2023-03-12 21:36:42 +00:00
|
|
|
import { api } from "./api.js";
|
|
|
|
|
2023-03-02 21:34:29 +00:00
|
|
|
export function getPngMetadata(file) {
|
|
|
|
return new Promise((r) => {
|
|
|
|
const reader = new FileReader();
|
|
|
|
reader.onload = (event) => {
|
|
|
|
// Get the PNG data as a Uint8Array
|
|
|
|
const pngData = new Uint8Array(event.target.result);
|
|
|
|
const dataView = new DataView(pngData.buffer);
|
|
|
|
|
|
|
|
// Check that the PNG signature is present
|
|
|
|
if (dataView.getUint32(0) !== 0x89504e47) {
|
|
|
|
console.error("Not a valid PNG file");
|
|
|
|
r();
|
|
|
|
return;
|
|
|
|
}
|
|
|
|
|
|
|
|
// Start searching for chunks after the PNG signature
|
|
|
|
let offset = 8;
|
|
|
|
let txt_chunks = {};
|
|
|
|
// Loop through the chunks in the PNG file
|
|
|
|
while (offset < pngData.length) {
|
|
|
|
// Get the length of the chunk
|
|
|
|
const length = dataView.getUint32(offset);
|
|
|
|
// Get the chunk type
|
|
|
|
const type = String.fromCharCode(...pngData.slice(offset + 4, offset + 8));
|
|
|
|
if (type === "tEXt") {
|
|
|
|
// Get the keyword
|
|
|
|
let keyword_end = offset + 8;
|
|
|
|
while (pngData[keyword_end] !== 0) {
|
|
|
|
keyword_end++;
|
|
|
|
}
|
|
|
|
const keyword = String.fromCharCode(...pngData.slice(offset + 8, keyword_end));
|
|
|
|
// Get the text
|
2023-04-08 15:00:03 +00:00
|
|
|
const contentArraySegment = pngData.slice(keyword_end + 1, offset + 8 + length);
|
|
|
|
const contentJson = Array.from(contentArraySegment).map(s=>String.fromCharCode(s)).join('')
|
|
|
|
txt_chunks[keyword] = contentJson;
|
2023-03-02 21:34:29 +00:00
|
|
|
}
|
|
|
|
|
|
|
|
offset += 12 + length;
|
|
|
|
}
|
|
|
|
|
|
|
|
r(txt_chunks);
|
|
|
|
};
|
|
|
|
|
|
|
|
reader.readAsArrayBuffer(file);
|
|
|
|
});
|
|
|
|
}
|
2023-03-12 21:36:42 +00:00
|
|
|
|
2023-10-24 01:13:50 +00:00
|
|
|
function parseExifData(exifData) {
|
|
|
|
// Check for the correct TIFF header (0x4949 for little-endian or 0x4D4D for big-endian)
|
|
|
|
const isLittleEndian = new Uint16Array(exifData.slice(0, 2))[0] === 0x4949;
|
|
|
|
console.log(exifData);
|
|
|
|
|
|
|
|
// Function to read 16-bit and 32-bit integers from binary data
|
|
|
|
function readInt(offset, isLittleEndian, length) {
|
|
|
|
let arr = exifData.slice(offset, offset + length)
|
|
|
|
if (length === 2) {
|
|
|
|
return new DataView(arr.buffer, arr.byteOffset, arr.byteLength).getUint16(0, isLittleEndian);
|
|
|
|
} else if (length === 4) {
|
|
|
|
return new DataView(arr.buffer, arr.byteOffset, arr.byteLength).getUint32(0, isLittleEndian);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
// Read the offset to the first IFD (Image File Directory)
|
|
|
|
const ifdOffset = readInt(4, isLittleEndian, 4);
|
|
|
|
|
|
|
|
function parseIFD(offset) {
|
|
|
|
const numEntries = readInt(offset, isLittleEndian, 2);
|
|
|
|
const result = {};
|
|
|
|
|
|
|
|
for (let i = 0; i < numEntries; i++) {
|
|
|
|
const entryOffset = offset + 2 + i * 12;
|
|
|
|
const tag = readInt(entryOffset, isLittleEndian, 2);
|
|
|
|
const type = readInt(entryOffset + 2, isLittleEndian, 2);
|
|
|
|
const numValues = readInt(entryOffset + 4, isLittleEndian, 4);
|
|
|
|
const valueOffset = readInt(entryOffset + 8, isLittleEndian, 4);
|
|
|
|
|
|
|
|
// Read the value(s) based on the data type
|
|
|
|
let value;
|
|
|
|
if (type === 2) {
|
|
|
|
// ASCII string
|
|
|
|
value = String.fromCharCode(...exifData.slice(valueOffset, valueOffset + numValues - 1));
|
|
|
|
}
|
|
|
|
|
|
|
|
result[tag] = value;
|
|
|
|
}
|
|
|
|
|
|
|
|
return result;
|
|
|
|
}
|
|
|
|
|
|
|
|
// Parse the first IFD
|
|
|
|
const ifdData = parseIFD(ifdOffset);
|
|
|
|
return ifdData;
|
|
|
|
}
|
|
|
|
|
|
|
|
function splitValues(input) {
|
|
|
|
var output = {};
|
|
|
|
for (var key in input) {
|
|
|
|
var value = input[key];
|
|
|
|
var splitValues = value.split(':', 2);
|
|
|
|
output[splitValues[0]] = splitValues[1];
|
|
|
|
}
|
|
|
|
return output;
|
|
|
|
}
|
|
|
|
|
|
|
|
export function getWebpMetadata(file) {
|
|
|
|
return new Promise((r) => {
|
|
|
|
const reader = new FileReader();
|
|
|
|
reader.onload = (event) => {
|
|
|
|
// Get the PNG data as a Uint8Array
|
|
|
|
const pngData = new Uint8Array(event.target.result);
|
|
|
|
const dataView = new DataView(pngData.buffer);
|
|
|
|
|
|
|
|
// Check that the PNG signature is present
|
|
|
|
if (dataView.getUint32(0) !== 0x52494646 || dataView.getUint32(8) !== 0x57454250) {
|
|
|
|
console.error("Not a valid WEBP file");
|
|
|
|
r();
|
|
|
|
return;
|
|
|
|
}
|
|
|
|
|
|
|
|
// Start searching for chunks after the PNG signature
|
|
|
|
let offset = 12;
|
|
|
|
let txt_chunks = {};
|
|
|
|
// Loop through the chunks in the PNG file
|
|
|
|
while (offset < pngData.length) {
|
|
|
|
// Get the length of the chunk
|
|
|
|
const length = dataView.getUint32(offset + 4, true);
|
|
|
|
// Get the chunk type
|
|
|
|
const type = String.fromCharCode(...pngData.slice(offset, offset + 4));
|
|
|
|
if (type === "EXIF") {
|
|
|
|
// Get the keyword
|
|
|
|
let data = parseExifData(pngData.slice(offset + 8, offset + 8 + length));
|
|
|
|
for (var key in data) {
|
|
|
|
var value = data[key];
|
|
|
|
let index = value.indexOf(':');
|
|
|
|
txt_chunks[value.slice(0, index)] = value.slice(index + 1);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
offset += 8 + length;
|
|
|
|
}
|
|
|
|
|
|
|
|
r(txt_chunks);
|
|
|
|
};
|
|
|
|
|
|
|
|
reader.readAsArrayBuffer(file);
|
|
|
|
});
|
|
|
|
}
|
|
|
|
|
2023-05-18 06:41:21 +00:00
|
|
|
export function getLatentMetadata(file) {
|
|
|
|
return new Promise((r) => {
|
|
|
|
const reader = new FileReader();
|
|
|
|
reader.onload = (event) => {
|
|
|
|
const safetensorsData = new Uint8Array(event.target.result);
|
|
|
|
const dataView = new DataView(safetensorsData.buffer);
|
|
|
|
let header_size = dataView.getUint32(0, true);
|
|
|
|
let offset = 8;
|
2023-06-26 16:21:07 +00:00
|
|
|
let header = JSON.parse(new TextDecoder().decode(safetensorsData.slice(offset, offset + header_size)));
|
2023-05-18 06:41:21 +00:00
|
|
|
r(header.__metadata__);
|
|
|
|
};
|
|
|
|
|
2023-06-26 16:21:07 +00:00
|
|
|
var slice = file.slice(0, 1024 * 1024 * 4);
|
|
|
|
reader.readAsArrayBuffer(slice);
|
2023-05-18 06:41:21 +00:00
|
|
|
});
|
|
|
|
}
|
|
|
|
|
2023-03-12 21:36:42 +00:00
|
|
|
export async function importA1111(graph, parameters) {
|
|
|
|
const p = parameters.lastIndexOf("\nSteps:");
|
|
|
|
if (p > -1) {
|
|
|
|
const embeddings = await api.getEmbeddings();
|
|
|
|
const opts = parameters
|
|
|
|
.substr(p)
|
2023-05-24 18:01:11 +00:00
|
|
|
.split("\n")[1]
|
2023-03-12 21:36:42 +00:00
|
|
|
.split(",")
|
|
|
|
.reduce((p, n) => {
|
|
|
|
const s = n.split(":");
|
|
|
|
p[s[0].trim().toLowerCase()] = s[1].trim();
|
|
|
|
return p;
|
|
|
|
}, {});
|
|
|
|
const p2 = parameters.lastIndexOf("\nNegative prompt:", p);
|
|
|
|
if (p2 > -1) {
|
|
|
|
let positive = parameters.substr(0, p2).trim();
|
|
|
|
let negative = parameters.substring(p2 + 18, p).trim();
|
|
|
|
|
|
|
|
const ckptNode = LiteGraph.createNode("CheckpointLoaderSimple");
|
|
|
|
const clipSkipNode = LiteGraph.createNode("CLIPSetLastLayer");
|
|
|
|
const positiveNode = LiteGraph.createNode("CLIPTextEncode");
|
|
|
|
const negativeNode = LiteGraph.createNode("CLIPTextEncode");
|
|
|
|
const samplerNode = LiteGraph.createNode("KSampler");
|
|
|
|
const imageNode = LiteGraph.createNode("EmptyLatentImage");
|
|
|
|
const vaeNode = LiteGraph.createNode("VAEDecode");
|
|
|
|
const vaeLoaderNode = LiteGraph.createNode("VAELoader");
|
|
|
|
const saveNode = LiteGraph.createNode("SaveImage");
|
|
|
|
let hrSamplerNode = null;
|
|
|
|
|
|
|
|
const ceil64 = (v) => Math.ceil(v / 64) * 64;
|
|
|
|
|
|
|
|
function getWidget(node, name) {
|
|
|
|
return node.widgets.find((w) => w.name === name);
|
|
|
|
}
|
|
|
|
|
|
|
|
function setWidgetValue(node, name, value, isOptionPrefix) {
|
|
|
|
const w = getWidget(node, name);
|
|
|
|
if (isOptionPrefix) {
|
|
|
|
const o = w.options.values.find((w) => w.startsWith(value));
|
|
|
|
if (o) {
|
|
|
|
w.value = o;
|
|
|
|
} else {
|
|
|
|
console.warn(`Unknown value '${value}' for widget '${name}'`, node);
|
|
|
|
w.value = value;
|
|
|
|
}
|
|
|
|
} else {
|
|
|
|
w.value = value;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
function createLoraNodes(clipNode, text, prevClip, prevModel) {
|
|
|
|
const loras = [];
|
|
|
|
text = text.replace(/<lora:([^:]+:[^>]+)>/g, function (m, c) {
|
|
|
|
const s = c.split(":");
|
|
|
|
const weight = parseFloat(s[1]);
|
|
|
|
if (isNaN(weight)) {
|
|
|
|
console.warn("Invalid LORA", m);
|
|
|
|
} else {
|
|
|
|
loras.push({ name: s[0], weight });
|
|
|
|
}
|
|
|
|
return "";
|
|
|
|
});
|
|
|
|
|
|
|
|
for (const l of loras) {
|
|
|
|
const loraNode = LiteGraph.createNode("LoraLoader");
|
|
|
|
graph.add(loraNode);
|
|
|
|
setWidgetValue(loraNode, "lora_name", l.name, true);
|
|
|
|
setWidgetValue(loraNode, "strength_model", l.weight);
|
|
|
|
setWidgetValue(loraNode, "strength_clip", l.weight);
|
|
|
|
prevModel.node.connect(prevModel.index, loraNode, 0);
|
|
|
|
prevClip.node.connect(prevClip.index, loraNode, 1);
|
|
|
|
prevModel = { node: loraNode, index: 0 };
|
|
|
|
prevClip = { node: loraNode, index: 1 };
|
|
|
|
}
|
|
|
|
|
|
|
|
prevClip.node.connect(1, clipNode, 0);
|
|
|
|
prevModel.node.connect(0, samplerNode, 0);
|
|
|
|
if (hrSamplerNode) {
|
|
|
|
prevModel.node.connect(0, hrSamplerNode, 0);
|
|
|
|
}
|
|
|
|
|
|
|
|
return { text, prevModel, prevClip };
|
|
|
|
}
|
|
|
|
|
|
|
|
function replaceEmbeddings(text) {
|
2023-04-15 09:29:32 +00:00
|
|
|
if(!embeddings.length) return text;
|
2023-03-12 21:36:42 +00:00
|
|
|
return text.replaceAll(
|
|
|
|
new RegExp(
|
|
|
|
"\\b(" + embeddings.map((e) => e.replace(/[.*+?^${}()|[\]\\]/g, "\\$&")).join("\\b|\\b") + ")\\b",
|
|
|
|
"ig"
|
|
|
|
),
|
|
|
|
"embedding:$1"
|
|
|
|
);
|
|
|
|
}
|
|
|
|
|
|
|
|
function popOpt(name) {
|
|
|
|
const v = opts[name];
|
|
|
|
delete opts[name];
|
|
|
|
return v;
|
|
|
|
}
|
|
|
|
|
|
|
|
graph.clear();
|
|
|
|
graph.add(ckptNode);
|
|
|
|
graph.add(clipSkipNode);
|
|
|
|
graph.add(positiveNode);
|
|
|
|
graph.add(negativeNode);
|
|
|
|
graph.add(samplerNode);
|
|
|
|
graph.add(imageNode);
|
|
|
|
graph.add(vaeNode);
|
|
|
|
graph.add(vaeLoaderNode);
|
|
|
|
graph.add(saveNode);
|
|
|
|
|
|
|
|
ckptNode.connect(1, clipSkipNode, 0);
|
|
|
|
clipSkipNode.connect(0, positiveNode, 0);
|
|
|
|
clipSkipNode.connect(0, negativeNode, 0);
|
|
|
|
ckptNode.connect(0, samplerNode, 0);
|
|
|
|
positiveNode.connect(0, samplerNode, 1);
|
|
|
|
negativeNode.connect(0, samplerNode, 2);
|
|
|
|
imageNode.connect(0, samplerNode, 3);
|
|
|
|
vaeNode.connect(0, saveNode, 0);
|
|
|
|
samplerNode.connect(0, vaeNode, 0);
|
|
|
|
vaeLoaderNode.connect(0, vaeNode, 1);
|
|
|
|
|
|
|
|
const handlers = {
|
|
|
|
model(v) {
|
|
|
|
setWidgetValue(ckptNode, "ckpt_name", v, true);
|
|
|
|
},
|
|
|
|
"cfg scale"(v) {
|
|
|
|
setWidgetValue(samplerNode, "cfg", +v);
|
|
|
|
},
|
|
|
|
"clip skip"(v) {
|
|
|
|
setWidgetValue(clipSkipNode, "stop_at_clip_layer", -v);
|
|
|
|
},
|
|
|
|
sampler(v) {
|
|
|
|
let name = v.toLowerCase().replace("++", "pp").replaceAll(" ", "_");
|
|
|
|
if (name.includes("karras")) {
|
|
|
|
name = name.replace("karras", "").replace(/_+$/, "");
|
|
|
|
setWidgetValue(samplerNode, "scheduler", "karras");
|
|
|
|
} else {
|
|
|
|
setWidgetValue(samplerNode, "scheduler", "normal");
|
|
|
|
}
|
|
|
|
const w = getWidget(samplerNode, "sampler_name");
|
|
|
|
const o = w.options.values.find((w) => w === name || w === "sample_" + name);
|
|
|
|
if (o) {
|
|
|
|
setWidgetValue(samplerNode, "sampler_name", o);
|
|
|
|
}
|
|
|
|
},
|
|
|
|
size(v) {
|
|
|
|
const wxh = v.split("x");
|
|
|
|
const w = ceil64(+wxh[0]);
|
|
|
|
const h = ceil64(+wxh[1]);
|
|
|
|
const hrUp = popOpt("hires upscale");
|
|
|
|
const hrSz = popOpt("hires resize");
|
|
|
|
let hrMethod = popOpt("hires upscaler");
|
|
|
|
|
|
|
|
setWidgetValue(imageNode, "width", w);
|
|
|
|
setWidgetValue(imageNode, "height", h);
|
|
|
|
|
|
|
|
if (hrUp || hrSz) {
|
|
|
|
let uw, uh;
|
|
|
|
if (hrUp) {
|
|
|
|
uw = w * hrUp;
|
|
|
|
uh = h * hrUp;
|
|
|
|
} else {
|
|
|
|
const s = hrSz.split("x");
|
|
|
|
uw = +s[0];
|
|
|
|
uh = +s[1];
|
|
|
|
}
|
|
|
|
|
|
|
|
let upscaleNode;
|
|
|
|
let latentNode;
|
|
|
|
|
|
|
|
if (hrMethod.startsWith("Latent")) {
|
|
|
|
latentNode = upscaleNode = LiteGraph.createNode("LatentUpscale");
|
|
|
|
graph.add(upscaleNode);
|
|
|
|
samplerNode.connect(0, upscaleNode, 0);
|
|
|
|
|
|
|
|
switch (hrMethod) {
|
|
|
|
case "Latent (nearest-exact)":
|
|
|
|
hrMethod = "nearest-exact";
|
|
|
|
break;
|
|
|
|
}
|
|
|
|
setWidgetValue(upscaleNode, "upscale_method", hrMethod, true);
|
|
|
|
} else {
|
|
|
|
const decode = LiteGraph.createNode("VAEDecodeTiled");
|
|
|
|
graph.add(decode);
|
|
|
|
samplerNode.connect(0, decode, 0);
|
|
|
|
vaeLoaderNode.connect(0, decode, 1);
|
|
|
|
|
|
|
|
const upscaleLoaderNode = LiteGraph.createNode("UpscaleModelLoader");
|
|
|
|
graph.add(upscaleLoaderNode);
|
|
|
|
setWidgetValue(upscaleLoaderNode, "model_name", hrMethod, true);
|
|
|
|
|
|
|
|
const modelUpscaleNode = LiteGraph.createNode("ImageUpscaleWithModel");
|
|
|
|
graph.add(modelUpscaleNode);
|
|
|
|
decode.connect(0, modelUpscaleNode, 1);
|
|
|
|
upscaleLoaderNode.connect(0, modelUpscaleNode, 0);
|
|
|
|
|
|
|
|
upscaleNode = LiteGraph.createNode("ImageScale");
|
|
|
|
graph.add(upscaleNode);
|
|
|
|
modelUpscaleNode.connect(0, upscaleNode, 0);
|
|
|
|
|
|
|
|
const vaeEncodeNode = (latentNode = LiteGraph.createNode("VAEEncodeTiled"));
|
|
|
|
graph.add(vaeEncodeNode);
|
|
|
|
upscaleNode.connect(0, vaeEncodeNode, 0);
|
|
|
|
vaeLoaderNode.connect(0, vaeEncodeNode, 1);
|
|
|
|
}
|
|
|
|
|
|
|
|
setWidgetValue(upscaleNode, "width", ceil64(uw));
|
|
|
|
setWidgetValue(upscaleNode, "height", ceil64(uh));
|
|
|
|
|
|
|
|
hrSamplerNode = LiteGraph.createNode("KSampler");
|
|
|
|
graph.add(hrSamplerNode);
|
|
|
|
ckptNode.connect(0, hrSamplerNode, 0);
|
|
|
|
positiveNode.connect(0, hrSamplerNode, 1);
|
|
|
|
negativeNode.connect(0, hrSamplerNode, 2);
|
|
|
|
latentNode.connect(0, hrSamplerNode, 3);
|
|
|
|
hrSamplerNode.connect(0, vaeNode, 0);
|
|
|
|
}
|
|
|
|
},
|
|
|
|
steps(v) {
|
|
|
|
setWidgetValue(samplerNode, "steps", +v);
|
|
|
|
},
|
|
|
|
seed(v) {
|
|
|
|
setWidgetValue(samplerNode, "seed", +v);
|
|
|
|
},
|
|
|
|
};
|
|
|
|
|
|
|
|
for (const opt in opts) {
|
|
|
|
if (opt in handlers) {
|
|
|
|
handlers[opt](popOpt(opt));
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
if (hrSamplerNode) {
|
|
|
|
setWidgetValue(hrSamplerNode, "steps", getWidget(samplerNode, "steps").value);
|
|
|
|
setWidgetValue(hrSamplerNode, "cfg", getWidget(samplerNode, "cfg").value);
|
|
|
|
setWidgetValue(hrSamplerNode, "scheduler", getWidget(samplerNode, "scheduler").value);
|
|
|
|
setWidgetValue(hrSamplerNode, "sampler_name", getWidget(samplerNode, "sampler_name").value);
|
|
|
|
setWidgetValue(hrSamplerNode, "denoise", +(popOpt("denoising strength") || "1"));
|
|
|
|
}
|
|
|
|
|
|
|
|
let n = createLoraNodes(positiveNode, positive, { node: clipSkipNode, index: 0 }, { node: ckptNode, index: 0 });
|
|
|
|
positive = n.text;
|
|
|
|
n = createLoraNodes(negativeNode, negative, n.prevClip, n.prevModel);
|
|
|
|
negative = n.text;
|
|
|
|
|
|
|
|
setWidgetValue(positiveNode, "text", replaceEmbeddings(positive));
|
|
|
|
setWidgetValue(negativeNode, "text", replaceEmbeddings(negative));
|
|
|
|
|
|
|
|
graph.arrange();
|
|
|
|
|
|
|
|
for (const opt of ["model hash", "ensd"]) {
|
|
|
|
delete opts[opt];
|
|
|
|
}
|
|
|
|
|
|
|
|
console.warn("Unhandled parameters:", opts);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|