mirror of
https://github.com/invoke-ai/InvokeAI
synced 2024-08-30 20:32:17 +00:00
Add bare bones web UI
This commit is contained in:
tesseractcat
parent
7ea168227c
commit
0efc3bf780
62
scripts/dream_web.py
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62
scripts/dream_web.py
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import json
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import os
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from http.server import BaseHTTPRequestHandler, HTTPServer
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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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class DreamServer(BaseHTTPRequestHandler):
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def do_GET(self):
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self.send_response(200)
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if self.path == "/":
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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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self.wfile.write(content.read())
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else:
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self.send_header("Content-type", "image/png")
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self.end_headers()
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with open("." + self.path, "rb") as content:
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self.wfile.write(content.read())
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def do_POST(self):
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self.send_response(200)
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self.send_header("Content-type", "application/json")
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self.end_headers()
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content_length = int(self.headers['Content-Length'])
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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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batch = int(post_data['batch'])
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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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cfgscale = float(post_data['cfgscale'])
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seed = None if int(post_data['seed']) == -1 else int(post_data['seed'])
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print(f"Request to generate with data: {post_data}")
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outputs = model.txt2img(prompt,
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batch_size = batch,
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cfg_scale = cfgscale,
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width = width,
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height = height,
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seed = seed,
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steps = steps);
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print(f"Prompt generated with output: {outputs}")
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outputs = [x + [prompt] for x in outputs] # Append prompt to each output
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result = {'outputs': outputs}
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self.wfile.write(bytes(json.dumps(result), "utf-8"))
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if __name__ == "__main__":
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dream_server = HTTPServer(("0.0.0.0", 9090), DreamServer)
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print("Started Stable Diffusion dream server!")
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try:
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dream_server.serve_forever()
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except KeyboardInterrupt:
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pass
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dream_server.server_close()
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148
scripts/static/index.html
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148
scripts/static/index.html
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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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height:30vh;
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border-radius:5px;
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margin:10px;
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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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</style>
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<script>
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function append_output(output) {
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let output_node = document.createElement("img");
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output_node.src = output[0];
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let alt_text = output[1].toString() + " | " + output[2];
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output_node.alt = alt_text;
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output_node.title = alt_text;
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document.querySelector("#results").prepend(output_node);
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}
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function append_outputs(outputs) {
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for (const output of outputs) {
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append_output(output);
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}
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}
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function save_fields(form) {
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for (const [k, v] of new FormData(form)) {
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localStorage.setItem(k, v);
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}
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}
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function load_fields(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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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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// Post as JSON
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fetch(form.action, {
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method: form.method,
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body: JSON.stringify(Object.fromEntries(new FormData(form))),
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}).then((result) => {
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result.json().then((data) => {
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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 = '';
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save_fields(form);
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if (data.outputs.length != 0) {
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document.querySelector("#no_results_message")?.remove();
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append_outputs(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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});
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// Disable form
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form.querySelector('fieldset').setAttribute('disabled','');
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document.querySelector("#prompt").value = 'Generating...';
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});
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document.querySelector("#generate_form").addEventListener('change', (e) => {
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save_fields(e.target.form);
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});
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load_fields(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>
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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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<span>•</span>
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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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</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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