// Adds a copy icon if the browser grants permission to write to clipboard.
function checkWriteToClipboardPermission (result) {
if (result.state == "granted" || result.state == "prompt") {
const resetSettings = document.getElementById('reset-image-settings')
const copyIcon = document.createElement('i')
copyIcon.id = 'copy-image-settings'
copyIcon.className = 'fa-solid fa-clipboard'
copyIcon.innerHTML = `<span class="simple-tooltip right">Copy Image Settings</span>`
copyIcon.addEventListener('click', (event) => {
event.stopPropagation()
const uiState = readUI()
TASK_REQ_NO_EXPORT.forEach((key) => delete uiState.reqBody[key])
if (uiState.reqBody.init_image && !IMAGE_REGEX.test(uiState.reqBody.init_image)) {
delete uiState.reqBody.init_image
delete uiState.reqBody.prompt_strength
}
navigator.clipboard.writeText(JSON.stringify(uiState, undefined, 4))
})
resetSettings.parentNode.insertBefore(copyIcon, resetSettings)
}
}
navigator.permissions.query({ name: "clipboard-write" }).then(checkWriteToClipboardPermission, (e) => {
if (e instanceof TypeError && typeof navigator?.clipboard?.writeText === 'function') {
// Fix for firefox https://bugzilla.mozilla.org/show_bug.cgi?id=1560373
checkWriteToClipboardPermission({state:"granted"})
}
})

43
ui/media/js/main.js
View File

@ -39,7 +39,7 @@ let useFaceCorrectionField = document.querySelector("#use_face_correction")
let useUpscalingField = document.querySelector("#use_upscale") let useUpscalingField = document.querySelector("#use_upscale")
let upscaleModelField = document.querySelector("#upscale_model") let upscaleModelField = document.querySelector("#upscale_model")
let stableDiffusionModelField = document.querySelector('#stable_diffusion_model') let stableDiffusionModelField = document.querySelector('#stable_diffusion_model')
let vaeModelField = document.querySelector('#default_vae_model') let vaeModelField = document.querySelector('#vae_model')
let outputFormatField = document.querySelector('#output_format') let outputFormatField = document.querySelector('#output_format')
let showOnlyFilteredImageField = document.querySelector("#show_only_filtered_image") let showOnlyFilteredImageField = document.querySelector("#show_only_filtered_image")
let updateBranchLabel = document.querySelector("#updateBranchLabel") let updateBranchLabel = document.querySelector("#updateBranchLabel")
@ -340,10 +340,10 @@ function onDownloadImageClick(req, img) {
imgDownload.click() imgDownload.click()
} }
function modifyCurrentRequest(req, ...reqDiff) { function modifyCurrentRequest(...reqDiff) {
const newTaskRequest = getCurrentUserRequest() const newTaskRequest = getCurrentUserRequest()
newTaskRequest.reqBody = Object.assign({}, req, ...reqDiff, { newTaskRequest.reqBody = Object.assign(newTaskRequest.reqBody, ...reqDiff, {
use_cpu: useCPUField.checked use_cpu: useCPUField.checked
}) })
newTaskRequest.seed = newTaskRequest.reqBody.seed newTaskRequest.seed = newTaskRequest.reqBody.seed
@ -774,6 +774,7 @@ function getCurrentUserRequest() {
use_cpu: useCPUField.checked, use_cpu: useCPUField.checked,
use_full_precision: useFullPrecisionField.checked, use_full_precision: useFullPrecisionField.checked,
use_stable_diffusion_model: stableDiffusionModelField.value, use_stable_diffusion_model: stableDiffusionModelField.value,
use_vae_model: vaeModelField.value,
stream_progress_updates: true, stream_progress_updates: true,
stream_image_progress: (numOutputsTotal > 50 ? false : streamImageProgressField.checked), stream_image_progress: (numOutputsTotal > 50 ? false : streamImageProgressField.checked),
show_only_filtered_image: showOnlyFilteredImageField.checked, show_only_filtered_image: showOnlyFilteredImageField.checked,
@ -823,7 +824,10 @@ function makeImage() {
function createTask(task) { function createTask(task) {
let taskConfig = `Seed: ${task.seed}, Sampler: ${task.reqBody.sampler}, Inference Steps: ${task.reqBody.num_inference_steps}, Guidance Scale: ${task.reqBody.guidance_scale}, Model: ${task.reqBody.use_stable_diffusion_model}` let taskConfig = `Seed: ${task.seed}, Sampler: ${task.reqBody.sampler}, Inference Steps: ${task.reqBody.num_inference_steps}, Guidance Scale: ${task.reqBody.guidance_scale}, Model: ${task.reqBody.use_stable_diffusion_model}`
if (negativePromptField.value.trim() !== '') { if (task.reqBody.use_vae_model.trim() !== '') {
taskConfig += `, VAE: ${task.reqBody.use_vae_model}`
}
if (task.reqBody.negative_prompt.trim() !== '') {
taskConfig += `, Negative Prompt: ${task.reqBody.negative_prompt}` taskConfig += `, Negative Prompt: ${task.reqBody.negative_prompt}`
} }
if (task.reqBody.init_image !== undefined) { if (task.reqBody.init_image !== undefined) {
@ -1141,12 +1145,6 @@ useBetaChannelField.addEventListener('click', async function(e) {
}) })
}) })
vaeModelField.addEventListener('change', async function() {
await changeAppConfig({
'model_vae': this.value
})
})
async function getAppConfig() { async function getAppConfig() {
try { try {
let res = await fetch('/get/app_config') let res = await fetch('/get/app_config')
@ -1165,22 +1163,25 @@ async function getAppConfig() {
async function getModels() { async function getModels() {
try { try {
var model_setting_key = "stable_diffusion_model" var sd_model_setting_key = "stable_diffusion_model"
var selectedModel = SETTINGS[model_setting_key].value var vae_model_setting_key = "vae_model"
var selectedSDModel = SETTINGS[sd_model_setting_key].value
var selectedVaeModel = SETTINGS[vae_model_setting_key].value
let res = await fetch('/get/models') let res = await fetch('/get/models')
const models = await res.json() const models = await res.json()
let activeModels = models['active'] console.log('get models response', models)
let modelOptions = models['options'] let modelOptions = models['options']
let stableDiffusionOptions = modelOptions['stable-diffusion'] let stableDiffusionOptions = modelOptions['stable-diffusion']
let vaeOptions = modelOptions['vae'] let vaeOptions = modelOptions['vae']
let activeVae = activeModels['vae'] vaeOptions.unshift('') // add a None option
function createModelOptions(modelField, selectedModel) { function createModelOptions(modelField, selectedModel) {
return function(modelName) { return function(modelName) {
let modelOption = document.createElement('option') let modelOption = document.createElement('option')
modelOption.value = modelName modelOption.value = modelName
modelOption.innerText = modelName modelOption.innerText = modelName !== '' ? modelName : 'None'
if (modelName === selectedModel) { if (modelName === selectedModel) {
modelOption.selected = true modelOption.selected = true
@ -1190,16 +1191,14 @@ async function getModels() {
} }
} }
stableDiffusionOptions.forEach(createModelOptions(stableDiffusionModelField, selectedModel)) stableDiffusionOptions.forEach(createModelOptions(stableDiffusionModelField, selectedSDModel))
vaeOptions.forEach(createModelOptions(vaeModelField, activeVae)) vaeOptions.forEach(createModelOptions(vaeModelField, selectedVaeModel))
// TODO: set default for model here too // TODO: set default for model here too
SETTINGS[model_setting_key].default = stableDiffusionOptions[0] SETTINGS[sd_model_setting_key].default = stableDiffusionOptions[0]
if (getSetting(model_setting_key) == '' || SETTINGS[model_setting_key].value == '') { if (getSetting(sd_model_setting_key) == '' || SETTINGS[sd_model_setting_key].value == '') {
setSetting(model_setting_key, stableDiffusionOptions[0]) setSetting(sd_model_setting_key, stableDiffusionOptions[0])
} }
console.log('get models response', models)
} catch (e) { } catch (e) {
console.log('get models error', e) console.log('get models error', e)
} }

5
ui/media/js/parameters.js
View File

@ -51,11 +51,6 @@ var PARAMETERS = [
return `<input id="${parameter.id}" name="${parameter.id}" size="30" disabled>` return `<input id="${parameter.id}" name="${parameter.id}" size="30" disabled>`
} }
}, },
{
id: "default_vae_model",
type: ParameterType.select, // Note: options generated dynamically
label: "Default VAE",
},
{ {
id: "sound_toggle", id: "sound_toggle",
type: ParameterType.checkbox, type: ParameterType.checkbox,

22
ui/media/js/utils.js
View File

@ -30,9 +30,15 @@ function toggleCollapsible(element) {
collapsibleHeader.classList.toggle("active") collapsibleHeader.classList.toggle("active")
let content = getNextSibling(collapsibleHeader, '.collapsible-content') let content = getNextSibling(collapsibleHeader, '.collapsible-content')
if (!collapsibleHeader.classList.contains("active")) { if (!collapsibleHeader.classList.contains("active")) {
handle.innerHTML = '&#x2795;' // plus content.style.display = "none"
if (handle != null) { // render results don't have a handle
handle.innerHTML = '&#x2795;' // plus
}
} else { } else {
handle.innerHTML = '&#x2796;' // minus content.style.display = "block"
if (handle != null) { // render results don't have a handle
handle.innerHTML = '&#x2796;' // minus
}
} }
if (COLLAPSIBLES_INITIALIZED && COLLAPSIBLE_PANELS.includes(element)) { if (COLLAPSIBLES_INITIALIZED && COLLAPSIBLE_PANELS.includes(element)) {
@ -340,3 +346,15 @@ function asyncDelay(timeout) {
setTimeout(resolve, timeout, true) setTimeout(resolve, timeout, true)
}) })
} }
function preventNonNumericalInput(e) {
e = e || window.event;
let charCode = (typeof e.which == "undefined") ? e.keyCode : e.which;
let charStr = String.fromCharCode(charCode);
let re = e.target.getAttribute('pattern') || '^[0-9]+$'
re = new RegExp(re)
if (!charStr.match(re)) {
e.preventDefault();
}
}

4
ui/sd_internal/__init__.py
View File

@ -18,7 +18,6 @@ class Request:
precision: str = "autocast" # or "full" precision: str = "autocast" # or "full"
save_to_disk_path: str = None save_to_disk_path: str = None
turbo: bool = True turbo: bool = True
use_cpu: bool = False
use_full_precision: bool = False use_full_precision: bool = False
use_face_correction: str = None # or "GFPGANv1.3" use_face_correction: str = None # or "GFPGANv1.3"
use_upscale: str = None # or "RealESRGAN_x4plus" or "RealESRGAN_x4plus_anime_6B" use_upscale: str = None # or "RealESRGAN_x4plus" or "RealESRGAN_x4plus_anime_6B"
@ -50,7 +49,7 @@ class Request:
"output_format": self.output_format, "output_format": self.output_format,
} }
def to_string(self): def __str__(self):
return f''' return f'''
session_id: {self.session_id} session_id: {self.session_id}
prompt: {self.prompt} prompt: {self.prompt}
@ -64,7 +63,6 @@ class Request:
precision: {self.precision} precision: {self.precision}
save_to_disk_path: {self.save_to_disk_path} save_to_disk_path: {self.save_to_disk_path}
turbo: {self.turbo} turbo: {self.turbo}
use_cpu: {self.use_cpu}
use_full_precision: {self.use_full_precision} use_full_precision: {self.use_full_precision}
use_face_correction: {self.use_face_correction} use_face_correction: {self.use_face_correction}
use_upscale: {self.use_upscale} use_upscale: {self.use_upscale}

96
ui/sd_internal/runtime.py
View File

@ -45,6 +45,25 @@ from io import BytesIO
from threading import local as LocalThreadVars from threading import local as LocalThreadVars
thread_data = LocalThreadVars() thread_data = LocalThreadVars()
def get_processor_name():
try:
import platform, subprocess
if platform.system() == "Windows":
return platform.processor()
elif platform.system() == "Darwin":
os.environ['PATH'] = os.environ['PATH'] + os.pathsep + '/usr/sbin'
command ="sysctl -n machdep.cpu.brand_string"
return subprocess.check_output(command).strip()
elif platform.system() == "Linux":
command = "cat /proc/cpuinfo"
all_info = subprocess.check_output(command, shell=True).decode().strip()
for line in all_info.split("\n"):
if "model name" in line:
return re.sub( ".*model name.*:", "", line,1).strip()
except:
print(traceback.format_exc())
return "cpu"
def device_would_fail(device): def device_would_fail(device):
if device == 'cpu': return None if device == 'cpu': return None
# Returns None when no issues found, otherwise returns the detected error str. # Returns None when no issues found, otherwise returns the detected error str.
@ -68,17 +87,17 @@ def device_select(device):
print(failure_msg) print(failure_msg)
return False return False
device_name = torch.cuda.get_device_name(device) thread_data.device_name = torch.cuda.get_device_name(device)
thread_data.device = device
# otherwise these NVIDIA cards create green images # Force full precision on 1660 and 1650 NVIDIA cards to avoid creating green images
thread_data.force_full_precision = ('nvidia' in device_name.lower() or 'geforce' in device_name.lower()) and (' 1660' in device_name or ' 1650' in device_name) device_name = thread_data.device_name.lower()
thread_data.force_full_precision = ('nvidia' in device_name or 'geforce' in device_name) and (' 1660' in device_name or ' 1650' in device_name)
if thread_data.force_full_precision: if thread_data.force_full_precision:
print('forcing full precision on NVIDIA 16xx cards, to avoid green images. GPU detected: ', device_name) print('forcing full precision on NVIDIA 16xx cards, to avoid green images. GPU detected: ', thread_data.device_name)
# Apply force_full_precision now before models are loaded. # Apply force_full_precision now before models are loaded.
thread_data.precision = 'full' thread_data.precision = 'full'
thread_data.device = device
thread_data.has_valid_gpu = True
return True return True
def device_init(device_selection=None): def device_init(device_selection=None):
@ -100,27 +119,31 @@ def device_init(device_selection=None):
thread_data.model_is_half = False thread_data.model_is_half = False
thread_data.model_fs_is_half = False thread_data.model_fs_is_half = False
thread_data.device = None thread_data.device = None
thread_data.device_name = None
thread_data.unet_bs = 1 thread_data.unet_bs = 1
thread_data.precision = 'autocast' thread_data.precision = 'autocast'
thread_data.sampler_plms = None thread_data.sampler_plms = None
thread_data.sampler_ddim = None thread_data.sampler_ddim = None
thread_data.turbo = False thread_data.turbo = False
thread_data.has_valid_gpu = False
thread_data.force_full_precision = False thread_data.force_full_precision = False
thread_data.reduced_memory = True thread_data.reduced_memory = True
if device_selection.lower() == 'cpu': device_selection = device_selection.lower()
print('CPU requested, skipping gpu init.')
if device_selection == 'cpu':
thread_data.device = 'cpu' thread_data.device = 'cpu'
thread_data.device_name = get_processor_name()
print('Render device CPU available as', thread_data.device_name)
return return
if not torch.cuda.is_available(): if not torch.cuda.is_available():
if device_selection == 'auto' or device_selection == 'current': if device_selection == 'auto' or device_selection == 'current':
print('WARNING: torch.cuda is not available. Using the CPU, but this will be very slow!') print('WARNING: Could not find a compatible GPU. Using the CPU, but this will be very slow!')
thread_data.device = 'cpu' thread_data.device = 'cpu'
thread_data.device_name = get_processor_name()
return return
else: else:
raise EnvironmentError('torch.cuda is not available.') raise EnvironmentError(f'Could not find a compatible GPU for the requested device_selection: {device_selection}!')
device_count = torch.cuda.device_count() device_count = torch.cuda.device_count()
if device_count <= 1 and device_selection == 'auto': if device_count <= 1 and device_selection == 'auto':
device_selection = 'current' # Use 'auto' only when there is more than one compatible device found. device_selection = 'current' # Use 'auto' only when there is more than one compatible device found.
@ -141,10 +164,10 @@ def device_init(device_selection=None):
print(f'Setting GPU:{device} as active') print(f'Setting GPU:{device} as active')
torch.cuda.device(device) torch.cuda.device(device)
return return
if isinstance(device_selection, str):
device_selection = device_selection.lower() if device_selection.startswith('gpu:'):
if device_selection.startswith('gpu:'): device_selection = int(device_selection[4:])
device_selection = int(device_selection[4:])
if device_selection != 'cuda' and device_selection != 'current' and device_selection != 'gpu': if device_selection != 'cuda' and device_selection != 'current' and device_selection != 'gpu':
if device_select(device_selection): if device_select(device_selection):
if isinstance(device_selection, int): if isinstance(device_selection, int):
@ -162,6 +185,7 @@ def device_init(device_selection=None):
return return
print('WARNING: No compatible GPU found. Using the CPU, but this will be very slow!') print('WARNING: No compatible GPU found. Using the CPU, but this will be very slow!')
thread_data.device = 'cpu' thread_data.device = 'cpu'
thread_data.device_name = get_processor_name()
def is_first_cuda_device(device): def is_first_cuda_device(device):
if device is None: return False if device is None: return False
@ -234,13 +258,15 @@ def load_model_ckpt():
_, _ = modelFS.load_state_dict(sd, strict=False) _, _ = modelFS.load_state_dict(sd, strict=False)
if thread_data.vae_file is not None: if thread_data.vae_file is not None:
if os.path.exists(thread_data.vae_file + '.vae.pt'): for model_extension in ['.ckpt', '.vae.pt']:
print(f"Loading VAE weights from: {thread_data.vae_file}.vae.pt") if os.path.exists(thread_data.vae_file + model_extension):
vae_ckpt = torch.load(thread_data.vae_file + '.vae.pt', map_location="cpu") print(f"Loading VAE weights from: {thread_data.vae_file}{model_extension}")
vae_dict = {k: v for k, v in vae_ckpt["state_dict"].items() if k[0:4] != "loss"} vae_ckpt = torch.load(thread_data.vae_file + model_extension, map_location="cpu")
modelFS.first_stage_model.load_state_dict(vae_dict, strict=False) vae_dict = {k: v for k, v in vae_ckpt["state_dict"].items() if k[0:4] != "loss"}
else: modelFS.first_stage_model.load_state_dict(vae_dict, strict=False)
print(f'Cannot find VAE file: {thread_data.vae_file}.vae.pt') break
else:
print(f'Cannot find VAE file: {thread_data.vae_file}{model_extension}')
modelFS.eval() modelFS.eval()
if thread_data.device != 'cpu': if thread_data.device != 'cpu':
@ -261,7 +287,12 @@ def load_model_ckpt():
thread_data.model_is_half = False thread_data.model_is_half = False
thread_data.model_fs_is_half = False thread_data.model_fs_is_half = False
print('loaded', thread_data.ckpt_file, 'as', model.device, '->', modelCS.cond_stage_model.device, '->', thread_data.modelFS.device, 'using precision', thread_data.precision) print(f'''loaded model
model file: {thread_data.ckpt_file}.ckpt
model.device: {model.device}
modelCS.device: {modelCS.cond_stage_model.device}
modelFS.device: {thread_data.modelFS.device}
using precision: {thread_data.precision}''')
def unload_filters(): def unload_filters():
if thread_data.model_gfpgan is not None: if thread_data.model_gfpgan is not None:
@ -341,13 +372,21 @@ def load_model_real_esrgan():
thread_data.model_real_esrgan.model.name = thread_data.real_esrgan_file thread_data.model_real_esrgan.model.name = thread_data.real_esrgan_file
print('loaded ', thread_data.real_esrgan_file, 'to', thread_data.model_real_esrgan.device, 'precision', thread_data.precision) print('loaded ', thread_data.real_esrgan_file, 'to', thread_data.model_real_esrgan.device, 'precision', thread_data.precision)
def get_session_out_path(disk_path, session_id):
if disk_path is None: return None
if session_id is None: return None
session_out_path = os.path.join(disk_path, filename_regex.sub('_',session_id))
os.makedirs(session_out_path, exist_ok=True)
return session_out_path
def get_base_path(disk_path, session_id, prompt, img_id, ext, suffix=None): def get_base_path(disk_path, session_id, prompt, img_id, ext, suffix=None):
if disk_path is None: return None if disk_path is None: return None
if session_id is None: return None if session_id is None: return None
if ext is None: raise Exception('Missing ext') if ext is None: raise Exception('Missing ext')
session_out_path = os.path.join(disk_path, session_id) session_out_path = get_session_out_path(disk_path, session_id)
os.makedirs(session_out_path, exist_ok=True)
prompt_flattened = filename_regex.sub('_', prompt)[:50] prompt_flattened = filename_regex.sub('_', prompt)[:50]
@ -475,7 +514,7 @@ def do_mk_img(req: Request):
thread_data.vae_file = req.use_vae_model thread_data.vae_file = req.use_vae_model
needs_model_reload = True needs_model_reload = True
if thread_data.has_valid_gpu: if thread_data.device != 'cpu':
if (thread_data.precision == 'autocast' and (req.use_full_precision or not thread_data.model_is_half)) or \ if (thread_data.precision == 'autocast' and (req.use_full_precision or not thread_data.model_is_half)) or \
(thread_data.precision == 'full' and not req.use_full_precision and not thread_data.force_full_precision): (thread_data.precision == 'full' and not req.use_full_precision and not thread_data.force_full_precision):
thread_data.precision = 'full' if req.use_full_precision else 'autocast' thread_data.precision = 'full' if req.use_full_precision else 'autocast'
@ -500,7 +539,7 @@ def do_mk_img(req: Request):
opt_f = 8 opt_f = 8
opt_ddim_eta = 0.0 opt_ddim_eta = 0.0
print(req.to_string(), '\n device', thread_data.device) print(req, '\n device', torch.device(thread_data.device), "as", thread_data.device_name)
print('\n\n Using precision:', thread_data.precision) print('\n\n Using precision:', thread_data.precision)
seed_everything(opt_seed) seed_everything(opt_seed)
@ -552,8 +591,7 @@ def do_mk_img(req: Request):
print(f"target t_enc is {t_enc} steps") print(f"target t_enc is {t_enc} steps")
if req.save_to_disk_path is not None: if req.save_to_disk_path is not None:
session_out_path = os.path.join(req.save_to_disk_path, req.session_id) session_out_path = get_session_out_path(req.save_to_disk_path, req.session_id)
os.makedirs(session_out_path, exist_ok=True)
else: else:
session_out_path = None session_out_path = None

73
ui/sd_internal/task_manager.py
View File

@ -21,6 +21,7 @@ LOCK_TIMEOUT = 15 # Maximum locking time in seconds before failing a task.
# It's better to get an exception than a deadlock... ALWAYS use timeout in critical paths. # It's better to get an exception than a deadlock... ALWAYS use timeout in critical paths.
DEVICE_START_TIMEOUT = 60 # seconds - Maximum time to wait for a render device to init. DEVICE_START_TIMEOUT = 60 # seconds - Maximum time to wait for a render device to init.
CPU_UNLOAD_TIMEOUT = 4 * 60 # seconds - Idle time before CPU unload resource when GPUs are present.
class SymbolClass(type): # Print nicely formatted Symbol names. class SymbolClass(type): # Print nicely formatted Symbol names.
def __repr__(self): return self.__qualname__ def __repr__(self): return self.__qualname__
@ -38,6 +39,7 @@ class RenderTask(): # Task with output queue and completion lock.
def __init__(self, req: Request): def __init__(self, req: Request):
self.request: Request = req # Initial Request self.request: Request = req # Initial Request
self.response: Any = None # Copy of the last reponse self.response: Any = None # Copy of the last reponse
self.render_device = None
self.temp_images:list = [None] * req.num_outputs * (1 if req.show_only_filtered_image else 2) self.temp_images:list = [None] * req.num_outputs * (1 if req.show_only_filtered_image else 2)
self.error: Exception = None self.error: Exception = None
self.lock: threading.Lock = threading.Lock() # Locks at task start and unlocks when task is completed self.lock: threading.Lock = threading.Lock() # Locks at task start and unlocks when task is completed
@ -68,7 +70,8 @@ class ImageRequest(BaseModel):
# allow_nsfw: bool = False # allow_nsfw: bool = False
save_to_disk_path: str = None save_to_disk_path: str = None
turbo: bool = True turbo: bool = True
use_cpu: bool = False use_cpu: bool = False ##TODO Remove after UI and plugins transition.
render_device: str = None
use_full_precision: bool = False use_full_precision: bool = False
use_face_correction: str = None # or "GFPGANv1.3" use_face_correction: str = None # or "GFPGANv1.3"
use_upscale: str = None # or "RealESRGAN_x4plus" or "RealESRGAN_x4plus_anime_6B" use_upscale: str = None # or "RealESRGAN_x4plus" or "RealESRGAN_x4plus_anime_6B"
@ -89,7 +92,7 @@ class FilterRequest(BaseModel):
height: int = 512 height: int = 512
save_to_disk_path: str = None save_to_disk_path: str = None
turbo: bool = True turbo: bool = True
use_cpu: bool = False render_device: str = None
use_full_precision: bool = False use_full_precision: bool = False
output_format: str = "jpeg" # or "png" output_format: str = "jpeg" # or "png"
@ -219,26 +222,24 @@ def thread_get_next_task():
queued_task.error = Exception('cuda:0 is not available with the current config. Remove GFPGANer filter to run task.') queued_task.error = Exception('cuda:0 is not available with the current config. Remove GFPGANer filter to run task.')
task = queued_task task = queued_task
break break
if queued_task.request.use_cpu: if queued_task.render_device == 'cpu':
queued_task.error = Exception('Cpu cannot be used to run this task. Remove GFPGANer filter to run task.') queued_task.error = Exception('Cpu cannot be used to run this task. Remove GFPGANer filter to run task.')
task = queued_task task = queued_task
break break
if not runtime.is_first_cuda_device(runtime.thread_data.device): if not runtime.is_first_cuda_device(runtime.thread_data.device):
continue # Wait for cuda:0 continue # Wait for cuda:0
if queued_task.request.use_cpu and runtime.thread_data.device != 'cpu': if queued_task.render_device and runtime.thread_data.device != queued_task.render_device:
if is_alive('cpu') > 0: # Is asking for a specific render device.
continue # CPU Tasks, Skip GPU device if is_alive(queued_task.render_device) > 0:
continue # requested device alive, skip current one.
else: else:
queued_task.error = Exception('Cpu is not enabled in render_devices.') # Requested device is not active, return error to UI.
task = queued_task queued_task.error = Exception(str(queued_task.render_device) + ' is not currently active.')
break
if not queued_task.request.use_cpu and runtime.thread_data.device == 'cpu':
if is_alive() > 1: # cpu is alive, so need more than one.
continue # GPU Tasks, don't run on CPU unless there is nothing else.
else:
queued_task.error = Exception('No active gpu found. Please check the error message in the command-line window at startup.')
task = queued_task task = queued_task
break break
if not queued_task.render_device and runtime.thread_data.device == 'cpu' and is_alive() > 1:
# not asking for any specific devices, cpu want to grab task but other render devices are alive.
continue # Skip Tasks, don't run on CPU unless there is nothing else or user asked for it.
task = queued_task task = queued_task
break break
if task is not None: if task is not None:
@ -252,11 +253,15 @@ def thread_render(device):
from . import runtime from . import runtime
try: try:
runtime.device_init(device) runtime.device_init(device)
except: except Exception as e:
print(traceback.format_exc()) print(traceback.format_exc())
weak_thread_data[threading.current_thread()] = {
'error': e
}
return return
weak_thread_data[threading.current_thread()] = { weak_thread_data[threading.current_thread()] = {
'device': runtime.thread_data.device 'device': runtime.thread_data.device,
'device_name': runtime.thread_data.device_name
} }
if runtime.thread_data.device != 'cpu' or is_alive() == 1: if runtime.thread_data.device != 'cpu' or is_alive() == 1:
preload_model() preload_model()
@ -268,6 +273,12 @@ def thread_render(device):
return return
task = thread_get_next_task() task = thread_get_next_task()
if task is None: if task is None:
if runtime.thread_data.device == 'cpu' and is_alive() > 1 and hasattr(runtime.thread_data, 'lastActive') and time.time() - runtime.thread_data.lastActive > CPU_UNLOAD_TIMEOUT:
# GPUs present and CPU is idle. Unload resources.
runtime.unload_models()
runtime.unload_filters()
del runtime.thread_data.lastActive
print('unloaded models from CPU because it was idle for too long')
time.sleep(1) time.sleep(1)
continue continue
if task.error is not None: if task.error is not None:
@ -280,9 +291,12 @@ def thread_render(device):
task.response = {"status": 'failed', "detail": str(task.error)} task.response = {"status": 'failed', "detail": str(task.error)}
task.buffer_queue.put(json.dumps(task.response)) task.buffer_queue.put(json.dumps(task.response))
continue continue
print(f'Session {task.request.session_id} starting task {id(task)}') print(f'Session {task.request.session_id} starting task {id(task)} on {runtime.thread_data.device_name}')
if not task.lock.acquire(blocking=False): raise Exception('Got locked task from queue.') if not task.lock.acquire(blocking=False): raise Exception('Got locked task from queue.')
try: try:
if runtime.thread_data.device == 'cpu' and is_alive() > 1:
# CPU is not the only device. Keep track of active time to unload resources later.
runtime.thread_data.lastActive = time.time()
# Open data generator. # Open data generator.
res = runtime.mk_img(task.request) res = runtime.mk_img(task.request)
if current_model_path == task.request.use_stable_diffusion_model: if current_model_path == task.request.use_stable_diffusion_model:
@ -331,7 +345,7 @@ def thread_render(device):
elif task.error is not None: elif task.error is not None:
print(f'Session {task.request.session_id} task {id(task)} failed!') print(f'Session {task.request.session_id} task {id(task)} failed!')
else: else:
print(f'Session {task.request.session_id} task {id(task)} completed.') print(f'Session {task.request.session_id} task {id(task)} completed by {runtime.thread_data.device_name}.')
current_state = ServerStates.Online current_state = ServerStates.Online
def get_cached_task(session_id:str, update_ttl:bool=False): def get_cached_task(session_id:str, update_ttl:bool=False):
@ -341,6 +355,21 @@ def get_cached_task(session_id:str, update_ttl:bool=False):
return None return None
return task_cache.tryGet(session_id) return task_cache.tryGet(session_id)
def get_devices():
if not manager_lock.acquire(blocking=True, timeout=LOCK_TIMEOUT): raise Exception('get_devices' + ERR_LOCK_FAILED)
try:
device_dict = {}
for rthread in render_threads:
if not rthread.is_alive():
continue
weak_data = weak_thread_data.get(rthread)
if not weak_data or not 'device' in weak_data or not 'device_name' in weak_data:
continue
device_dict.update({weak_data['device']:weak_data['device_name']})
return device_dict
finally:
manager_lock.release()
def is_first_cuda_device(device): def is_first_cuda_device(device):
from . import runtime # When calling runtime from outside thread_render DO NOT USE thread specific attributes or functions. from . import runtime # When calling runtime from outside thread_render DO NOT USE thread specific attributes or functions.
return runtime.is_first_cuda_device(device) return runtime.is_first_cuda_device(device)
@ -352,8 +381,7 @@ def is_alive(name=None):
for rthread in render_threads: for rthread in render_threads:
if name is not None: if name is not None:
weak_data = weak_thread_data.get(rthread) weak_data = weak_thread_data.get(rthread)
if weak_data is None or weak_data['device'] is None: if weak_data is None or not 'device' in weak_data or weak_data['device'] is None:
print('The thread', rthread.name, 'is registered but has no data store in the task manager.')
continue continue
thread_name = str(weak_data['device']).lower() thread_name = str(weak_data['device']).lower()
if is_first_cuda_device(name): if is_first_cuda_device(name):
@ -380,6 +408,8 @@ def start_render_thread(device='auto'):
manager_lock.release() manager_lock.release()
timeout = DEVICE_START_TIMEOUT timeout = DEVICE_START_TIMEOUT
while not rthread.is_alive() or not rthread in weak_thread_data or not 'device' in weak_thread_data[rthread]: while not rthread.is_alive() or not rthread in weak_thread_data or not 'device' in weak_thread_data[rthread]:
if rthread in weak_thread_data and 'error' in weak_thread_data[rthread]:
return False
if timeout <= 0: if timeout <= 0:
return False return False
timeout -= 1 timeout -= 1
@ -416,7 +446,6 @@ def render(req : ImageRequest):
r.sampler = req.sampler r.sampler = req.sampler
# r.allow_nsfw = req.allow_nsfw # r.allow_nsfw = req.allow_nsfw
r.turbo = req.turbo r.turbo = req.turbo
r.use_cpu = req.use_cpu
r.use_full_precision = req.use_full_precision r.use_full_precision = req.use_full_precision
r.save_to_disk_path = req.save_to_disk_path r.save_to_disk_path = req.save_to_disk_path
r.use_upscale: str = req.use_upscale r.use_upscale: str = req.use_upscale
@ -433,6 +462,8 @@ def render(req : ImageRequest):
r.stream_image_progress = False r.stream_image_progress = False
new_task = RenderTask(r) new_task = RenderTask(r)
new_task.render_device = req.render_device
if task_cache.put(r.session_id, new_task, TASK_TTL): if task_cache.put(r.session_id, new_task, TASK_TTL):
# Use twice the normal timeout for adding user requests. # Use twice the normal timeout for adding user requests.
# Tries to force task_cache.put to fail before tasks_queue.put would. # Tries to force task_cache.put to fail before tasks_queue.put would.

166
ui/server.py
View File

@ -30,9 +30,6 @@ APP_CONFIG_DEFAULT_MODELS = [
'custom-model', # Check if user has a custom model, use it first. 'custom-model', # Check if user has a custom model, use it first.
'sd-v1-4', # Default fallback. 'sd-v1-4', # Default fallback.
] ]
APP_CONFIG_DEFAULT_VAE = [
'vae-ft-mse-840000-ema-pruned', # Default fallback.
]
from fastapi import FastAPI, HTTPException from fastapi import FastAPI, HTTPException
from fastapi.staticfiles import StaticFiles from fastapi.staticfiles import StaticFiles
@ -107,11 +104,24 @@ def setConfig(config):
config_bat = [ config_bat = [
f"@set update_branch={config['update_branch']}" f"@set update_branch={config['update_branch']}"
] ]
if len(gpu_devices) > 0 and not has_first_cuda_device:
config_bat.append('::Set the devices visible inside SD-UI here') if os.getenv('CUDA_VISIBLE_DEVICES') is None:
config_bat.append(f"::@set CUDA_VISIBLE_DEVICES={','.join(gpu_devices)}") # Needs better detection for edge cases, add as a comment for now. if len(gpu_devices) > 0 and not has_first_cuda_device:
print('Add the line "@set CUDA_VISIBLE_DEVICES=N" where N is the GPUs to use to config.bat') config_bat.append('::Set the devices visible inside SD-UI here')
config_bat.append(f"::@set CUDA_VISIBLE_DEVICES={','.join(gpu_devices)}") # Needs better detection for edge cases, add as a comment for now.
print('Add the line "@set CUDA_VISIBLE_DEVICES=N" where N is the GPUs to use to config.bat')
else:
config_bat.append(f"@set CUDA_VISIBLE_DEVICES={os.getenv('CUDA_VISIBLE_DEVICES')}")
if len(gpu_devices) > 0 and not has_first_cuda_device:
print('GPU:0 seems to be missing! Validate that CUDA_VISIBLE_DEVICES is set properly.')
config_bat_path = os.path.join(CONFIG_DIR, 'config.bat') config_bat_path = os.path.join(CONFIG_DIR, 'config.bat')
if os.getenv('SD_UI_BIND_PORT') is not None:
config_bat.append(f"@set SD_UI_BIND_PORT={os.getenv('SD_UI_BIND_PORT')}")
if os.getenv('SD_UI_BIND_IP') is not None:
config_bat.append(f"@set SD_UI_BIND_IP={os.getenv('SD_UI_BIND_IP')}")
with open(config_bat_path, 'w', encoding='utf-8') as f: with open(config_bat_path, 'w', encoding='utf-8') as f:
f.write('\r\n'.join(config_bat)) f.write('\r\n'.join(config_bat))
except Exception as e: except Exception as e:
@ -122,17 +132,28 @@ def setConfig(config):
'#!/bin/bash', '#!/bin/bash',
f"export update_branch={config['update_branch']}" f"export update_branch={config['update_branch']}"
] ]
if len(gpu_devices) > 0 and not has_first_cuda_device: if os.getenv('CUDA_VISIBLE_DEVICES') is None:
config_sh.append('#Set the devices visible inside SD-UI here') if len(gpu_devices) > 0 and not has_first_cuda_device:
config_sh.append(f"#CUDA_VISIBLE_DEVICES={','.join(gpu_devices)}") # Needs better detection for edge cases, add as a comment for now. config_sh.append('#Set the devices visible inside SD-UI here')
print('Add the line "CUDA_VISIBLE_DEVICES=N" where N is the GPUs to use to config.sh') config_sh.append(f"#CUDA_VISIBLE_DEVICES={','.join(gpu_devices)}") # Needs better detection for edge cases, add as a comment for now.
print('Add the line "CUDA_VISIBLE_DEVICES=N" where N is the GPUs to use to config.sh')
else:
config_sh.append(f"export CUDA_VISIBLE_DEVICES=\"{os.getenv('CUDA_VISIBLE_DEVICES')}\"")
if len(gpu_devices) > 0 and not has_first_cuda_device:
print('GPU:0 seems to be missing! Validate that CUDA_VISIBLE_DEVICES is set properly.')
if os.getenv('SD_UI_BIND_PORT') is not None:
config_sh.append(f"export SD_UI_BIND_PORT={os.getenv('SD_UI_BIND_PORT')}")
if os.getenv('SD_UI_BIND_IP') is not None:
config_sh.append(f"export SD_UI_BIND_IP={os.getenv('SD_UI_BIND_IP')}")
config_sh_path = os.path.join(CONFIG_DIR, 'config.sh') config_sh_path = os.path.join(CONFIG_DIR, 'config.sh')
with open(config_sh_path, 'w', encoding='utf-8') as f: with open(config_sh_path, 'w', encoding='utf-8') as f:
f.write('\n'.join(config_sh)) f.write('\n'.join(config_sh))
except Exception as e: except Exception as e:
print(traceback.format_exc()) print(traceback.format_exc())
def resolve_model_to_use(model_name:str, model_type:str, model_dir:str, model_extension:str, default_models=[]): def resolve_model_to_use(model_name:str, model_type:str, model_dir:str, model_extensions:list, default_models=[]):
model_dirs = [os.path.join(MODELS_DIR, model_dir), SD_DIR] model_dirs = [os.path.join(MODELS_DIR, model_dir), SD_DIR]
if not model_name: # When None try user configured model. if not model_name: # When None try user configured model.
config = getConfig() config = getConfig()
@ -141,43 +162,38 @@ def resolve_model_to_use(model_name:str, model_type:str, model_dir:str, model_ex
if model_name: if model_name:
# Check models directory # Check models directory
models_dir_path = os.path.join(MODELS_DIR, model_dir, model_name) models_dir_path = os.path.join(MODELS_DIR, model_dir, model_name)
if os.path.exists(models_dir_path + model_extension): for model_extension in model_extensions:
return models_dir_path if os.path.exists(models_dir_path + model_extension):
if os.path.exists(model_name + model_extension): return models_dir_path
# Direct Path to file if os.path.exists(model_name + model_extension):
model_name = os.path.abspath(model_name) # Direct Path to file
return model_name model_name = os.path.abspath(model_name)
return model_name
# Default locations # Default locations
if model_name in default_models: if model_name in default_models:
default_model_path = os.path.join(SD_DIR, model_name) default_model_path = os.path.join(SD_DIR, model_name)
if os.path.exists(default_model_path + model_extension): for model_extension in model_extensions:
return default_model_path if os.path.exists(default_model_path + model_extension):
return default_model_path
# Can't find requested model, check the default paths. # Can't find requested model, check the default paths.
for default_model in default_models: for default_model in default_models:
for model_dir in model_dirs: for model_dir in model_dirs:
default_model_path = os.path.join(model_dir, default_model) default_model_path = os.path.join(model_dir, default_model)
if os.path.exists(default_model_path + model_extension): for model_extension in model_extensions:
if model_name is not None: if os.path.exists(default_model_path + model_extension):
print(f'Could not find the configured custom model {model_name}{model_extension}. Using the default one: {default_model_path}{model_extension}') if model_name is not None:
return default_model_path print(f'Could not find the configured custom model {model_name}{model_extension}. Using the default one: {default_model_path}{model_extension}')
return default_model_path
raise Exception('No valid models found.') raise Exception('No valid models found.')
def resolve_ckpt_to_use(model_name:str=None): def resolve_ckpt_to_use(model_name:str=None):
return resolve_model_to_use(model_name, model_type='stable-diffusion', model_dir='stable-diffusion', model_extension='.ckpt', default_models=APP_CONFIG_DEFAULT_MODELS) return resolve_model_to_use(model_name, model_type='stable-diffusion', model_dir='stable-diffusion', model_extensions=['.ckpt'], default_models=APP_CONFIG_DEFAULT_MODELS)
def resolve_vae_to_use(ckpt_model_path:str=None): def resolve_vae_to_use(model_name:str=None):
if ckpt_model_path is not None: try:
if os.path.exists(ckpt_model_path + '.vae.pt'): return resolve_model_to_use(model_name, model_type='vae', model_dir='vae', model_extensions=['.vae.pt', '.ckpt'], default_models=[])
return ckpt_model_path except:
return None
ckpt_model_name = os.path.basename(ckpt_model_path)
model_dirs = [os.path.join(MODELS_DIR, 'stable-diffusion'), SD_DIR]
for model_dir in model_dirs:
default_model_path = os.path.join(model_dir, ckpt_model_name)
if os.path.exists(default_model_path + '.vae.pt'):
return default_model_path
return resolve_model_to_use(model_name=None, model_type='vae', model_dir='stable-diffusion', model_extension='.vae.pt', default_models=APP_CONFIG_DEFAULT_VAE)
class SetAppConfigRequest(BaseModel): class SetAppConfigRequest(BaseModel):
update_branch: str = None update_branch: str = None
@ -203,10 +219,6 @@ async def setAppConfig(req : SetAppConfigRequest):
render_devices.append('GPU:' + req.render_devices) render_devices.append('GPU:' + req.render_devices)
if len(render_devices) > 0: if len(render_devices) > 0:
config['render_devices'] = render_devices config['render_devices'] = render_devices
if req.model_vae:
if 'model' not in config:
config['model'] = {}
config['model']['vae'] = req.model_vae
try: try:
setConfig(config) setConfig(config)
return JSONResponse({'status': 'OK'}, headers=NOCACHE_HEADERS) return JSONResponse({'status': 'OK'}, headers=NOCACHE_HEADERS)
@ -226,21 +238,25 @@ def getModels():
}, },
} }
def listModels(models_dirname, model_type, model_extensions):
models_dir = os.path.join(MODELS_DIR, models_dirname)
for file in os.listdir(models_dir):
for model_extension in model_extensions:
if file.endswith(model_extension):
model_name = file[:-len(model_extension)]
models['options'][model_type].append(model_name)
models['options'][model_type] = [*set(models['options'][model_type])] # remove duplicates
# custom models # custom models
sd_models_dir = os.path.join(MODELS_DIR, 'stable-diffusion') listModels(models_dirname='stable-diffusion', model_type='stable-diffusion', model_extensions=['.ckpt'])
for model_type, model_extension in [('stable-diffusion', '.ckpt'), ('vae', '.vae.pt')]: listModels(models_dirname='vae', model_type='vae', model_extensions=['.vae.pt', '.ckpt'])
for file in os.listdir(sd_models_dir):
if file.endswith(model_extension):
model_name = file[:-len(model_extension)]
models['options'][model_type].append(model_name)
# legacy # legacy
custom_weight_path = os.path.join(SD_DIR, 'custom-model.ckpt') custom_weight_path = os.path.join(SD_DIR, 'custom-model.ckpt')
if os.path.exists(custom_weight_path): if os.path.exists(custom_weight_path):
models['options']['stable-diffusion'].append('custom-model') models['options']['stable-diffusion'].append('custom-model')
models['active']['vae'] = os.path.basename(task_manager.default_vae_to_load)
return models return models
def getUIPlugins(): def getUIPlugins():
@ -261,6 +277,8 @@ def read_web_data(key:str=None):
if config is None: if config is None:
raise HTTPException(status_code=500, detail="Config file is missing or unreadable") raise HTTPException(status_code=500, detail="Config file is missing or unreadable")
return JSONResponse(config, headers=NOCACHE_HEADERS) return JSONResponse(config, headers=NOCACHE_HEADERS)
elif key == 'devices':
return JSONResponse(task_manager.get_devices(), headers=NOCACHE_HEADERS)
elif key == 'models': elif key == 'models':
return JSONResponse(getModels(), headers=NOCACHE_HEADERS) return JSONResponse(getModels(), headers=NOCACHE_HEADERS)
elif key == 'modifiers': return FileResponse(os.path.join(SD_UI_DIR, 'modifiers.json'), headers=NOCACHE_HEADERS) elif key == 'modifiers': return FileResponse(os.path.join(SD_UI_DIR, 'modifiers.json'), headers=NOCACHE_HEADERS)
@ -295,23 +313,32 @@ def ping(session_id:str=None):
response['session'] = 'pending' response['session'] = 'pending'
return JSONResponse(response, headers=NOCACHE_HEADERS) return JSONResponse(response, headers=NOCACHE_HEADERS)
def save_model_to_config(model_name): def save_model_to_config(ckpt_model_name, vae_model_name):
config = getConfig() config = getConfig()
if 'model' not in config: if 'model' not in config:
config['model'] = {} config['model'] = {}
config['model']['stable-diffusion'] = model_name config['model']['stable-diffusion'] = ckpt_model_name
config['model']['vae'] = vae_model_name
if vae_model_name is None or vae_model_name == "":
del config['model']['vae']
setConfig(config) setConfig(config)
@app.post('/render') @app.post('/render')
def render(req : task_manager.ImageRequest): def render(req : task_manager.ImageRequest):
if req.use_cpu and task_manager.is_alive('cpu') <= 0: raise HTTPException(status_code=403, detail=f'CPU rendering is not enabled in config.json or the thread has died...') # HTTP403 Forbidden if req.use_cpu: # TODO Remove after transition.
print('WARNING Replace {use_cpu: true} by {render_device: "cpu"}')
req.render_device = 'cpu'
del req.use_cpu
if req.render_device and task_manager.is_alive(req.render_device) <= 0: raise HTTPException(status_code=403, detail=f'{req.render_device} rendering is not enabled in config.json or the thread has died...') # HTTP403 Forbidden
if req.use_face_correction and task_manager.is_alive(0) <= 0: #TODO Remove when GFPGANer is fixed upstream. if req.use_face_correction and task_manager.is_alive(0) <= 0: #TODO Remove when GFPGANer is fixed upstream.
raise HTTPException(status_code=412, detail=f'GFPGANer only works GPU:0, use CUDA_VISIBLE_DEVICES if GFPGANer is needed on a specific GPU.') # HTTP412 Precondition Failed raise HTTPException(status_code=412, detail=f'GFPGANer only works GPU:0, use CUDA_VISIBLE_DEVICES if GFPGANer is needed on a specific GPU.') # HTTP412 Precondition Failed
try: try:
save_model_to_config(req.use_stable_diffusion_model) save_model_to_config(req.use_stable_diffusion_model, req.use_vae_model)
req.use_stable_diffusion_model = resolve_ckpt_to_use(req.use_stable_diffusion_model) req.use_stable_diffusion_model = resolve_ckpt_to_use(req.use_stable_diffusion_model)
req.use_vae_model = resolve_vae_to_use(ckpt_model_path=req.use_stable_diffusion_model) req.use_vae_model = resolve_vae_to_use(req.use_vae_model)
new_task = task_manager.render(req) new_task = task_manager.render(req)
response = { response = {
'status': str(task_manager.current_state), 'status': str(task_manager.current_state),
@ -390,44 +417,41 @@ config = getConfig()
# Start the task_manager # Start the task_manager
task_manager.default_model_to_load = resolve_ckpt_to_use() task_manager.default_model_to_load = resolve_ckpt_to_use()
task_manager.default_vae_to_load = resolve_vae_to_use(ckpt_model_path=task_manager.default_model_to_load) task_manager.default_vae_to_load = resolve_vae_to_use()
if 'render_devices' in config: # Start a new thread for each device. if 'render_devices' in config: # Start a new thread for each device.
if isinstance(config['render_devices'], str): if isinstance(config['render_devices'], str):
config['render_devices'] = config['render_devices'].split(',') config['render_devices'] = config['render_devices'].split(',')
if not isinstance(config['render_devices'], list): if not isinstance(config['render_devices'], list):
raise Exception('Invalid render_devices value in config.') raise Exception('Invalid render_devices value in config.')
for device in config['render_devices']: for device in config['render_devices']:
if task_manager.is_alive(device) >= 1:
print(device, 'already registered.')
continue
if not task_manager.start_render_thread(device): if not task_manager.start_render_thread(device):
print(device, 'failed to start.') print(device, 'failed to start.')
if task_manager.is_alive() <= 0: # No running devices, probably invalid user config. if task_manager.is_alive() <= 0: # No running devices, probably invalid user config.
print('WARNING: No active render devices after loading config. Validate "render_devices" in config.json') print('WARNING: No active render devices after loading config. Validate "render_devices" in config.json')
print('Loading default render devices to replace invalid render_devices field from config', config['render_devices']) print('Loading default render devices to replace invalid render_devices field from config', config['render_devices'])
display_warning = False
if task_manager.is_alive() <= 0: # Either no defauls or no devices after loading config. if task_manager.is_alive() <= 0: # Either no defauls or no devices after loading config.
# Select best GPU device using free memory, if more than one device. # Select best GPU device using free memory, if more than one device.
if task_manager.start_render_thread('auto'): # Detect best device for renders if task_manager.start_render_thread('auto'): # Detect best device for renders
if task_manager.is_alive(0) <= 0: # has no cuda:0 # if cuda:0 is missing, another cuda device is better. try to start it...
if task_manager.is_alive('cpu') >= 1: # auto used CPU. if task_manager.is_alive(0) <= 0 and task_manager.is_alive('cpu') <= 0 and not task_manager.start_render_thread('cuda'):
pass # Maybe add warning here about CPU mode... print('Failed to start GPU:0...')
elif task_manager.start_render_thread('cuda'): # An other cuda device is better and cuda:0 is missing, try to start it...
display_warning = True # And warn user to update settings...
else:
print('Failed to start GPU:0...')
else: else:
print('Failed to start gpu device.') print('Failed to start gpu device.')
if task_manager.is_alive('cpu') <= 0: if task_manager.is_alive('cpu') <= 0 and not task_manager.start_render_thread('cpu'): # Allow CPU to be used for renders
# Allow CPU to be used for renders print('Failed to start CPU render device...')
if not task_manager.start_render_thread('cpu'):
print('Failed to start CPU render device...')
if display_warning or task_manager.is_alive(0) <= 0: is_using_a_gpu = (task_manager.is_alive() > task_manager.is_alive('cpu'))
if is_using_a_gpu and task_manager.is_alive(0) <= 0:
print('WARNING: GFPGANer only works on GPU:0, use CUDA_VISIBLE_DEVICES if GFPGANer is needed on a specific GPU.') print('WARNING: GFPGANer only works on GPU:0, use CUDA_VISIBLE_DEVICES if GFPGANer is needed on a specific GPU.')
print('Using CUDA_VISIBLE_DEVICES will remap the selected devices starting at GPU:0 fixing GFPGANer') print('Using CUDA_VISIBLE_DEVICES will remap the selected devices starting at GPU:0 fixing GFPGANer')
print('Add the line "@set CUDA_VISIBLE_DEVICES=N" where N is the GPUs to use to config.bat') print('Add the line "@set CUDA_VISIBLE_DEVICES=N" where N is the GPUs to use to config.bat')
print('Add the line "CUDA_VISIBLE_DEVICES=N" where N is the GPUs to use to config.sh') print('Add the line "CUDA_VISIBLE_DEVICES=N" where N is the GPUs to use to config.sh')
del display_warning print('active devices', task_manager.get_devices())
# start the browser ui # start the browser ui
import webbrowser; webbrowser.open('http://localhost:9000') import webbrowser; webbrowser.open('http://localhost:9000')