mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
Small cleanups.
- Quenched tokenizer warnings during model initialization. - Changed "batch" to "iterations" for generating multiple images in order to conserve vram. - Updated README. - Moved static folder from under scripts to top level. Can store other static content there in future. - Added screenshot of web server in action (to static folder).
This commit is contained in:
Lincoln Stein
@ -1,11 +1,20 @@
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import json
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import base64
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import os
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from pytorch_lightning import logging
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from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
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print("Loading model...")
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from ldm.simplet2i import T2I
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model = T2I()
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model = T2I(sampler_name='k_lms')
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# to get rid of annoying warning messages from pytorch
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import transformers
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transformers.logging.set_verbosity_error()
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logging.getLogger("pytorch_lightning").setLevel(logging.ERROR)
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print("Initializing model, be patient...")
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model.load_model()
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class DreamServer(BaseHTTPRequestHandler):
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def do_GET(self):
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@ -13,7 +22,7 @@ class DreamServer(BaseHTTPRequestHandler):
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self.send_response(200)
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self.send_header("Content-type", "text/html")
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self.end_headers()
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with open("./scripts/static/index.html", "rb") as content:
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with open("./static/index.html", "rb") as content:
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self.wfile.write(content.read())
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elif os.path.exists("." + self.path):
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self.send_response(200)
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@ -33,7 +42,7 @@ class DreamServer(BaseHTTPRequestHandler):
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post_data = json.loads(self.rfile.read(content_length))
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prompt = post_data['prompt']
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initimg = post_data['initimg']
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batch = int(post_data['batch'])
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iterations = int(post_data['iterations'])
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steps = int(post_data['steps'])
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width = int(post_data['width'])
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height = int(post_data['height'])
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@ -46,7 +55,7 @@ class DreamServer(BaseHTTPRequestHandler):
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if initimg is None:
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# Run txt2img
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outputs = model.txt2img(prompt,
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batch_size = batch,
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iterations=iterations,
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cfg_scale = cfgscale,
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width = width,
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height = height,
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@ -61,7 +70,7 @@ class DreamServer(BaseHTTPRequestHandler):
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# Run img2img
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outputs = model.img2img(prompt,
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init_img = "./img2img-tmp.png",
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batch_size = batch,
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iterations = iterations,
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cfg_scale = cfgscale,
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seed = seed,
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steps = steps)
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@ -77,7 +86,7 @@ class DreamServer(BaseHTTPRequestHandler):
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if __name__ == "__main__":
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dream_server = ThreadingHTTPServer(("0.0.0.0", 9090), DreamServer)
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print("Started Stable Diffusion dream server!")
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print("\n\n* Started Stable Diffusion dream server! Point your browser at http://localhost:9090 or use the host's DNS name or IP address. *")
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try:
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dream_server.serve_forever()
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@ -1,194 +0,0 @@
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<html>
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<head>
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<title>Stable Diffusion WebUI</title>
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<link rel="icon" href="data:,">
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<style>
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* {
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font-family: 'Arial';
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}
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#header {
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text-decoration: dotted underline;
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}
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#search {
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margin-top: 20vh;
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text-align: center;
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}
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fieldset {
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border: none;
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}
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#prompt {
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width: 500px;
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border-radius: 20px 0px 0px 20px;
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padding: 5px 10px 5px 10px;
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border: 1px solid black;
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outline: none;
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}
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#submit {
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border-radius: 0px 20px 20px 0px;
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padding: 5px 10px 5px 10px;
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border: 1px solid black;
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}
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#results {
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text-align: center;
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padding-left: 20vw;
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padding-right: 20vw;
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padding-top: 10px;
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}
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img {
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cursor: pointer;
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height: 30vh;
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border-radius: 5px;
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margin: 10px;
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}
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#generate-config {
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line-height:2em;
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}
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input[type="number"] {
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width: 60px;
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}
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#seed {
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width: 150px;
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}
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</style>
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<script>
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function toBase64(file) {
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return new Promise((resolve, reject) => {
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const r = new FileReader();
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r.readAsDataURL(file);
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r.onload = () => resolve(r.result);
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r.onerror = (error) => reject(error);
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});
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}
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function appendOutput(output) {
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let outputNode = document.createElement("img");
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outputNode.src = output[0];
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let outputConfig = output[2];
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let altText = output[1].toString() + " | " + outputConfig.prompt;
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outputNode.alt = altText;
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outputNode.title = altText;
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// Reload image config
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outputNode.addEventListener('click', () => {
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let form = document.querySelector("#generate-form");
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for (const [k, v] of new FormData(form)) {
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form.querySelector(`*[name=${k}]`).value = outputConfig[k];
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}
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document.querySelector("#seed").value = output[1];
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saveFields(document.querySelector("#generate-form"));
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});
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document.querySelector("#results").prepend(outputNode);
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}
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function appendOutputs(outputs) {
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for (const output of outputs) {
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appendOutput(output);
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}
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}
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function saveFields(form) {
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for (const [k, v] of new FormData(form)) {
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if (typeof v !== 'object') { // Don't save 'file' type
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localStorage.setItem(k, v);
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}
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}
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}
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function loadFields(form) {
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for (const [k, v] of new FormData(form)) {
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const item = localStorage.getItem(k);
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if (item != null) {
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form.querySelector(`*[name=${k}]`).value = item;
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}
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}
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}
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async function generateSubmit(form) {
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const prompt = document.querySelector("#prompt").value;
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// Convert file data to base64
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let formData = Object.fromEntries(new FormData(form));
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formData.initimg = formData.initimg.name !== '' ? await toBase64(formData.initimg) : null;
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// Post as JSON
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fetch(form.action, {
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method: form.method,
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body: JSON.stringify(formData),
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}).then(async (result) => {
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let data = await result.json();
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// Re-enable form, remove no-results-message
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form.querySelector('fieldset').removeAttribute('disabled');
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document.querySelector("#prompt").value = prompt;
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if (data.outputs.length != 0) {
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document.querySelector("#no-results-message")?.remove();
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appendOutputs(data.outputs);
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} else {
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alert("Error occurred while generating.");
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}
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});
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// Disable form while generating
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form.querySelector('fieldset').setAttribute('disabled','');
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document.querySelector("#prompt").value = `Generating: "${prompt}"`;
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}
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window.onload = () => {
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document.querySelector("#generate-form").addEventListener('submit', (e) => {
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e.preventDefault();
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const form = e.target;
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generateSubmit(form);
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});
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document.querySelector("#generate-form").addEventListener('change', (e) => {
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saveFields(e.target.form);
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});
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document.querySelector("#reset").addEventListener('click', (e) => {
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document.querySelector("#seed").value = -1;
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saveFields(e.target.form);
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});
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loadFields(document.querySelector("#generate-form"));
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};
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</script>
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</head>
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<body>
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<div id="search">
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<h2 id="header">Stable Diffusion</h2>
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<form id="generate-form" method="post" action="#">
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<fieldset>
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<input type="text" id="prompt" name="prompt">
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<input type="submit" id="submit" value="Generate">
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</fieldset>
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<fieldset id="generate-config">
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<label for="batch">Batch Size:</label>
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<input value="1" type="number" id="batch" name="batch">
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<label for="steps">Steps:</label>
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<input value="50" type="number" id="steps" name="steps">
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<label for="cfgscale">Cfg Scale:</label>
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<input value="7.5" type="number" id="cfgscale" name="cfgscale" step="any">
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<span>•</span>
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<label title="Set to multiple of 64" for="width">Width:</label>
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<input value="512" type="number" id="width" name="width">
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<label title="Set to multiple of 64" for="height">Height:</label>
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<input value="512" type="number" id="height" name="height">
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<br>
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<label title="Upload an image to use img2img" for="initimg">Img2Img Init:</label>
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<input type="file" id="initimg" name="initimg" accept=".jpg, .jpeg, .png">
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<label title="Set to -1 for random seed" for="seed">Seed:</label>
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<input value="-1" type="number" id="seed" name="seed">
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<button type="button" id="reset">↺</button>
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</fieldset>
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</form>
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</div>
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<hr style="width: 200px">
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<div id="results">
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<div id="no-results-message">
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<i><p>No results...</p></i>
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</div>
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</div>
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</body>
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</html>
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