2681 lines
99 KiB
Python
2681 lines
99 KiB
Python
import base64
|
|
import hashlib
|
|
import html
|
|
import json
|
|
import threading
|
|
import time
|
|
from pathlib import Path
|
|
from io import BytesIO
|
|
|
|
import imageio.v3 as iio
|
|
import requests
|
|
import torch
|
|
import torch.nn.functional as NNF
|
|
import transformers
|
|
import numpy as np
|
|
import mss
|
|
from PIL import Image, ImageDraw
|
|
from aiohttp import web
|
|
from aiohttp.web_exceptions import HTTPForbidden, HTTPError
|
|
|
|
import server
|
|
import folder_paths
|
|
import comfy
|
|
from nodes import CheckpointLoaderSimple, VAELoader
|
|
|
|
import sys
|
|
sys.path.append("ComfyUI/custom_nodes")
|
|
|
|
try:
|
|
from llama_cpp import Llama # llama-cpp-python
|
|
except:
|
|
Llama = None
|
|
|
|
try:
|
|
wd14tagger = __import__("comfyui-wd14-tagger").wd14tagger
|
|
except:
|
|
wd14tagger = None
|
|
|
|
try:
|
|
rembg = __import__("comfyui-inspyrenet-rembg")
|
|
except:
|
|
rembg = None
|
|
|
|
try:
|
|
florence2 = __import__("comfyui-florence2")
|
|
except:
|
|
florence2 = None
|
|
|
|
try:
|
|
film = __import__("comfyui-frame-interpolation.vfi_models.film").vfi_models.film
|
|
except:
|
|
film = None
|
|
|
|
try:
|
|
from comfyui_tensorrt import TensorRTLoader
|
|
except:
|
|
TensorRTLoader = None
|
|
|
|
def btoa_utf8(value):
|
|
return base64.b64encode(value.encode("utf-8")).decode()
|
|
|
|
def atob_utf8(value):
|
|
return base64.b64decode(value.encode()).decode("utf-8")
|
|
|
|
STREAM_COMPRESSION = 0
|
|
UPDATE_DELAY = 1.0
|
|
allowed_ips = ["127.0.0.1"]
|
|
setparam = {}
|
|
setstate = {}
|
|
param = {"lora": "", "_capture_offsetX": 0, "_capture_offsetY": 0, "_capture_scale": 100}
|
|
state = {"message": btoa_utf8(""), "update_and_reload": False, "presetTitle": time.strftime("%Y%m%d-%H%M"), "presetFolder": "", "presetFile": "", "loraRate": "1", "loraRank": "0", "loraMode": "", "loraFolder": "", "loraFile": "", "loraTagOptions": "[]", "loraTag": "", "loraLinkHref": "", "loraPreviewSrc": "", "darker": 0.0, "wd14th": 0.35, "wd14cth": 0.85}
|
|
frame_updating = False
|
|
frame_buffer = None
|
|
frame_mtime = 0
|
|
exclude_tags = ""
|
|
|
|
class AnyType(str):
|
|
def __ne__(self, __value: object) -> bool:
|
|
return False
|
|
|
|
any = AnyType("*")
|
|
|
|
|
|
HEAD=r"""
|
|
<head>
|
|
<style type="text/css">
|
|
|
|
html {
|
|
background-color: black;
|
|
}
|
|
|
|
body {
|
|
color: lightgray;
|
|
background: url('/flipstreamviewer/stream') rgba(0, 0, 0, 0) no-repeat top center local;
|
|
background-blend-mode: overlay;
|
|
margin: 4px;
|
|
padding: 0px;
|
|
}
|
|
|
|
textarea {
|
|
color: lightgray;
|
|
background-color: black;
|
|
width: 100%;
|
|
font-size: 100%;
|
|
}
|
|
|
|
input {
|
|
color: lightgray;
|
|
background-color: black;
|
|
font-size: 100%;
|
|
}
|
|
|
|
button {
|
|
color: black;
|
|
background-color: dimgray;
|
|
font-size: 100%;
|
|
border-radius: 4px;
|
|
padding: 0px;
|
|
min-width: 2em;
|
|
}
|
|
|
|
button.tags {
|
|
padding: 2px;
|
|
min-width: 2em;
|
|
}
|
|
|
|
hr {
|
|
background-color: dimgray;
|
|
border: none;
|
|
height: 3px;
|
|
padding: 0px;
|
|
margin: 1px;
|
|
}
|
|
|
|
button.disabled {
|
|
opacity: 0.5;
|
|
}
|
|
|
|
select {
|
|
color: lightgray;
|
|
background-color: black;
|
|
font-size: 100%;
|
|
}
|
|
|
|
div.row {
|
|
display: flex;
|
|
position: relative;
|
|
}
|
|
|
|
.FlipStreamSlider {
|
|
width: 50%;
|
|
}
|
|
|
|
.FlipStreamInputBox {
|
|
width: 100%;
|
|
}
|
|
|
|
.FlipStreamSelectBox,
|
|
.FlipStreamFolderSelect,
|
|
.FlipStreamFileSelect,
|
|
.FlipStreamMoveFileSelect {
|
|
width: 100%;
|
|
}
|
|
|
|
.FlipStreamMoveFileSelect {
|
|
display: none;
|
|
}
|
|
|
|
.FlipStreamPreviewBox {
|
|
max-width: 100%;
|
|
}
|
|
|
|
.FlipStreamPreviewRoi {
|
|
position: absolute;
|
|
top: 0;
|
|
left: 0;
|
|
}
|
|
|
|
#statusInfo {
|
|
line-break: anywhere;
|
|
}
|
|
|
|
#leftPanel,
|
|
#rightPanel,
|
|
#captureLeftPanel,
|
|
#captureRightPanel,
|
|
#tagLeftPanel,
|
|
#tagRightPanel,
|
|
#presetLeftPanel,
|
|
#presetRightPanel {
|
|
width: 12%;
|
|
background: rgba(0, 0, 0, 0.8);
|
|
}
|
|
|
|
#centerPanel,
|
|
#captureCenterPanel,
|
|
#tagCenterPanel,
|
|
#presetCenterPanel {
|
|
width: 76%;
|
|
text-align: center;
|
|
}
|
|
|
|
#captureCenterPanel,
|
|
#tagCenterPanel {
|
|
background: rgba(0, 0, 0, 0.8);
|
|
}
|
|
|
|
#mainDialog, #captureDialog, #tagDialog, #presetDialog {
|
|
position: fixed;
|
|
top: 0;
|
|
left: 0;
|
|
width: 100%;
|
|
height: 100%;
|
|
}
|
|
|
|
#mainDialog {
|
|
display: flex;
|
|
}
|
|
|
|
#captureDialog, #tagDialog, #presetDialog {
|
|
display: none;
|
|
z-index: 999;
|
|
}
|
|
|
|
#presetFolderSelect,
|
|
#movePresetSelect,
|
|
#loraFolderSelect,
|
|
#moveLoraSelect {
|
|
width: 100%;
|
|
}
|
|
|
|
#movePresetSelect,
|
|
#moveLoraSelect {
|
|
display: none;
|
|
}
|
|
|
|
#presetFileSelect,
|
|
#presetTitleInput,
|
|
#loraFileSelect,
|
|
#loraTagSelect {
|
|
width: 80%;
|
|
}
|
|
|
|
#darkerRange,
|
|
#wd14thRange,
|
|
#wd14cthRange {
|
|
width: 50%;
|
|
}
|
|
|
|
#toggleViewButton {
|
|
width: 100%;
|
|
height: 85%;
|
|
border: none;
|
|
background: transparent;
|
|
}
|
|
|
|
#messageBox {
|
|
width: 100%;
|
|
height: 15%;
|
|
border: none;
|
|
background: transparent;
|
|
font-size: 1.5rem;
|
|
text-shadow:
|
|
black 2px 0px, black -2px 0px,
|
|
black 0px -2px, black 0px 2px,
|
|
black 2px 2px , black -2px 2px,
|
|
black 2px -2px, black -2px -2px,
|
|
black 1px 2px, black -1px 2px,
|
|
black 1px -2px, black -1px -2px,
|
|
black 2px 1px, black -2px 1px,
|
|
black 2px -1px, black -2px -1px;
|
|
}
|
|
|
|
#loraLink img {
|
|
max-width: 100%;
|
|
max-height: 8em;
|
|
width: auto;
|
|
height: auto;
|
|
margin: auto;
|
|
display: block;
|
|
}
|
|
|
|
#offsetXRange,
|
|
#offsetYRange,
|
|
#scaleRange {
|
|
width: 80%;
|
|
}
|
|
|
|
</style>
|
|
<title>FlipStreamViewer</title>
|
|
</head>
|
|
"""
|
|
|
|
SCRIPT_PARAM=r"""
|
|
function btoa_utf8(str) {
|
|
return btoa(unescape(encodeURIComponent(str)));
|
|
}
|
|
|
|
function atob_utf8(str) {
|
|
return decodeURIComponent(escape(atob(str)));
|
|
}
|
|
|
|
function getStateAsJson(force_state={}) {
|
|
const presetTitle = document.getElementById("presetTitleInput").value;
|
|
const presetFolder = document.getElementById("presetFolderSelect").value;
|
|
const presetFile = document.getElementById("presetFileSelect").value;
|
|
const loraFolder = document.getElementById("loraFolderSelect").value;
|
|
const loraFile = document.getElementById("loraFileSelect").value;
|
|
const loraTagSelect = document.getElementById("loraTagSelect");
|
|
const loraTagOptions = JSON.stringify([...loraTagSelect.options].map(o => ({ value: o.value, text: o.text })));
|
|
const loraTag = document.getElementById("loraTagSelect").value;
|
|
const loraRate = document.getElementById("loraRate").value;
|
|
const loraRank = document.getElementById("loraRank").value;
|
|
const loraLinkHref = document.getElementById("loraLink").getAttribute("href");
|
|
const loraPreviewSrc = document.getElementById("loraPreview").getAttribute("src");
|
|
const darker = parseFloat(document.getElementById("darkerRange").value);
|
|
const wd14th = parseFloat(document.getElementById("wd14thRange").value);
|
|
const wd14cth = parseFloat(document.getElementById("wd14cthRange").value);
|
|
var res = { presetTitle: presetTitle, presetFolder: presetFolder, presetFile: presetFile, loraRate: loraRate, loraRank: loraRank, loraFolder: loraFolder, loraFile: loraFile, loraTagOptions: loraTagOptions, loraTag: loraTag, loraLinkHref: loraLinkHref, loraPreviewSrc: loraPreviewSrc, loraTagOptions: loraTagOptions, darker: darker, wd14th: wd14th, wd14cth: wd14cth };
|
|
document.querySelectorAll('.FlipStreamFolderSelect').forEach(x => res[x.name] = x.value);
|
|
res = Object.assign(res, force_state);
|
|
return res;
|
|
}
|
|
|
|
function getParamAsJson(force_param={}) {
|
|
const lora = btoa_utf8(document.getElementById("loraInput").value.trim());
|
|
const _capture_offsetX = parseInt(document.getElementById("offsetXRange").value);
|
|
const _capture_offsetY = parseInt(document.getElementById("offsetYRange").value);
|
|
const _capture_scale = parseInt(document.getElementById("scaleRange").value);
|
|
|
|
var res = { lora: lora, _capture_offsetX: _capture_offsetX, _capture_offsetY: _capture_offsetY, _capture_scale: _capture_scale }
|
|
document.querySelectorAll('.FlipStreamSlider').forEach(x => res[x.name] = x.value);
|
|
document.querySelectorAll('.FlipStreamTextBox').forEach(x => res[x.name] = btoa_utf8(x.value));
|
|
document.querySelectorAll('.FlipStreamInputBox').forEach(x => res[x.name] = x.value);
|
|
document.querySelectorAll('.FlipStreamSelectBox').forEach(x => res[x.name] = x.value);
|
|
document.querySelectorAll('.FlipStreamFileSelect').forEach(x => res[x.name] = x.value);
|
|
res = Object.assign(res, force_param);
|
|
return res;
|
|
}
|
|
|
|
function setParam(param) {
|
|
document.getElementById("loraInput").value = param.lora || "";
|
|
document.getElementById("offsetXRange").value = param.offsetX || 0;
|
|
document.getElementById("offsetYRange").value = param.offsetY || 0;
|
|
document.getElementById("scaleRange").value = param.scale || 100;
|
|
for (let key in param) {
|
|
const elem = document.querySelector(`input[name=${key}]`);
|
|
elem.value = param[key] || elem.value;
|
|
}
|
|
}
|
|
|
|
function updateParam(reload=false, force_state={}, force_param={}, search="") {
|
|
var updateButton = document.getElementById("updateButton");
|
|
updateButton.disabled = true;
|
|
fetch("/flipstreamviewer/update_param", {
|
|
method: "POST",
|
|
body: JSON.stringify([getStateAsJson(force_state), getParamAsJson(force_param)]),
|
|
headers: {"Content-Type": "application/json"}
|
|
}).then(response => {
|
|
if (response.ok) {
|
|
if (reload) {
|
|
reloadPage(search);
|
|
}
|
|
} else {
|
|
alert("Failed to update parameter.");
|
|
}
|
|
}).catch(error => {
|
|
alert("An error occurred while updating parameter.");
|
|
});
|
|
updateButton.disabled = false;
|
|
}
|
|
|
|
function setupPreviewRoi() {
|
|
document.querySelectorAll('.FlipStreamPreviewRoi').forEach(canvas => {
|
|
const ctx = canvas.getContext('2d');
|
|
const img = canvas.parentElement.querySelector('img');
|
|
const label = canvas.id.replace("PreviewRoi", "");
|
|
img.onload = () => {
|
|
canvas.width = img.width;
|
|
canvas.height = img.height;
|
|
};
|
|
|
|
let drawing = false, x, y;
|
|
canvas.onmousedown = e => { drawing = true; [x, y] = [e.offsetX, e.offsetY]; };
|
|
canvas.onmousemove = e => { if (drawing) { canvas.width = canvas.width; ctx.strokeStyle = 'red'; ctx.strokeRect(x, y, e.offsetX - x, e.offsetY - y); } };
|
|
canvas.onmouseup = e => {
|
|
if (!drawing) return;
|
|
drawing = false;
|
|
var sx = x / canvas.width;
|
|
var sy = y / canvas.height;
|
|
var ex = e.offsetX / canvas.width;
|
|
var ey = e.offsetY / canvas.height;
|
|
if (ex <= sx || ey <= sy) {
|
|
sx = 0;
|
|
sy = 0;
|
|
ex = 1;
|
|
ey = 1;
|
|
}
|
|
fetch('/flipstreamviewer/preview_setroi', {
|
|
method: 'POST',
|
|
headers: { 'Content-Type': 'application/json' },
|
|
body: JSON.stringify({
|
|
label: label,
|
|
sx: sx,
|
|
sy: sy,
|
|
ex: ex,
|
|
ey: ey
|
|
})
|
|
});
|
|
};
|
|
});
|
|
}
|
|
setupPreviewRoi();
|
|
"""
|
|
|
|
SCRIPT_PRESET=r"""
|
|
function loadPreset(loraPromptOnly=false, force_state={}, search="") {
|
|
fetch("/flipstreamviewer/load_preset", {
|
|
method: "POST",
|
|
body: JSON.stringify([getStateAsJson(force_state), loraPromptOnly]),
|
|
headers: {"Content-Type": "application/json"}
|
|
}).then(response => response.json()).then(json => {
|
|
if (loraPromptOnly) {
|
|
document.getElementById("loraInput").value = atob_utf8(json.lora);
|
|
document.getElementById("presetTitleInput").value = json.presetTitle;
|
|
}
|
|
else {
|
|
reloadPage(search);
|
|
}
|
|
}).catch(error => {
|
|
alert("An error occurred while loading preset: " + error);
|
|
});
|
|
}
|
|
|
|
function movePreset() {
|
|
document.getElementById("movePresetSelect").style.display = "block";
|
|
document.getElementById("movePresetSelect").value = "";
|
|
}
|
|
|
|
function movePresetFile() {
|
|
const moveFile = document.getElementById("presetFileSelect").value;
|
|
const moveTo = document.getElementById("movePresetSelect").value;
|
|
if (!moveFile || !moveTo) {
|
|
return;
|
|
}
|
|
fetch("/flipstreamviewer/move_presetfile", {
|
|
method: "POST",
|
|
body: JSON.stringify([getStateAsJson(), moveTo]),
|
|
headers: {"Content-Type": "application/json"}
|
|
}).then(response => {
|
|
if (response.ok) {
|
|
alert("Preset moved successfully!");
|
|
} else {
|
|
alert("Failed to move preset.");
|
|
}
|
|
}).catch(error => {
|
|
alert("An error occurred while moving preset.");
|
|
});
|
|
}
|
|
|
|
function savePreset() {
|
|
const title = document.getElementById("presetTitleInput").value;
|
|
if (title == "") {
|
|
alert("Please enter a title to save.");
|
|
return;
|
|
}
|
|
if (!/^[a-zA-Z0-9-_]+$/.test(title)) {
|
|
alert("Title can only contain [a-zA-Z0-9-_] characters.");
|
|
return;
|
|
}
|
|
fetch("/flipstreamviewer/save_preset", {
|
|
method: "POST",
|
|
body: JSON.stringify([getStateAsJson(), getParamAsJson()]),
|
|
headers: {"Content-Type": "application/json"}
|
|
}).then(response => {
|
|
if (response.ok) {
|
|
alert("Preset saved successfully!");
|
|
} else {
|
|
alert("Failed to save preset.");
|
|
}
|
|
}).catch(error => {
|
|
alert("An error occurred while saving preset.");
|
|
});
|
|
}
|
|
|
|
function showPresetDialog() {
|
|
document.getElementById("mainDialog").style.display = "none";
|
|
document.getElementById("presetDialog").style.display = "flex";
|
|
}
|
|
|
|
function closePresetDialog() {
|
|
document.getElementById("mainDialog").style.display = "flex";
|
|
document.getElementById("presetDialog").style.display = "none";
|
|
}
|
|
"""
|
|
|
|
SCRIPT_CKPT=r"""
|
|
function showMoveFileSelect(obj) {
|
|
obj.style.display="block";
|
|
obj.value="";
|
|
}
|
|
|
|
function moveFile(folder_path, mode, label) {
|
|
const moveFrom = document.getElementById(label + "FileSelect").value;
|
|
const moveTo = document.getElementById(label + "MoveFileSelect").value;
|
|
if (!moveFrom || !moveTo) {
|
|
return;
|
|
}
|
|
fetch("/flipstreamviewer/move_file", {
|
|
method: "POST",
|
|
body: JSON.stringify([getStateAsJson(), folder_path, mode, label, moveFrom, moveTo]),
|
|
headers: {"Content-Type": "application/json"}
|
|
}).then(response => {
|
|
if (response.ok) {
|
|
alert("Moved successfully!");
|
|
} else {
|
|
alert("Failed to move.");
|
|
}
|
|
reloadPage();
|
|
}).catch(error => {
|
|
alert("An error occurred while moving.");
|
|
});
|
|
}
|
|
"""
|
|
|
|
SCRIPT_LORA=r"""
|
|
function selectLoraFile() {
|
|
const loraFolder = document.getElementById("loraFolderSelect").value;
|
|
const loraFileSelect = document.getElementById("loraFileSelect");
|
|
const loraName = loraFileSelect.options[loraFileSelect.selectedIndex].text;
|
|
const loraFile = loraFileSelect.value;
|
|
const loraRate = document.getElementById("loraRate").value;
|
|
const loraTagSelect = document.getElementById("loraTagSelect");
|
|
const loraInput = document.getElementById("loraInput");
|
|
const loraLink = document.getElementById("loraLink");
|
|
const loraPreview = document.getElementById("loraPreview");
|
|
|
|
if (loraFile) {
|
|
const re = new RegExp("[\\n]?<lora:" + loraName + ":[-]?[0-9.]+>", "g");
|
|
if (loraInput.value.search(re) == -1) {
|
|
if (loraInput.value.trim() != "") {
|
|
loraInput.value += "\n";
|
|
}
|
|
loraInput.value += "<lora:" + loraName + ":" + loraRate + ">";
|
|
}
|
|
}
|
|
|
|
fetch("/flipstreamviewer/get_lorainfo", {
|
|
method: "POST",
|
|
body: JSON.stringify({loraFolder: loraFolder, loraFile: loraFile}),
|
|
headers: {"Content-Type": "application/json"}
|
|
}).then(response => response.json()).then(json => {
|
|
loraTagSelect.innerHTML = "";
|
|
|
|
item = document.createElement("option");
|
|
item.value = "";
|
|
item.text = "tags";
|
|
loraTagSelect.appendChild(item);
|
|
|
|
if (json.ss_tag_frequency) {
|
|
const datasets = JSON.parse(json.ss_tag_frequency);
|
|
const tags = {};
|
|
for (const setName in datasets) {
|
|
const set = datasets[setName];
|
|
for (const t in set) {
|
|
if (t in tags) {
|
|
tags[t] += set[t];
|
|
} else {
|
|
tags[t] = set[t];
|
|
}
|
|
}
|
|
}
|
|
const sorted_tags = Object.entries(tags).sort((a, b) => b[1] - a[1]);
|
|
for (const i in sorted_tags) {
|
|
item = document.createElement("option");
|
|
item.value = sorted_tags[i][0].trim();
|
|
item.text = sorted_tags[i][0].trim() + ":" + sorted_tags[i][1];
|
|
loraTagSelect.appendChild(item);
|
|
}
|
|
}
|
|
|
|
loraLink.href = json._lorapreview_href || "";
|
|
loraPreview.src = json._lorapreview_src || "";
|
|
});
|
|
}
|
|
|
|
function toggleLora() {
|
|
const loraFileSelect = document.getElementById("loraFileSelect");
|
|
const loraName = loraFileSelect.options[loraFileSelect.selectedIndex].text;
|
|
const loraFile = loraFileSelect.value;
|
|
const loraRate = document.getElementById("loraRate").value;
|
|
const loraInput = document.getElementById("loraInput");
|
|
if (loraFile) {
|
|
const re = new RegExp("[\\n]?<lora:" + loraName + ":[-]?[0-9.]+>", "g");
|
|
if (loraInput.value.search(re) >= 0) {
|
|
loraInput.value = loraInput.value.replace(re, "");
|
|
} else {
|
|
loraInput.value += "\n<lora:" + loraName + ":" + loraRate + ">";
|
|
}
|
|
}
|
|
}
|
|
|
|
function moveLora() {
|
|
document.getElementById("moveLoraSelect").style.display = "block";
|
|
document.getElementById("moveLoraSelect").value = "";
|
|
}
|
|
|
|
function moveLoraFile() {
|
|
const moveFile = document.getElementById("loraFileSelect").value;
|
|
const moveTo = document.getElementById("moveLoraSelect").value;
|
|
if (!moveFile || !moveTo) {
|
|
return;
|
|
}
|
|
fetch("/flipstreamviewer/move_lorafile", {
|
|
method: "POST",
|
|
body: JSON.stringify([getStateAsJson(), moveTo]),
|
|
headers: {"Content-Type": "application/json"}
|
|
}).then(response => {
|
|
if (response.ok) {
|
|
alert("Lora moved successfully!");
|
|
} else {
|
|
alert("Failed to move lora.");
|
|
}
|
|
}).catch(error => {
|
|
alert("An error occurred while moving lora.");
|
|
});
|
|
}
|
|
"""
|
|
|
|
SCRIPT_TAG=r"""
|
|
function toggleTag() {
|
|
const loraTagSelect = document.getElementById("loraTagSelect");
|
|
const loraTag = document.getElementById("loraTagSelect").value;
|
|
const loraRank = parseInt(document.getElementById("loraRank").value);
|
|
const loraInput = document.getElementById("loraInput");
|
|
if (loraTag) {
|
|
const re = new RegExp("^\\s*" + loraTag + "\\s*(,\\s*|\n|$)|,\\s*" + loraTag + "\\s*(,|\n|$)", "g");
|
|
if (loraInput.value.search(re) >= 0) {
|
|
loraInput.value = loraInput.value.replace(re, "$2")
|
|
} else {
|
|
if (loraInput.value) {
|
|
loraInput.value += ", " + loraTag;
|
|
} else {
|
|
loraInput.value = loraTag;
|
|
}
|
|
}
|
|
} else {
|
|
for (var i = 1; i < Math.min(loraRank + 1, loraTagSelect.length); i++) {
|
|
loraInput.value += ", " + loraTagSelect.options[i].value;
|
|
}
|
|
}
|
|
}
|
|
|
|
function randomTag() {
|
|
const options = document.getElementById("loraTagSelect").options;
|
|
const loraInput = document.getElementById("loraInput");
|
|
const loraTag = options[Math.floor(Math.random() * options.length)].value;
|
|
if (loraTag) {
|
|
const re = new RegExp("^\\s*" + loraTag + "\\s*(,\\s*|\n|$)|,\\s*" + loraTag + "\\s*(,|\n|$)", "g");
|
|
if (loraInput.value.search(re) < 0) {
|
|
if (loraInput.value) {
|
|
loraInput.value += ", " + loraTag;
|
|
} else {
|
|
loraInput.value = loraTag;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
async function addWD14Tag() {
|
|
const json = await (await fetch("/flipstreamviewer/get_wd14tag", {
|
|
method: "POST",
|
|
body: JSON.stringify(getStateAsJson()),
|
|
headers: {"Content-Type": "application/json"}
|
|
})).json();
|
|
if (json.tags != "") {
|
|
loraInput.value = json.tags + "\n\n" + loraInput.value;
|
|
}
|
|
}
|
|
|
|
function clearLoraInput() {
|
|
document.getElementById("loraInput").value = "";
|
|
}
|
|
|
|
function showTagDialog() {
|
|
const lora = document.getElementById("loraInput").value;
|
|
const tags = lora.replace(/\n/g, ',').split(',').map(value => value.trim());
|
|
const tagCenterPanel = document.getElementById("tagCenterPanel");
|
|
const count = tagCenterPanel.children.length;
|
|
|
|
for (const child of Array.from(tagCenterPanel.children)) {
|
|
if (!child.classList.contains("disabled")) {
|
|
child.classList.add("disabled");
|
|
}
|
|
}
|
|
|
|
for (let i = 0; i < tags.length; i++) {
|
|
if (!tags[i])
|
|
continue;
|
|
|
|
const child = Array.from(tagCenterPanel.children).find(child => child.value == tags[i]);
|
|
if (child)
|
|
{
|
|
child.classList.remove("disabled");
|
|
continue;
|
|
}
|
|
|
|
if (tags[i] == "----") {
|
|
if (count == 0) {
|
|
const hr = document.createElement("hr");
|
|
hr.classList.add("tags");
|
|
hr.classList.add("separator");
|
|
tagCenterPanel.appendChild(hr);
|
|
}
|
|
} else {
|
|
const button = document.createElement("button");
|
|
button.value = tags[i];
|
|
button.textContent = tags[i];
|
|
button.classList.add("tags");
|
|
button.addEventListener("click", function() {
|
|
if (button.classList.contains("disabled")) {
|
|
button.classList.remove("disabled");
|
|
} else {
|
|
button.classList.add("disabled");
|
|
}
|
|
});
|
|
tagCenterPanel.appendChild(button);
|
|
}
|
|
}
|
|
|
|
document.getElementById("tagDialog").style.display = "flex";
|
|
}
|
|
|
|
function getRandomInt(min, max) {
|
|
return Math.floor(Math.random() * (max - min + 1) + min);
|
|
}
|
|
|
|
function tagCSel() {
|
|
const tagCenterPanel = document.getElementById("tagCenterPanel");
|
|
Array.from(tagCenterPanel.children).forEach(child => child.classList.contains("disabled") || child.classList.add("disabled"));
|
|
}
|
|
|
|
function tagRSel() {
|
|
const tagCenterPanel = document.getElementById("tagCenterPanel");
|
|
var group = [];
|
|
Array.from(tagCenterPanel.children).forEach(child => {
|
|
if (child.classList.contains("separator") && group.length > 0) {
|
|
const r = getRandomInt(0, group.length);
|
|
if (r != group.length) {
|
|
group[r].classList.remove("disabled");
|
|
}
|
|
group = [];
|
|
} else {
|
|
group.push(child);
|
|
}
|
|
});
|
|
const r = getRandomInt(0, group.length);
|
|
if (r != group.length) {
|
|
group[r].classList.remove("disabled");
|
|
}
|
|
}
|
|
|
|
function tagOK() {
|
|
const tagCenterPanel = document.getElementById("tagCenterPanel");
|
|
var selectedTags = [];
|
|
Array.from(tagCenterPanel.children).forEach(child => {
|
|
if (!child.classList.contains("separator") && !child.classList.contains("disabled")) {
|
|
selectedTags.push(child.value);
|
|
}
|
|
});
|
|
loraInput.value = selectedTags.join(", ");
|
|
closeTagDialog();
|
|
}
|
|
|
|
function closeTagDialog() {
|
|
document.getElementById("tagDialog").style.display = "none";
|
|
}
|
|
"""
|
|
|
|
SCRIPT_VIEW=r"""
|
|
var toggleViewFlag = true;
|
|
function toggleView() {
|
|
const leftPanel = document.getElementById("leftPanel");
|
|
const rightPanel = document.getElementById("rightPanel");
|
|
const presetLeftPanel = document.getElementById("presetLeftPanel");
|
|
const presetRightPanel = document.getElementById("presetRightPanel");
|
|
const messageBox = document.getElementById("messageBox");
|
|
if (toggleViewFlag) {
|
|
leftPanel.style.visibility = "hidden";
|
|
rightPanel.style.visibility = "hidden";
|
|
presetLeftPanel.style.visibility = "hidden";
|
|
presetRightPanel.style.visibility = "hidden";
|
|
toggleViewFlag = false;
|
|
} else {
|
|
document.body.style.backgroundImage = "none";
|
|
messageBox.style.visibility = "hidden";
|
|
document.getElementById("loraPreview").src = "";
|
|
document.querySelectorAll('.FlipStreamPreviewBox').forEach(x => x.src = "");
|
|
leftPanel.style.visibility = "visible";
|
|
rightPanel.style.visibility = "visible";
|
|
presetLeftPanel.style.visibility = "visible";
|
|
presetRightPanel.style.visibility = "visible";
|
|
toggleViewFlag = true;
|
|
}
|
|
}
|
|
|
|
function hideView() {
|
|
const leftPanel = document.getElementById("leftPanel");
|
|
const rightPanel = document.getElementById("rightPanel");
|
|
const presetLeftPanel = document.getElementById("presetLeftPanel");
|
|
const presetRightPanel = document.getElementById("presetRightPanel");
|
|
const messageBox = document.getElementById("messageBox");
|
|
closeCaptureDialog();
|
|
document.body.style.backgroundImage = "none";
|
|
messageBox.style.visibility = "hidden";
|
|
document.getElementById("loraPreview").src = "";
|
|
document.querySelectorAll('.FlipStreamPreviewBox').forEach(x => x.src = "");
|
|
leftPanel.style.visibility = "hidden";
|
|
rightPanel.style.visibility = "hidden";
|
|
presetLeftPanel.style.visibility = "hidden";
|
|
presetRightPanel.style.visibility = "hidden";
|
|
toggleViewFlag = false;
|
|
}
|
|
setTimeout(hideView, 300 * 1000);
|
|
|
|
async function refreshView() {
|
|
const data = await fetch("/flipstreamviewer/refresh_view")
|
|
.then(r => r.json()).catch(e => ({ status: "Fails to refresh view: " + e }));
|
|
document.getElementById("statusInfo").textContent = data.status_info || "Empty";
|
|
document.getElementById("messageBox").textContent = atob_utf8(data.message) || "";
|
|
if (document.body.style.backgroundImage != "none") {
|
|
document.body.style.backgroundImage = `url('/flipstreamviewer/stream?mtime=${data.stream_mtime || 0}')`;
|
|
}
|
|
document.querySelectorAll('.FlipStreamPreviewBox').forEach(async x => {
|
|
if (x.src != "") {
|
|
x.src = `/flipstreamviewer/preview?label=${x.name}&mtime=${data.preview_mtime[x.id] || 0}`;
|
|
}
|
|
});
|
|
if (data.update_and_reload) {
|
|
updateParam(true);
|
|
}
|
|
}
|
|
setInterval(refreshView, 1000);
|
|
"""
|
|
|
|
SCRIPT_CAPTURE=r"""
|
|
let capturedCanvas = document.createElement("canvas");
|
|
async function capture() {
|
|
try {
|
|
const video = document.createElement("video");
|
|
video.srcObject = await navigator.mediaDevices.getDisplayMedia({ video: true });
|
|
video.style.display = "none";
|
|
video.play();
|
|
video.addEventListener("loadedmetadata", () => {
|
|
const { videoWidth, videoHeight } = video;
|
|
capturedCtx = capturedCanvas.getContext("2d");
|
|
capturedCtx.clearRect(0, 0, capturedCanvas.width, capturedCanvas.height);
|
|
capturedCanvas.width = videoWidth;
|
|
capturedCanvas.height = videoHeight;
|
|
capturedCtx.drawImage(video, 0, 0);
|
|
video.srcObject.getTracks().forEach(track => track.stop());
|
|
video.srcObject = null;
|
|
updateCanvas();
|
|
});
|
|
} catch (error) {
|
|
alert("An error occurred while capture.");
|
|
}
|
|
}
|
|
|
|
function updateCanvas() {
|
|
document.getElementById("captureDialog").style.display = "flex";
|
|
const canvas = document.getElementById("canvas");
|
|
const ctx = canvas.getContext("2d");
|
|
const _capture_offsetX = parseInt(document.getElementById("offsetXRange").value, 10);
|
|
const _capture_offsetY = parseInt(document.getElementById("offsetYRange").value, 10);
|
|
const _capture_scale = parseInt(document.getElementById("scaleRange").value, 10) / 100;
|
|
ctx.clearRect(0, 0, canvas.width, canvas.height);
|
|
ctx.save();
|
|
ctx.scale(_capture_scale, _capture_scale);
|
|
ctx.translate(_capture_offsetX, _capture_offsetY);
|
|
ctx.drawImage(capturedCanvas, 0, 0);
|
|
ctx.restore();
|
|
}
|
|
|
|
function closeCaptureDialog() {
|
|
document.getElementById("captureDialog").style.display = "none";
|
|
}
|
|
|
|
function resetPos() {
|
|
document.getElementById("offsetXRange").value = 0;
|
|
document.getElementById("offsetYRange").value = 0;
|
|
document.getElementById("scaleRange").value = 100;
|
|
updateCanvas();
|
|
}
|
|
|
|
async function setFrame() {
|
|
const canvas = document.getElementById("canvas");
|
|
await fetch("/flipstreamviewer/set_frame", {
|
|
method: "POST",
|
|
body: canvas.toDataURL("image/png"),
|
|
headers: { "Content-Type": "image/png" }
|
|
});
|
|
closeCaptureDialog();
|
|
}
|
|
"""
|
|
|
|
SCRIPT_QUERY=r"""
|
|
function onInputDarker(value=-1) {
|
|
value = parseFloat(value);
|
|
if (value < 0) {
|
|
value = document.getElementById("darkerRange").value;
|
|
} else {
|
|
document.getElementById("darkerRange").value = value;
|
|
}
|
|
document.getElementById("darkerValue").innerText = value;
|
|
document.body.style.backgroundColor = 'rgba(0,0,0,' + value + ')';
|
|
}
|
|
onInputDarker();
|
|
|
|
function reloadPage(search="") {
|
|
if (search) {
|
|
location.replace(location.pathname + "?" + search);
|
|
} else {
|
|
location.reload();
|
|
}
|
|
}
|
|
|
|
function parseQueryParam() {
|
|
const p = new URLSearchParams(location.search)
|
|
if (p.has("darker")) {
|
|
onInputDarker(p.get("darker"));
|
|
}
|
|
if (p.has("toggleView")) {
|
|
toggleView();
|
|
}
|
|
if (p.has("showPresetDialog")) {
|
|
showPresetDialog();
|
|
}
|
|
if (p.has("presetFolder")) {
|
|
const presetFolder = document.getElementById("presetFolderSelect").value;
|
|
if (presetFolder != p.get("presetFolder")) {
|
|
updateParam(true, { presetFolder: p.get("presetFolder") }, {}, p.toString());
|
|
return;
|
|
}
|
|
}
|
|
if (p.has("presetFile")) {
|
|
const presetFile = document.getElementById("presetFileSelect").value;
|
|
if (presetFile != p.get("presetFile")) {
|
|
loadPreset(false, { presetFile: p.get("presetFile") }, p.toString());
|
|
return;
|
|
}
|
|
}
|
|
}
|
|
parseQueryParam();
|
|
"""
|
|
|
|
@server.PromptServer.instance.routes.get("/flipstreamviewer/stream")
|
|
async def stream(request):
|
|
if request.remote not in allowed_ips:
|
|
raise HTTPForbidden()
|
|
|
|
return web.Response(body=frame_buffer, headers={"Content-Type": "image/apng"})
|
|
|
|
|
|
@server.PromptServer.instance.routes.get("/flipstreamviewer/preview")
|
|
async def preview(request):
|
|
if request.remote not in allowed_ips:
|
|
raise HTTPForbidden()
|
|
|
|
label = request.rel_url.query.get('label', '')
|
|
key = label + "PreviewBox"
|
|
if key in state:
|
|
data = state[key][1]
|
|
else:
|
|
data = b""
|
|
return web.Response(body=data, headers={"Content-Type": "image/png"})
|
|
|
|
|
|
@server.PromptServer.instance.routes.post("/flipstreamviewer/preview_setroi")
|
|
async def preview_setroi(request):
|
|
if request.remote not in allowed_ips: raise HTTPForbidden()
|
|
data = await request.json()
|
|
param[data['label'] + "PreviewRoi"] = data
|
|
return web.Response()
|
|
|
|
|
|
@server.PromptServer.instance.routes.get("/flipstreamviewer")
|
|
async def viewer(request):
|
|
if request.remote not in allowed_ips:
|
|
print(request.remote)
|
|
raise HTTPForbidden()
|
|
|
|
block = {}
|
|
|
|
def add_section(title, section, hook):
|
|
block[f"{title}_{section}"] = f"""
|
|
<div class="row"><i>{section}</i></div>"""
|
|
|
|
def add_slider(title, label, default, min, max, step):
|
|
if not label.isidentifier():
|
|
raise RuntimeError(f"{title}: label must contain only valid identifier characters.")
|
|
param.setdefault(label, default)
|
|
block[f"{title}_{label}"] = f"""
|
|
<div class="row" style="color: lightslategray;">
|
|
<input class="FlipStreamSlider" id="{label}Slider" type="range" min="{min}" max="{max}" step="{step}" name="{label}" value="{float(param[label]):g}" oninput="{label}Value.innerText = this.value;" />
|
|
<span id="{label}Value">{float(param[label]):g}</span>{label}
|
|
</div>"""
|
|
|
|
def add_textbox(title, label, default, rows):
|
|
if not label.isidentifier():
|
|
raise RuntimeError(f"{title}: label must contain only valid identifier characters.")
|
|
param.setdefault(label, default)
|
|
block[f"{title}_{label}"] = f"""
|
|
<textarea class="FlipStreamTextBox" id="{label}TextBox" style="color: lightslategray;" placeholder="{label}" rows="{rows}" name="{label}">{atob_utf8(param[label])}</textarea>"""
|
|
|
|
def add_inputbox(title, label, default, boxtype):
|
|
if not label.isidentifier():
|
|
raise RuntimeError(f"{title}: label must contain only valid identifier characters.")
|
|
param.setdefault(label, default)
|
|
if boxtype == "seed":
|
|
block[f"{title}_{label}"] = f"""
|
|
<div class="row" style="color: lightslategray;">
|
|
{label}: <input class="FlipStreamInputBox" id="{label}InputBox" style="color: lightslategray;" placeholder="{label}" type="number" name="{label}" value="{param[label]}" />
|
|
<button onclick="{label}InputBox.value=Math.floor(Math.random()*1e7); updateParam()">R</button>
|
|
</div>"""
|
|
elif boxtype == "r4d":
|
|
block[f"{title}_{label}"] = f"""
|
|
<div class="row" style="color: lightslategray;">
|
|
{label}: <input class="FlipStreamInputBox" id="{label}InputBox" style="color: lightslategray;" placeholder="{label}" type="number" name="{label}" value="{param[label]}" />
|
|
<button onclick="{label}InputBox.value=Math.floor(Math.random()*1e4); updateParam()">R</button>
|
|
</div>"""
|
|
else:
|
|
block[f"{title}_{label}"] = f"""
|
|
<div class="row" style="color: lightslategray;">
|
|
{label}: <input class="FlipStreamInputBox" id="{label}InputBox" style="color: lightslategray;" placeholder="{label}" type="{boxtype}" name="{label}" value="{param[label]}" />
|
|
<button onclick="updateParam()">U</button>
|
|
</div>"""
|
|
|
|
def add_selectbox(title, label, default, listitems):
|
|
listitems = listitems.split(",")
|
|
if not label.isidentifier():
|
|
raise RuntimeError(f"{title}: label must contain only valid identifier characters.")
|
|
if not all(item == html.escape(item) for item in listitems):
|
|
raise RuntimeError(f"{title}: listitems must contain only HTML-acceptable characters.")
|
|
param.setdefault(label, "")
|
|
text_html = f"""
|
|
<select class="FlipStreamSelectBox" id="{label}SelectBox" name="{label}">
|
|
<option value="" disabled selected>{label}</option>"""
|
|
for item in listitems:
|
|
text_html += f"""
|
|
<option value="{item}"{" selected" if param[label] == item else ""}>{item}</option>"""
|
|
text_html += f"""
|
|
</select>"""
|
|
block[f"{title}_{label}"] = text_html
|
|
|
|
def add_fileselect(title, label, default, folder_name, folder_path, mode, use_sub, use_move):
|
|
if not label.isidentifier():
|
|
raise RuntimeError(f"{title}: label must contain only valid identifier characters.")
|
|
if not (mode == "" or mode.isidentifier()):
|
|
raise RuntimeError(f"{title}: mode must contain only valid identifier characters.")
|
|
param.setdefault(label, "")
|
|
state.setdefault(f"{label}Folder", "")
|
|
text_html = ""
|
|
if use_sub:
|
|
text_html += f"""
|
|
<select class="FlipStreamFolderSelect willreload" id="{label}FolderSelect" name="{label}Folder" onchange="updateParam(true)">
|
|
<option value="">{label} folder</option>"""
|
|
for dir in sorted(Path(folder_path, mode).glob("*/")):
|
|
selected = " selected" if state[f"{label}Folder"] == dir.name else ""
|
|
text_html += f"""
|
|
<option value="{dir.name}"{selected}>{dir.name}</option>"""
|
|
text_html += f"""
|
|
</select>"""
|
|
text_html += f"""
|
|
<div class="row">
|
|
<select class="FlipStreamFileSelect" id="{label}FileSelect" name="{label}">
|
|
<option value="">{label} default</option>"""
|
|
if param[label]:
|
|
text_html += f"""
|
|
<option value="{param[label]}" selected>*{Path(param[label]).stem}</option>"""
|
|
if use_sub:
|
|
files = sorted(Path(folder_path, mode, state[f"{label}Folder"]).glob("*.*"))
|
|
files = [Path(file).relative_to(folder_path) for file in files]
|
|
else:
|
|
files = [Path(file) for file in FlipStreamFileSelect.get_filelist(folder_name, folder_path)]
|
|
|
|
png_files = [file for file in files if file.suffix.lower() == '.png']
|
|
other_files = [file for file in files if file.suffix.lower() != '.png']
|
|
|
|
for file in other_files:
|
|
if file != param[label]:
|
|
text_html += f"""
|
|
<option value="{file}">{file.stem}</option>"""
|
|
png_file = file.with_suffix('.png')
|
|
if png_file in png_files:
|
|
png_files.remove(png_file)
|
|
for file in png_files:
|
|
if file != param[label]:
|
|
text_html += f"""
|
|
<option value="{file}">{file.stem}</option>"""
|
|
text_html += f"""
|
|
</select>"""
|
|
if use_move:
|
|
text_html += f"""
|
|
<button class="willreload" id="{label}MoveButton" onClick="showMoveFileSelect({label}MoveFileSelect)">M</button>"""
|
|
text_html += f"""
|
|
</div>"""
|
|
if use_move:
|
|
text_html += f"""
|
|
<select class="FlipStreamMoveFileSelect" id="{label}MoveFileSelect" onchange="moveFile(String.raw`{folder_path}`, '{mode}', '{label}')">
|
|
<option value="" disabled selected>move to</option>"""
|
|
for dir in Path(folder_path, mode).glob("*/"):
|
|
text_html += f"""
|
|
<option value="{dir.name}">{dir.name}</option>"""
|
|
text_html += f"""
|
|
</select>"""
|
|
block[f"{title}_{label}"] = text_html
|
|
|
|
def add_previewbox(title, label, tensor):
|
|
if not label.isidentifier():
|
|
raise RuntimeError(f"{title}: label must contain only valid identifier characters.")
|
|
if (label + "PreviewBox") in state:
|
|
block[f"{title}_{label}"] = f"""
|
|
<div class="row" style="color: lightslategray;">
|
|
<img class="FlipStreamPreviewBox" id="{label}PreviewBox" name="{label}" src="/flipstreamviewer/preview?label={label}" alt onerror="this.onerror = null; this.src='';" />
|
|
<canvas class="FlipStreamPreviewRoi" id="{label}PreviewRoi"></canvas>
|
|
</div>"""
|
|
|
|
hist = server.PromptServer.instance.prompt_queue.get_history(max_items=1)
|
|
nodedict = next(iter(hist.values()))["prompt"][2] if hist else None
|
|
if nodedict:
|
|
for node in nodedict.values():
|
|
class_type = node["class_type"]
|
|
title = node["_meta"]["title"]
|
|
inputs = node["inputs"]
|
|
if class_type == "FlipStreamSection":
|
|
add_section(title, **inputs)
|
|
if class_type == "FlipStreamSlider":
|
|
add_slider(title, **inputs)
|
|
if class_type == "FlipStreamTextBox":
|
|
add_textbox(title, **inputs)
|
|
if class_type == "FlipStreamInputBox":
|
|
add_inputbox(title, **inputs)
|
|
if class_type.startswith("FlipStreamSelectBox"):
|
|
add_selectbox(title, **inputs)
|
|
if class_type.startswith("FlipStreamFileSelect"):
|
|
add_fileselect(title, **inputs)
|
|
if class_type == "FlipStreamPreviewBox":
|
|
add_previewbox(title, **inputs)
|
|
|
|
text_html = f"""<html>{HEAD}<body>
|
|
<div id="mainDialog">
|
|
<div id="leftPanel">
|
|
<div class="row">
|
|
<button id="updateButton" class="willreload" onclick="updateParam(true)">Update and reload</button>
|
|
</div>
|
|
{"".join([x[1] for x in sorted(block.items())])}
|
|
</div>
|
|
<div id="centerPanel">
|
|
<button id="toggleViewButton" onclick="toggleView()"></button>
|
|
<div id="messageBox" onclick="toggleView()"></div>
|
|
</div>
|
|
<div id="rightPanel">
|
|
<div class="row"><i>Status</i></div>
|
|
<div id="statusInfo"></div>
|
|
<div class="row"><i>Darker</i></div>
|
|
<div class="row">
|
|
<input id="darkerRange" type="range" min="0" max="1" step="0.01" value="{state["darker"]}" oninput="onInputDarker();" />
|
|
<span id="darkerValue">{state["darker"]}</span>drk
|
|
</div>
|
|
<div class="row"><i>Tagger</i></div>
|
|
<div class="row">
|
|
<button onclick="capture()">Capture</button>
|
|
<button onclick="addWD14Tag()">WD14</button>
|
|
</div>
|
|
<div class="row">
|
|
<input id="wd14thRange" type="range" min="0" max="1" step="0.01" value="{state["wd14th"]}" oninput="wd14thValue.innerText = this.value;" />
|
|
<span id="wd14thValue">{state["wd14th"]}</span>wth
|
|
</div>
|
|
<div class="row">
|
|
<input id="wd14cthRange" type="range" min="0" max="1" step="0.01" value="{state["wd14cth"]}" oninput="wd14cthValue.innerText = this.value;" />
|
|
<span id="wd14cthValue">{state["wd14cth"]}</span>cth
|
|
</div>
|
|
<div class="row"><i>Preset</i></div>
|
|
<select id="presetFolderSelect" class="willreload" onchange="updateParam(true)">
|
|
<option value="" selected>preset folder</option>
|
|
{"".join([f'<option value="{dir.name}"{" selected" if state["presetFolder"] == dir.name else ""}>{dir.name}</option>' for dir in Path("preset").glob("*/")])}
|
|
</select>
|
|
<div class="row">
|
|
<select id="presetFileSelect">
|
|
<option value="" disabled selected>preset</option>
|
|
{"".join([f'<option value="{file.name}"{" selected" if state["presetFile"] == file.name else ""}>{file.stem}</option>' for file in Path("preset", state["presetFolder"]).glob("*.json")])}
|
|
</select>
|
|
<button onclick="movePreset()">M</button>
|
|
</div>
|
|
<select id="movePresetSelect" onchange="movePresetFile()">
|
|
<option value="" disabled selected>move to</option>
|
|
{"".join([f'<option value="{dir.name}">{dir.name}</option>' for dir in Path("preset").glob("*/")])}
|
|
</select>
|
|
<div class="row">
|
|
<input id="presetTitleInput" placeholder="preset title" value="{state["presetTitle"]}" />
|
|
<button onclick="savePreset()">Save</button>
|
|
</div>
|
|
<div class="row">
|
|
<button onclick="showPresetDialog()">Choose</button>
|
|
<button class="willreload" onclick="loadPreset()">Load</button>
|
|
<button class="willreload" onclick="loadPreset(true)">LoraOnly</button>
|
|
</div>
|
|
<div class="row"><i>Lora</i></div>
|
|
<select id="loraFolderSelect" class="willreload" onchange="updateParam(true)">
|
|
<option value="" selected>lora folder</option>
|
|
{"".join([f'<option value="{dir.name}"{" selected" if state["loraFolder"] == dir.name else ""}>{dir.name}</option>' for dir in Path("ComfyUI/models/loras", state["loraMode"]).glob("*/")])}
|
|
</select>
|
|
<div class="row">
|
|
<select id="loraFileSelect" onchange="selectLoraFile()">
|
|
<option value="" disabled selected>lora file</option>
|
|
{"".join([f'<option value="{file.name}"{" selected" if state["loraFile"] == file.name else ""}>{file.stem}</option>' for file in Path("ComfyUI/models/loras", state["loraMode"], state["loraFolder"]).glob("*.safetensors")])}
|
|
</select>
|
|
<button onclick="toggleLora()">T</button>
|
|
<button onClick="moveLora()">M</button>
|
|
</div>
|
|
<select id="moveLoraSelect" onchange="moveLoraFile()">
|
|
<option value="" disabled selected>move to</option>
|
|
{"".join([f'<option value="{dir.name}">{dir.name}</option>' for dir in Path("ComfyUI/models/loras", state["loraMode"]).glob("*/")])}
|
|
</select>
|
|
<div class="row">
|
|
<select id="loraTagSelect" onchange="toggleTag()">
|
|
<option value="">tags</option>
|
|
{"".join([f'<option value="{opt["value"]}"{" selected" if state["loraTag"] == opt["value"] else ""}>{opt["text"]}</option>' if opt["value"] else "" for opt in json.loads(state["loraTagOptions"])])}
|
|
</select>
|
|
<button onclick="toggleTag()">T</button>
|
|
<button onclick="randomTag()">R</button>
|
|
</div>
|
|
Rate: <select id="loraRate">
|
|
<option value="8" {"selected" if state["loraRate"] == "8" else ""}>8</option>
|
|
<option value="7" {"selected" if state["loraRate"] == "7" else ""}>7</option>
|
|
<option value="6" {"selected" if state["loraRate"] == "6" else ""}>6</option>
|
|
<option value="5" {"selected" if state["loraRate"] == "5" else ""}>5</option>
|
|
<option value="4" {"selected" if state["loraRate"] == "4" else ""}>4</option>
|
|
<option value="3" {"selected" if state["loraRate"] == "3" else ""}>3</option>
|
|
<option value="2" {"selected" if state["loraRate"] == "2" else ""}>2</option>
|
|
<option value="1" {"selected" if state["loraRate"] == "1" else ""}>1</option>
|
|
<option value="0.9" {"selected" if state["loraRate"] == "0.9" else ""}>0.9</option>
|
|
<option value="0.8" {"selected" if state["loraRate"] == "0.8" else ""}>0.8</option>
|
|
<option value="0.7" {"selected" if state["loraRate"] == "0.7" else ""}>0.7</option>
|
|
<option value="0.6" {"selected" if state["loraRate"] == "0.6" else ""}>0.6</option>
|
|
<option value="0.5" {"selected" if state["loraRate"] == "0.5" else ""}>0.5</option>
|
|
<option value="0.4" {"selected" if state["loraRate"] == "0.4" else ""}>0.4</option>
|
|
<option value="0.3" {"selected" if state["loraRate"] == "0.3" else ""}>0.3</option>
|
|
<option value="0.2" {"selected" if state["loraRate"] == "0.2" else ""}>0.2</option>
|
|
<option value="0.1" {"selected" if state["loraRate"] == "0.1" else ""}>0.1</option>
|
|
<option value="0" {"selected" if state["loraRate"] == "0" else ""}>0</option>
|
|
<option value="-1" {"selected" if state["loraRate"] == "-1" else ""}>-1</option>
|
|
<option value="-2" {"selected" if state["loraRate"] == "-2" else ""}>-2</option>
|
|
<option value="-3" {"selected" if state["loraRate"] == "-3" else ""}>-3</option>
|
|
<option value="-4" {"selected" if state["loraRate"] == "-4" else ""}>-4</option>
|
|
<option value="-5" {"selected" if state["loraRate"] == "-5" else ""}>-5</option>
|
|
</select>
|
|
<select id="loraRank">
|
|
<option value="0" {"selected" if state["loraRank"] == "0" else ""}>0</option>
|
|
<option value="10" {"selected" if state["loraRank"] == "10" else ""}>10</option>
|
|
<option value="20" {"selected" if state["loraRank"] == "20" else ""}>20</option>
|
|
<option value="30" {"selected" if state["loraRank"] == "30" else ""}>30</option>
|
|
<option value="40" {"selected" if state["loraRank"] == "40" else ""}>40</option>
|
|
<option value="50" {"selected" if state["loraRank"] == "50" else ""}>50</option>
|
|
</select>
|
|
<div class="row">
|
|
<button onclick="showTagDialog()">Choose</button>
|
|
<button onclick="updateParam()">Update</button>
|
|
<button onclick="clearLoraInput()">Clr</button>
|
|
<button onclick="showTagDialog();tagCSel();tagRSel();tagOK();updateParam()">R</button>
|
|
</div>
|
|
<textarea id="loraInput" placeholder="Enter lora" rows="12">{atob_utf8(param["lora"])}</textarea>
|
|
<div class="row">
|
|
<a id="loraLink" href="{state["loraLinkHref"] or "javascript:void(0)"}" target="_blank">
|
|
<img id="loraPreview" src="{state["loraPreviewSrc"]}" alt onerror="this.onerror = null; this.src='';" />
|
|
</a>
|
|
</div>
|
|
</div>
|
|
</div>
|
|
<div id="captureDialog">
|
|
<div id="captureLeftPanel">
|
|
</div>
|
|
<div id="captureCenterPanel">
|
|
<canvas id="canvas" width="960" height="600" />
|
|
</div>
|
|
<div id="captureRightPanel">
|
|
<div class="row">
|
|
<button onclick="resetPos()">Reset</button>
|
|
</div>
|
|
<div class="row">
|
|
X <input id="offsetXRange" type="range" min="-960" max="960" value="{param["_capture_offsetX"]}" onchange="updateCanvas()">
|
|
</div>
|
|
<div class="row">
|
|
Y <input id="offsetYRange" type="range" min="-600" max="600" value="{param["_capture_offsetY"]}" onchange="updateCanvas()">
|
|
</div>
|
|
<div class="row">
|
|
S <input id="scaleRange" type="range" min="50" max="400" value="{param["_capture_scale"]}" onchange="updateCanvas()">
|
|
</div>
|
|
<div class="row">
|
|
<button onclick="setFrame()">SetFrame</button>
|
|
<button onclick="closeCaptureDialog()">Close</button>
|
|
</div>
|
|
</div>
|
|
</div>
|
|
<div id="tagDialog">
|
|
<div id="tagLeftPanel">
|
|
</div>
|
|
<div id="tagCenterPanel">
|
|
</div>
|
|
<div id="tagRightPanel">
|
|
<div class="row">
|
|
<button onclick="tagCSel()">CSel</button>
|
|
<button onclick="tagRSel()">RSel</button>
|
|
</div>
|
|
<div class="row">
|
|
<button onclick="tagOK()">OK</button>
|
|
<button onclick="closeTagDialog()">Cancel</button>
|
|
</div>
|
|
</div>
|
|
</div>
|
|
<div id="presetDialog">
|
|
<div id="presetLeftPanel">
|
|
</div>
|
|
<div id="presetCenterPanel">
|
|
<button id="toggleViewButton" onclick="toggleView()"></button>
|
|
<div id="messageBox" onclick="toggleView()"></div>
|
|
</div>
|
|
<div id="presetRightPanel">
|
|
<div class="row">
|
|
<button onclick="closePresetDialog()">Close</button>
|
|
</div>
|
|
<div class="row"><i>Status</i></div>
|
|
<div id="statusInfo"></div>
|
|
<div class="row"><i>Darker</i></div>
|
|
<div class="row">
|
|
<input id="darkerRange" type="range" min="0" max="1" step="0.01" value="{state["darker"]}" oninput="onInputDarker(this.value);" />
|
|
<span id="darkerValue">{state["darker"]}</span>drk
|
|
</div>
|
|
<div class="row"><i>Preset</i></div>
|
|
{"".join([f'''
|
|
<button onclick="loadPreset(false, {{ presetFile: '{file.name}' }}, 'showPresetDialog')">{file.stem}</button>
|
|
''' for file in Path("preset", state["presetFolder"]).glob("*.json")])}
|
|
</div>
|
|
</div>
|
|
<script>
|
|
{SCRIPT_PARAM}
|
|
{SCRIPT_PRESET}
|
|
{SCRIPT_CKPT}
|
|
{SCRIPT_LORA}
|
|
{SCRIPT_TAG}
|
|
{SCRIPT_VIEW}
|
|
{SCRIPT_CAPTURE}
|
|
{SCRIPT_QUERY}
|
|
</script>
|
|
</body></html>"""
|
|
return web.Response(text=text_html, content_type="text/html")
|
|
|
|
|
|
@server.PromptServer.instance.routes.get("/flipstreamviewer/refresh_view")
|
|
async def get_status(request):
|
|
if request.remote not in allowed_ips:
|
|
raise HTTPForbidden()
|
|
|
|
# Get status info from history
|
|
remain = server.PromptServer.instance.prompt_queue.get_tasks_remaining()
|
|
hist = server.PromptServer.instance.prompt_queue.get_history(max_items=1)
|
|
status_info = []
|
|
if frame_updating:
|
|
status_info.append("updating")
|
|
status_info.append(f"q{remain}")
|
|
info = next(iter(hist.values()))["status"] if hist else None
|
|
if info:
|
|
errinfo = info["messages"][2][1]
|
|
status_info.append(info["status_str"])
|
|
status_info += [errinfo[key] for key in ["node_id", "node_type", "exception_message", "exception_type"] if key in errinfo]
|
|
|
|
state.update(setstate)
|
|
setstate.clear()
|
|
data = {}
|
|
data["status_info"] = status_info
|
|
data["stream_mtime"] = frame_mtime
|
|
data["preview_mtime"] = {key: state[key][0] for key in state if key.endswith("PreviewBox")}
|
|
data["message"] = state["message"]
|
|
data["update_and_reload"] = state["update_and_reload"]
|
|
state["update_and_reload"] = False
|
|
return web.json_response(data)
|
|
|
|
|
|
@server.PromptServer.instance.routes.post("/flipstreamviewer/update_param")
|
|
async def update_param(request):
|
|
if request.remote not in allowed_ips:
|
|
raise HTTPForbidden()
|
|
|
|
stt, prm = await request.json()
|
|
state.update(stt)
|
|
state.update(setstate)
|
|
setstate.clear()
|
|
param.update(prm)
|
|
param.update(setparam)
|
|
setparam.clear()
|
|
time.sleep(UPDATE_DELAY)
|
|
return web.Response()
|
|
|
|
|
|
@server.PromptServer.instance.routes.post("/flipstreamviewer/get_lorainfo")
|
|
async def get_lorainfo(request):
|
|
if request.remote not in allowed_ips:
|
|
raise HTTPForbidden()
|
|
|
|
req = await request.json()
|
|
loraPath = Path("ComfyUI/models/loras", state["loraMode"], req["loraFolder"], req["loraFile"])
|
|
hash = None
|
|
with open(loraPath, "rb") as file:
|
|
header_size = int.from_bytes(file.read(8), "little", signed=False)
|
|
if header_size <= 0:
|
|
raise HTTPError("get_lorainfo: Invalid header size")
|
|
|
|
header = file.read(header_size)
|
|
if header_size <= 0:
|
|
raise HTTPError("get_lorainfo: Invalid header")
|
|
|
|
file.seek(0)
|
|
hash = hashlib.sha256(file.read()).hexdigest()
|
|
|
|
header_json = json.loads(header)
|
|
lorainfo = header_json["__metadata__"] if "__metadata__" in header_json else {}
|
|
|
|
if hash:
|
|
res = requests.get("https://civitai.com/api/v1/model-versions/by-hash/" + hash).json()
|
|
lorainfo["_lorapreview_href"] = "https://civitai.com/models/" + str(res["modelId"])
|
|
lorainfo["_lorapreview_src"] = res["images"][0]["url"]
|
|
|
|
return web.json_response(lorainfo)
|
|
|
|
|
|
@server.PromptServer.instance.routes.post("/flipstreamviewer/get_wd14tag")
|
|
async def get_wd14tag(request):
|
|
if request.remote not in allowed_ips:
|
|
raise HTTPForbidden()
|
|
|
|
if wd14tagger is None:
|
|
raise RuntimeError("get_wd14tag: ComfyUI-WD14-Tagger must be installed to use this function.")
|
|
|
|
stt = await request.json()
|
|
state.update(stt);
|
|
tags = []
|
|
if frame_buffer is not None:
|
|
tags = await wd14tagger.tag(Image.fromarray(iio.imread(frame_buffer, index=0)), "wd-v1-4-moat-tagger-v2.onnx", state["wd14th"], state["wd14cth"], exclude_tags)
|
|
return web.json_response({"tags": tags})
|
|
|
|
|
|
@server.PromptServer.instance.routes.post("/flipstreamviewer/set_frame")
|
|
async def set_frame(request):
|
|
if request.remote not in allowed_ips:
|
|
raise HTTPForbidden()
|
|
|
|
global frame_buffer
|
|
global frame_mtime
|
|
pngdata = base64.b64decode((await request.text()).split(',', 1)[1])
|
|
with BytesIO(pngdata) as data:
|
|
with BytesIO() as output:
|
|
iio.imwrite(output, [iio.imread(data)], format="png", extension=".apng", compression=STREAM_COMPRESSION)
|
|
frame_buffer = output.getvalue()
|
|
frame_mtime = time.time()
|
|
return web.Response()
|
|
|
|
|
|
@server.PromptServer.instance.routes.post("/flipstreamviewer/move_file")
|
|
async def move_file(request):
|
|
if request.remote not in allowed_ips:
|
|
raise HTTPForbidden()
|
|
|
|
stt, folder_path, mode, label, moveFrom, moveTo = await request.json()
|
|
state.update(stt)
|
|
pathFrom = Path(folder_path, mode, state[label + "Folder"], Path(moveFrom).name)
|
|
pathTo = Path(folder_path, mode, moveTo, pathFrom.name)
|
|
Path(pathFrom).rename(pathTo)
|
|
state[label + "Folder"] = moveTo
|
|
return web.Response()
|
|
|
|
|
|
@server.PromptServer.instance.routes.post("/flipstreamviewer/move_presetfile")
|
|
async def move_presetfile(request):
|
|
if request.remote not in allowed_ips:
|
|
raise HTTPForbidden()
|
|
|
|
stt, moveTo = await request.json()
|
|
state.update(stt)
|
|
pathFrom = Path("preset", state["presetFolder"], state["presetFile"])
|
|
pathTo = Path("preset", moveTo, pathFrom.name)
|
|
Path(pathFrom).rename(pathTo)
|
|
state["presetFolder"] = moveTo
|
|
return web.Response()
|
|
|
|
|
|
@server.PromptServer.instance.routes.post("/flipstreamviewer/move_lorafile")
|
|
async def move_lorafile(request):
|
|
if request.remote not in allowed_ips:
|
|
raise HTTPForbidden()
|
|
|
|
stt, moveTo = await request.json()
|
|
state.update(stt)
|
|
pathFrom = Path("ComfyUI/models/loras", state["loraMode"], state["loraFolder"], state["loraFile"])
|
|
pathTo = Path("ComfyUI/models/loras", state["loraMode"], moveTo, pathFrom.name)
|
|
Path(pathFrom).rename(pathTo)
|
|
state["loraFolder"] = moveTo
|
|
return web.Response()
|
|
|
|
|
|
@server.PromptServer.instance.routes.post("/flipstreamviewer/load_preset")
|
|
async def load_preset(request):
|
|
if request.remote not in allowed_ips:
|
|
raise HTTPForbidden()
|
|
|
|
stt, loraPromptOnly = await request.json()
|
|
with open(Path("preset", stt["presetFolder"], stt["presetFile"]), "r") as file:
|
|
buf = json.load(file)
|
|
if loraPromptOnly:
|
|
buf = {"lora": buf.get("lora", "")}
|
|
|
|
state.update(stt)
|
|
param.update(buf)
|
|
state["presetTitle"] = Path(state["presetFile"]).stem
|
|
time.sleep(UPDATE_DELAY)
|
|
return web.json_response({"lora": param["lora"], "presetTitle": state["presetTitle"]})
|
|
|
|
|
|
@server.PromptServer.instance.routes.post("/flipstreamviewer/save_preset")
|
|
async def save_preset(request):
|
|
if request.remote not in allowed_ips:
|
|
raise HTTPForbidden()
|
|
|
|
stt, prm = await request.json()
|
|
state.update(stt)
|
|
param.update(prm)
|
|
time.sleep(UPDATE_DELAY)
|
|
with open(Path("preset", state["presetFolder"], state["presetTitle"] + ".json"), "w") as file:
|
|
json.dump(param, file)
|
|
return web.Response()
|
|
|
|
|
|
class FlipStreamSection:
|
|
@classmethod
|
|
def INPUT_TYPES(s):
|
|
return {
|
|
"required": {
|
|
"section": ("STRING", {"default": "Section"}),
|
|
},
|
|
"optional": {
|
|
"hook": (any,),
|
|
}
|
|
}
|
|
|
|
RETURN_TYPES = (any,)
|
|
FUNCTION = "run"
|
|
CATEGORY = "FlipStreamViewer"
|
|
|
|
def run(self, section, hook=None):
|
|
return (hook,)
|
|
|
|
|
|
class FlipStreamSlider:
|
|
@classmethod
|
|
def INPUT_TYPES(s):
|
|
return {
|
|
"required": {
|
|
"label": ("STRING", {"default": "empty"}),
|
|
"default": ("FLOAT", {"default": 0, "step": 0.01, "round": 0.01}),
|
|
"min": ("FLOAT", {"default": 0, "step": 0.01, "round": 0.01}),
|
|
"max": ("FLOAT", {"default": 0, "step": 0.01, "round": 0.01}),
|
|
"step": ("FLOAT", {"default": 0.01, "min": 0.00, "step": 0.01, "round": 0.01}),
|
|
}
|
|
}
|
|
|
|
RETURN_TYPES = ("FLOAT", "INT", "BOOLEAN")
|
|
FUNCTION = "run"
|
|
CATEGORY = "FlipStreamViewer"
|
|
|
|
@classmethod
|
|
def IS_CHANGED(cls, label, default, **kwargs):
|
|
param.setdefault(label, default)
|
|
return hash((param[label],))
|
|
|
|
def run(self, label, default, **kwargs):
|
|
global frame_updating
|
|
frame_updating = True
|
|
param.setdefault(label, default)
|
|
return (float(param[label]), int(float(param[label])), bool(float(param[label])))
|
|
|
|
|
|
class FlipStreamTextBox:
|
|
@classmethod
|
|
def INPUT_TYPES(s):
|
|
return {
|
|
"required": {
|
|
"label": ("STRING", {"default": "empty"}),
|
|
"default": ("STRING", {"default": "", "multiline": True}),
|
|
"rows": ("INT", {"default": 3}),
|
|
}
|
|
}
|
|
|
|
RETURN_TYPES = ("STRING",)
|
|
FUNCTION = "run"
|
|
CATEGORY = "FlipStreamViewer"
|
|
|
|
@classmethod
|
|
def IS_CHANGED(cls, label, default, **kwargs):
|
|
param.setdefault(label, btoa_utf8(default))
|
|
return hash((param[label],))
|
|
|
|
def run(self, label, default, **kwargs):
|
|
global frame_updating
|
|
frame_updating = True
|
|
param.setdefault(label, btoa_utf8(default))
|
|
return (atob_utf8(param[label]),)
|
|
|
|
|
|
class FlipStreamInputBox:
|
|
@classmethod
|
|
def INPUT_TYPES(s):
|
|
return {
|
|
"required": {
|
|
"label": ("STRING", {"default": "empty"}),
|
|
"default": ("STRING", {"default": ""}),
|
|
"boxtype": (["text", "number", "seed", "r4d"],),
|
|
}
|
|
}
|
|
|
|
RETURN_TYPES = ("STRING", "FLOAT", "INT", "BOOLEAN")
|
|
FUNCTION = "run"
|
|
CATEGORY = "FlipStreamViewer"
|
|
|
|
@classmethod
|
|
def IS_CHANGED(cls, label, default, **kwargs):
|
|
param.setdefault(label, default)
|
|
return hash((param[label],))
|
|
|
|
def floator0(self, v):
|
|
try:
|
|
return float(v)
|
|
except:
|
|
return 0
|
|
|
|
def run(self, label, default, boxtype, **kwargs):
|
|
global frame_updating
|
|
frame_updating = True
|
|
param.setdefault(label, default)
|
|
t = param[label]
|
|
v = self.floator0(t)
|
|
return (t, v, int(v), bool(t if boxtype == "text" else v))
|
|
|
|
|
|
class FlipStreamSelectBox:
|
|
LISTITEMS = ["a", "b", "c"]
|
|
|
|
@classmethod
|
|
def INPUT_TYPES(s):
|
|
return {
|
|
"required": {
|
|
"label": ("STRING", {"default": "empty"}),
|
|
"default": (s.LISTITEMS,),
|
|
"listitems": ("STRING", {"default": ",".join(s.LISTITEMS)})
|
|
},
|
|
}
|
|
|
|
RETURN_TYPES = (any, "BOOLEAN",)
|
|
RETURN_NAMES = ("item", "enable",)
|
|
FUNCTION = "run"
|
|
CATEGORY = "FlipStreamViewer"
|
|
|
|
@classmethod
|
|
def IS_CHANGED(cls, label, **kwargs):
|
|
param.setdefault(label, "")
|
|
return hash((param[label],))
|
|
|
|
def run(self, label, default, **kwargs):
|
|
global frame_updating
|
|
frame_updating = True
|
|
param.setdefault(label, "")
|
|
item = param[label] if param[label] else default
|
|
return (item, param[label] != "")
|
|
|
|
|
|
class FlipStreamSelectBox_Samplers(FlipStreamSelectBox):
|
|
LISTITEMS = comfy.samplers.KSampler.SAMPLERS
|
|
|
|
|
|
class FlipStreamSelectBox_Scheduler(FlipStreamSelectBox):
|
|
LISTITEMS = comfy.samplers.KSampler.SCHEDULERS
|
|
|
|
|
|
class FlipStreamFileSelect:
|
|
FOLDER_NAME = ""
|
|
FOLDER_PATH = ""
|
|
|
|
@staticmethod
|
|
def get_filelist(folder_name, folder_path):
|
|
if folder_name == "checkpoints":
|
|
return CheckpointLoaderSimple.INPUT_TYPES()["required"]["ckpt_name"][0]
|
|
elif folder_name == "vae":
|
|
return VAELoader.INPUT_TYPES()["required"]["vae_name"][0]
|
|
elif folder_name == "controlnet":
|
|
return folder_paths.get_filename_list("controlnet")
|
|
elif folder_name == "tensorrt":
|
|
if folder_path.startswith("_error_"):
|
|
return [folder_path]
|
|
if TensorRTLoader is None:
|
|
return ["_error_ ComfyUI_TensorRT is not installed"]
|
|
return TensorRTLoader.INPUT_TYPES()["required"]["unet_name"][0]
|
|
elif folder_name == "animatediff_models":
|
|
if folder_path.startswith("_error_"):
|
|
return [folder_path]
|
|
return folder_paths.get_filename_list(folder_name)
|
|
else:
|
|
return list(map(str, Path(folder_path).glob("*.*")))
|
|
|
|
@classmethod
|
|
def INPUT_TYPES(s):
|
|
return {
|
|
"required": {
|
|
"label": ("STRING", {"default": "empty"}),
|
|
"default": ([""] + s.get_filelist(s.FOLDER_NAME, s.FOLDER_PATH),),
|
|
"folder_name": ([s.FOLDER_NAME],),
|
|
"folder_path": ([s.FOLDER_PATH],),
|
|
"mode": ("STRING", {"default": ""}),
|
|
"use_sub": ("BOOLEAN", {"defalut": False}),
|
|
"use_move": ("BOOLEAN", {"defalut": False}),
|
|
}
|
|
}
|
|
|
|
RETURN_TYPES = (any, any, "BOOLEAN",)
|
|
RETURN_NAMES = ("file", "path", "enable",)
|
|
FUNCTION = "run"
|
|
CATEGORY = "FlipStreamViewer"
|
|
|
|
@classmethod
|
|
def IS_CHANGED(cls, label, **kwargs):
|
|
param.setdefault(label, "")
|
|
return hash((param[label],))
|
|
|
|
def run(self, label, default, folder_path, **kwargs):
|
|
global frame_updating
|
|
frame_updating = True
|
|
param.setdefault(label, "")
|
|
file = param[label] if param[label] else default
|
|
return (file, str(Path(folder_path, file)), param[label] != "")
|
|
|
|
|
|
class FlipStreamFileSelect_Checkpoints(FlipStreamFileSelect):
|
|
FOLDER_NAME = "checkpoints"
|
|
FOLDER_PATH = Path(folder_paths.get_folder_paths(FOLDER_NAME)[0]).relative_to(Path.cwd()).as_posix()
|
|
|
|
|
|
class FlipStreamFileSelect_VAE(FlipStreamFileSelect):
|
|
FOLDER_NAME = "vae"
|
|
FOLDER_PATH = Path(folder_paths.get_folder_paths(FOLDER_NAME)[0]).relative_to(Path.cwd()).as_posix()
|
|
|
|
|
|
class FlipStreamFileSelect_ControlNetModel(FlipStreamFileSelect):
|
|
FOLDER_NAME = "controlnet"
|
|
FOLDER_PATH = Path(folder_paths.get_folder_paths(FOLDER_NAME)[0]).relative_to(Path.cwd()).as_posix()
|
|
|
|
|
|
class FlipStreamFileSelect_TensorRT(FlipStreamFileSelect):
|
|
FOLDER_NAME = "tensorrt"
|
|
try:
|
|
FOLDER_PATH = Path(folder_paths.get_folder_paths(FOLDER_NAME)[0]).relative_to(Path.cwd()).as_posix()
|
|
except:
|
|
FOLDER_PATH = "_error_ tensorrt folder is not found"
|
|
|
|
|
|
class FlipStreamFileSelect_AnimateDiffModel(FlipStreamFileSelect):
|
|
FOLDER_NAME = "animatediff_models"
|
|
try:
|
|
FOLDER_PATH = Path(folder_paths.get_folder_paths(FOLDER_NAME)[0]).relative_to(Path.cwd()).as_posix()
|
|
except:
|
|
FOLDER_PATH = "_error_ animatediff_models folder is not found"
|
|
|
|
|
|
class FlipStreamFileSelect_Input(FlipStreamFileSelect):
|
|
FOLDER_NAME = "input"
|
|
FOLDER_PATH = Path(folder_paths.input_directory).relative_to(Path.cwd()).as_posix()
|
|
|
|
|
|
class FlipStreamFileSelect_Output(FlipStreamFileSelect):
|
|
FOLDER_NAME = "output"
|
|
FOLDER_PATH = Path(folder_paths.output_directory).relative_to(Path.cwd()).as_posix()
|
|
|
|
|
|
class FlipStreamPreviewBox:
|
|
@classmethod
|
|
def INPUT_TYPES(s):
|
|
return {
|
|
"required": {
|
|
"label": ("STRING", {"default": "empty"}),
|
|
"tensor": ("IMAGE",),
|
|
}
|
|
}
|
|
|
|
RETURN_TYPES = ()
|
|
OUTPUT_NODE = True
|
|
FUNCTION = "run"
|
|
CATEGORY = "FlipStreamViewer"
|
|
|
|
def run(self, label, tensor, **kwargs):
|
|
buf = np.array(tensor[0].cpu().numpy() * 255, dtype=np.uint8)
|
|
image = Image.fromarray(buf)
|
|
image.thumbnail((256, 256))
|
|
with BytesIO() as output:
|
|
iio.imwrite(output, np.array(image), format="png", extension=".png", compression=STREAM_COMPRESSION)
|
|
state[label + "PreviewBox"] = (time.time(), output.getvalue())
|
|
return ()
|
|
|
|
|
|
class FlipStreamSetUpdateAndReload:
|
|
@classmethod
|
|
def INPUT_TYPES(s):
|
|
return {
|
|
"required": {
|
|
"delay_sec": ("FLOAT", {"default": 1, "min": 0.0, "max": 30.0, "step": 0.1}),
|
|
},
|
|
"optional": {
|
|
"hook": (any,),
|
|
}
|
|
}
|
|
|
|
RETURN_TYPES = (any,)
|
|
OUTPUT_NODE = True
|
|
FUNCTION = "run"
|
|
CATEGORY = "FlipStreamViewer"
|
|
|
|
def run(self, delay_sec, hook=None):
|
|
time.sleep(delay_sec)
|
|
setstate["update_and_reload"] = True
|
|
return (hook,)
|
|
|
|
|
|
class FlipStreamSetMessage:
|
|
@classmethod
|
|
def INPUT_TYPES(s):
|
|
return {
|
|
"required": {
|
|
"message": ("STRING", {"default": "", "multiline": True}),
|
|
},
|
|
"optional": {
|
|
"hook": (any,),
|
|
}
|
|
}
|
|
|
|
RETURN_TYPES = (any,)
|
|
OUTPUT_NODE = True
|
|
FUNCTION = "run"
|
|
CATEGORY = "FlipStreamViewer"
|
|
|
|
def run(self, message, hook=None):
|
|
setstate["message"] = btoa_utf8(message)
|
|
return (hook,)
|
|
|
|
|
|
class FlipStreamSetParam:
|
|
@classmethod
|
|
def INPUT_TYPES(s):
|
|
return {
|
|
"required": {
|
|
"label": ("STRING", {"default": "empty"}),
|
|
"value": ("STRING", {"default": "", "multiline": True}),
|
|
"replace": ("BOOLEAN", {"default": False}),
|
|
"b64enc": ("BOOLEAN", {"default": False}),
|
|
},
|
|
"optional": {
|
|
"hook": (any,),
|
|
}
|
|
}
|
|
|
|
RETURN_TYPES = (any,)
|
|
OUTPUT_NODE = True
|
|
FUNCTION = "run"
|
|
CATEGORY = "FlipStreamViewer"
|
|
|
|
def run(self, label, value, replace, b64enc, hook=None):
|
|
empty = ""
|
|
if b64enc:
|
|
value = btoa_utf8(value)
|
|
empty = btoa_utf8(empty)
|
|
if replace or label not in param or param[label] == empty:
|
|
setparam[label] = value
|
|
return (hook,)
|
|
|
|
|
|
class FlipStreamGetParam:
|
|
@classmethod
|
|
def INPUT_TYPES(s):
|
|
return {
|
|
"required": {
|
|
"label": ("STRING", {"default": "empty"}),
|
|
"default": ("STRING", {"default": ""}),
|
|
"b64dec": ("BOOLEAN", {"default": False}),
|
|
},
|
|
}
|
|
|
|
RETURN_TYPES = ("STRING",)
|
|
FUNCTION = "run"
|
|
CATEGORY = "FlipStreamViewer"
|
|
|
|
@classmethod
|
|
def IS_CHANGED(cls, label, default, b64dec):
|
|
value = default
|
|
if label in param:
|
|
value = param[label]
|
|
if b64dec:
|
|
value = atob_utf8(value)
|
|
return hash((value,))
|
|
|
|
def run(self, label, default, b64dec):
|
|
global frame_updating
|
|
frame_updating = True
|
|
value = default
|
|
if label in param:
|
|
value = param[label]
|
|
if b64dec:
|
|
value = atob_utf8(value)
|
|
return (value,)
|
|
|
|
|
|
class FlipStreamGetPreviewRoi:
|
|
@classmethod
|
|
def INPUT_TYPES(cls):
|
|
return {
|
|
"required": {
|
|
"label": ("STRING", {"default": "empty"}),
|
|
"width": ("INT", {"default": 512, "min": 256, "max": 2048, "step": 32}),
|
|
"height": ("INT", {"default": 512, "min": 256, "max": 2048, "step": 32}),
|
|
"default_left": ("INT", {"default": 0}),
|
|
"default_top": ("INT", {"default": 0}),
|
|
"default_right": ("INT", {"default": 0}),
|
|
"default_bottom": ("INT", {"default": 0}),
|
|
},
|
|
}
|
|
|
|
RETURN_TYPES = ("INT", "INT", "INT", "INT", "INT", "INT")
|
|
RETURN_NAMES = ("left", "top", "right", "bottom", "inner_width", "inner_height")
|
|
FUNCTION = "run"
|
|
CATEGORY = "FlipStreamViewer"
|
|
|
|
@classmethod
|
|
def IS_CHANGED(cls, label, **kwargs):
|
|
roi_data = frozenset(param.get(label + "PreviewRoi", {}).items())
|
|
return hash(roi_data)
|
|
|
|
def run(self, label, default_left, default_top, default_right, default_bottom, width, height):
|
|
global frame_updating
|
|
frame_updating = True
|
|
roi_data = param.get(label + "PreviewRoi", {})
|
|
left = int(roi_data['sx'] * width) if 'sx' in roi_data else default_left
|
|
top = int(roi_data['sy'] * height) if 'sy' in roi_data else default_top
|
|
right = int(width - roi_data['ex'] * width) if 'ex' in roi_data else default_right
|
|
bottom = int(height - roi_data['ey'] * height) if 'ey' in roi_data else default_bottom
|
|
inner_width = width - left - right
|
|
inner_height = height - top - bottom
|
|
return (left, top, right, bottom, inner_width, inner_height)
|
|
|
|
|
|
class FlipStreamImageSize:
|
|
@classmethod
|
|
def INPUT_TYPES(s):
|
|
return {
|
|
"required": {
|
|
"tensor": ("IMAGE",),
|
|
}
|
|
}
|
|
|
|
RETURN_TYPES = ("IMAGE","INT","INT","INT")
|
|
RETURN_NAMES = ("tensor","width","height","batchsize")
|
|
FUNCTION = "run"
|
|
CATEGORY = "FlipStreamViewer"
|
|
|
|
def run(self, tensor):
|
|
(batchsize, height, width) = tensor.shape[0:3]
|
|
return (tensor, width, height, batchsize)
|
|
|
|
|
|
class FlipStreamTextReplace:
|
|
@classmethod
|
|
def INPUT_TYPES(s):
|
|
return {
|
|
"required": {
|
|
"text": ("STRING", {"default": "", "multiline": True}),
|
|
"find": ("STRING", {"default": ""}),
|
|
"replace": ("STRING", {"default": ""}),
|
|
},
|
|
"optional": {
|
|
"value": (any,),
|
|
}
|
|
}
|
|
|
|
RETURN_TYPES = ("STRING",)
|
|
FUNCTION = "run"
|
|
CATEGORY = "FlipStreamViewer"
|
|
|
|
def run(self, text, find, replace, value=None):
|
|
return (text.replace(find, replace.format(value)),)
|
|
|
|
|
|
class FlipStreamScreenGrabber:
|
|
@classmethod
|
|
def INPUT_TYPES(s):
|
|
return {
|
|
"required": {
|
|
"left": ("INT", {"default": 0, "min": 0, "step": 32}),
|
|
"top": ("INT", {"default": 0, "min": 0, "step": 32}),
|
|
"width": ("INT", {"default": 512, "min": 256, "max": 2048, "step": 32}),
|
|
"height": ("INT", {"default": 512, "min": 256, "max": 2048, "step": 32}),
|
|
"frames": ("INT", {"default": 8, "min": 1, "max": 100}),
|
|
"fps": ("INT", {"default": 8, "min": 1, "max": 30}),
|
|
"delay_sec": ("FLOAT", {"default": 3, "min": 0.0, "max": 30.0, "step": 0.1}),
|
|
"enable": ("BOOLEAN", {"default": True}),
|
|
}
|
|
}
|
|
|
|
RETURN_TYPES = ("IMAGE", "BOOLEAN")
|
|
RETURN_NAMES = ("image", "enable")
|
|
FUNCTION = "run"
|
|
CATEGORY = "FlipStreamViewer"
|
|
|
|
def __init__(self):
|
|
self.grabber_thread = None
|
|
self.flag_stop_grabber = False
|
|
self.last_args = None
|
|
self.grabbed_frames = []
|
|
|
|
def grabber(self, area, frames, fps):
|
|
with mss.mss() as sct:
|
|
while True:
|
|
self.grabbed_frames.append(sct.grab(area)) # BGRA format
|
|
self.grabbed_frames = self.grabbed_frames[-frames:]
|
|
time.sleep(1 / fps)
|
|
if self.flag_stop_grabber:
|
|
break
|
|
|
|
def start_grabber(self, area, frames, fps):
|
|
if self.grabber_thread is None or not self.grabber_thread.is_alive():
|
|
self.flag_stop_grabber = False
|
|
self.grabber_thread = threading.Thread(target=self.grabber, args=(area, frames, fps), daemon=True)
|
|
self.grabber_thread.start()
|
|
|
|
def stop_grabber(self):
|
|
if self.grabber_thread is not None and self.grabber_thread.is_alive():
|
|
self.flag_stop_grabber = True
|
|
self.grabber_thread.join()
|
|
|
|
def __del__(self):
|
|
self.stop_grabber()
|
|
|
|
def run(self, top, left, width, height, frames, fps, delay_sec, enable):
|
|
image = None
|
|
if enable:
|
|
enable = False
|
|
area = {"left": left, "top": top, "width": width, "height": height}
|
|
if self.last_args is None or self.last_args != (area, frames, fps):
|
|
self.last_args = (area, frames, fps)
|
|
self.stop_grabber()
|
|
self.start_grabber(area, frames, fps)
|
|
time.sleep(delay_sec)
|
|
buf = self.grabbed_frames[-frames:]
|
|
if len(buf) == frames:
|
|
image = torch.tensor(np.array(buf)[:, :, :, (2, 1, 0)] / 255, dtype=torch.float32)
|
|
enable = True
|
|
else:
|
|
self.stop_grabber()
|
|
return (image, enable)
|
|
|
|
|
|
class FlipStreamVideoInput:
|
|
@classmethod
|
|
def INPUT_TYPES(cls):
|
|
return {
|
|
"required": {
|
|
"path": ("STRING", {"default": ""}),
|
|
"first": ("INT", {"default": 0, "min": 0}),
|
|
"step": ("INT", {"default": 1, "min": 1}),
|
|
"frames": ("INT", {"default": 1, "min": 1}),
|
|
},
|
|
}
|
|
|
|
RETURN_TYPES = ("IMAGE", "BOOLEAN")
|
|
RETURN_NAMES = ("image", "enable")
|
|
FUNCTION = "run"
|
|
CATEGORY = "FlipStreamViewer"
|
|
|
|
def run(self, path, first, step, frames):
|
|
if not path or not Path(path).is_file():
|
|
return (torch.zeros([1, 32, 32, 3]), False)
|
|
try:
|
|
with iio.imopen(path, "r") as file:
|
|
buf = [file.read(index=i) for i in range(first, first+(frames-1)*step+1, step)]
|
|
buf = np.stack(buf).astype(np.float32) / 255
|
|
enable = buf.shape[0] == frames
|
|
image = torch.from_numpy(buf) if enable else None
|
|
return (image, enable)
|
|
except:
|
|
return (torch.zeros([1, 32, 32, 3]), False)
|
|
|
|
|
|
class FlipStreamSource:
|
|
@classmethod
|
|
def INPUT_TYPES(s):
|
|
return {
|
|
"required": {
|
|
"width": ("INT", {"default": 512, "min": 256, "max": 2048, "step": 32}),
|
|
"height": ("INT", {"default": 512, "min": 256, "max": 2048, "step": 32}),
|
|
"frames": ("INT", {"default": 8, "min": 1}),
|
|
},
|
|
"optional": {
|
|
"image": ("IMAGE",),
|
|
"vae": ("VAE",),
|
|
}
|
|
}
|
|
|
|
RETURN_TYPES = ("IMAGE", "LATENT",)
|
|
RETURN_NAMES = ("image", "latent",)
|
|
FUNCTION = "run"
|
|
CATEGORY = "FlipStreamViewer"
|
|
|
|
def run(self, width, height, frames, image=None, vae=None):
|
|
latent = None
|
|
if image is not None and not torch.any(image):
|
|
image = None
|
|
if image is not None and image.shape[3] == 4:
|
|
image = image[:,:,:,:3] * image[:,:,:,3:4]
|
|
if image is not None and image.shape[0] >= frames:
|
|
buf = image[:frames]
|
|
buf = buf.movedim(-1,1)
|
|
buf = comfy.utils.common_upscale(buf, width, height, "lanczos", "centor")
|
|
image = buf.movedim(1,-1)
|
|
if vae:
|
|
latent = {"samples": vae.encode(image)}
|
|
else:
|
|
latent = {"samples": torch.zeros([frames, 4, height // 8, width // 8], device=comfy.model_management.intermediate_device())}
|
|
else:
|
|
image = torch.zeros([frames, height, width, 3])
|
|
latent = {"samples": torch.zeros([frames, 4, height // 8, width // 8], device=comfy.model_management.intermediate_device())}
|
|
return (image, latent,)
|
|
|
|
|
|
class FlipStreamSwitch:
|
|
@classmethod
|
|
def INPUT_TYPES(s):
|
|
return {
|
|
"required": {
|
|
"value": (any,),
|
|
},
|
|
"optional": {
|
|
"value_enable": (any,),
|
|
"enable": ("BOOLEAN",),
|
|
}
|
|
}
|
|
|
|
RETURN_TYPES = (any,)
|
|
FUNCTION = "run"
|
|
CATEGORY = "FlipStreamViewer"
|
|
|
|
def run(self, value=None, value_enable=None, enable=None):
|
|
if enable:
|
|
return (value_enable,)
|
|
return (value,)
|
|
|
|
|
|
class FlipStreamSwitchImage:
|
|
@classmethod
|
|
def INPUT_TYPES(s):
|
|
return {
|
|
"required": {
|
|
"image": ("IMAGE",),
|
|
},
|
|
"optional": {
|
|
"image_enable": ("IMAGE",),
|
|
"enable": ("BOOLEAN",),
|
|
}
|
|
}
|
|
|
|
RETURN_TYPES = ("IMAGE",)
|
|
FUNCTION = "run"
|
|
CATEGORY = "FlipStreamViewer"
|
|
|
|
def run(self, image=None, image_enable=None, enable=None):
|
|
if enable:
|
|
return (image_enable,)
|
|
return (image,)
|
|
|
|
|
|
class FlipStreamSwitchLatent:
|
|
@classmethod
|
|
def INPUT_TYPES(s):
|
|
return {
|
|
"required": {
|
|
"latent": ("LATENT",),
|
|
},
|
|
"optional": {
|
|
"latent_enable": ("LATENT",),
|
|
"enable": ("BOOLEAN",),
|
|
}
|
|
}
|
|
|
|
RETURN_TYPES = ("LATENT",)
|
|
FUNCTION = "run"
|
|
CATEGORY = "FlipStreamViewer"
|
|
|
|
def run(self, latent, latent_enable=None, enable=None):
|
|
if enable:
|
|
return (latent_enable,)
|
|
return (latent,)
|
|
|
|
|
|
class FlipStreamGate:
|
|
@classmethod
|
|
def INPUT_TYPES(s):
|
|
return {
|
|
"required": {
|
|
"model": ("MODEL",),
|
|
"pos": ("CONDITIONING",),
|
|
"neg": ("CONDITIONING",),
|
|
"latent": ("LATENT",),
|
|
},
|
|
"optional": {
|
|
"a": (any,),
|
|
"b": (any,),
|
|
"c": (any,),
|
|
"d": (any,),
|
|
"e": (any,),
|
|
"f": (any,),
|
|
"g": (any,),
|
|
"h": (any,)
|
|
}
|
|
}
|
|
|
|
RETURN_TYPES = ("MODEL", "CONDITIONING", "CONDITIONING", "LATENT", any, any, any, any, any, any, any, any)
|
|
RETURN_NAMES = ("model", "pos", "neg", "latent", "a", "b", "c", "d", "e", "f", "g", "h")
|
|
FUNCTION = "run"
|
|
CATEGORY = "FlipStreamViewer"
|
|
|
|
def run(self, model, pos, neg, latent, a=None, b=None, c=None, d=None, e=None, f=None, g=None, h=None):
|
|
return (model, pos, neg, latent, a, b, c, d, e, f, g, h)
|
|
|
|
|
|
class FlipStreamRembg:
|
|
@classmethod
|
|
def INPUT_TYPES(s):
|
|
return {
|
|
"required": {
|
|
"image": ("IMAGE",),
|
|
},
|
|
}
|
|
|
|
RETURN_TYPES = ("IMAGE", "MASK")
|
|
FUNCTION = "run"
|
|
CATEGORY = "image"
|
|
|
|
def __init__(self):
|
|
if rembg is None:
|
|
raise RuntimeError("FlipStreamRembg: ComfyUI-Inspyrenet-Rembg must be installed to use this function.")
|
|
|
|
self.rembg = rembg.InspyrenetRembg()
|
|
|
|
def run(self, image):
|
|
img, mask = self.rembg.remove_background(image, "default")
|
|
return (img[..., :3] * img[..., 3:4], mask)
|
|
|
|
|
|
class FlipStreamSegMask:
|
|
@classmethod
|
|
def INPUT_TYPES(s):
|
|
return {
|
|
"required": {
|
|
"tensor": ("IMAGE",),
|
|
"target": ("STRING", {"default": "", "multiline": True}),
|
|
},
|
|
}
|
|
|
|
RETURN_TYPES = ("IMAGE", "MASK",)
|
|
RETURN_NAMES =("preview", "mask",)
|
|
FUNCTION = "run"
|
|
CATEGORY = "FlipStreamViewer"
|
|
|
|
model = None
|
|
processor = None
|
|
|
|
def run(self, tensor, target):
|
|
if florence2 is None:
|
|
raise RuntimeError("FlipStreamSegMask: ComfyUI-Florence2 must be installed to use this function.")
|
|
|
|
# Create mask
|
|
_, h, w = tensor.shape[0:3]
|
|
mask_image = Image.new('RGB', (w, h), 'black')
|
|
|
|
# Skip if empty target
|
|
if target.strip() == "":
|
|
mask_tensor = torch.from_numpy(np.array(mask_image).astype(np.float32) / 255.0).unsqueeze(0)
|
|
return (mask_tensor, mask_tensor[:,:,:,0])
|
|
|
|
# Download model if it not found
|
|
model_id = 'microsoft/Florence-2-large'
|
|
if FlipStreamSegMask.model is None:
|
|
model_dir = Path(folder_paths.models_dir, "LLM")
|
|
model_dir.mkdir(exist_ok=True)
|
|
model_name = model_id.rsplit('/', 1)[-1]
|
|
model_path = Path(model_dir, model_name)
|
|
|
|
if not model_path.exists():
|
|
print(f"Downloading Florence2 model to: {model_path}")
|
|
from huggingface_hub import snapshot_download
|
|
snapshot_download(repo_id=model_id, local_dir=str(model_path), local_dir_use_symlinks=False)
|
|
|
|
# Load model
|
|
if FlipStreamSegMask.model is None:
|
|
FlipStreamSegMask.model = transformers.AutoModelForCausalLM.from_pretrained(
|
|
model_id,
|
|
trust_remote_code=True,
|
|
attn_implementation='sdpa',
|
|
device_map=comfy.model_management.get_torch_device(),
|
|
torch_dtype=torch.bfloat16
|
|
)
|
|
FlipStreamSegMask.processor = transformers.AutoProcessor.from_pretrained(model_id, trust_remote_code=True)
|
|
model = FlipStreamSegMask.model
|
|
processor = FlipStreamSegMask.processor
|
|
model.to(comfy.model_management.get_torch_device())
|
|
|
|
# Process prompt for each target
|
|
task_prompt = '<REFERRING_EXPRESSION_SEGMENTATION>'
|
|
image = Image.fromarray(np.clip(255. * tensor[0,:,:,:].cpu().numpy().squeeze(), 0, 255).astype(np.uint8))
|
|
mask_draw = ImageDraw.Draw(mask_image)
|
|
for item in target.split(','):
|
|
prompt = task_prompt + item
|
|
inputs = processor(text=prompt, images=image, return_tensors="pt", do_rescale=False).to('cuda', torch.bfloat16)
|
|
generated_ids = model.generate(
|
|
input_ids=inputs["input_ids"].cuda(),
|
|
pixel_values=inputs["pixel_values"].cuda(),
|
|
max_new_tokens=1024,
|
|
early_stopping=False,
|
|
do_sample=False,
|
|
num_beams=1,
|
|
)
|
|
generated_text = processor.batch_decode(generated_ids, skip_special_tokens=False)[0]
|
|
parsed_answer = processor.post_process_generation(generated_text, task=task_prompt, image_size=(w, h))
|
|
|
|
# Draw mask
|
|
predictions = parsed_answer[task_prompt]
|
|
for polygons in predictions['polygons']:
|
|
for p in polygons:
|
|
p = np.array(p).reshape(-1, 2)
|
|
p = np.clip(p, [0, 0], [w - 1, h - 1])
|
|
if len(p) < 3:
|
|
print('Invalid polygon:', p)
|
|
continue
|
|
|
|
p = p.reshape(-1).tolist()
|
|
mask_draw.polygon(p, outline="white", fill="white")
|
|
|
|
# Offload model
|
|
model.to(torch.device("cpu"))
|
|
|
|
mask_tensor = torch.from_numpy(np.array(mask_image).astype(np.float32) / 255.0).unsqueeze(0)
|
|
return (mask_tensor, mask_tensor[:,:,:,0])
|
|
|
|
|
|
class FlipStreamChat:
|
|
@classmethod
|
|
def INPUT_TYPES(cls):
|
|
return {
|
|
"required": {
|
|
"model_file": ([path.name for path in Path(folder_paths.models_dir, "LLM").glob("*.gguf")],),
|
|
"n_ctx": ("INT", {"default": 2048}),
|
|
"n_gpu_layers": ("INT", {"default": -1}),
|
|
"unload_other_models": ("BOOLEAN", {"default": False}),
|
|
"close_after_use": ("BOOLEAN", {"default": False}),
|
|
"system": ("STRING", {"default": "", "multiline": True}),
|
|
"user": ("STRING", {"default": "", "multiline": True}),
|
|
"instant": ("BOOLEAN", {"default": False}),
|
|
"max_history": ("INT", {"default": 10, "min": -1}),
|
|
"stop": ("STRING", {"default": "[,<"}),
|
|
"temperature": ("FLOAT", {"default": 0.2, "min": 0}),
|
|
"top_p": ("FLOAT", {"default": 0.95, "min": 0}),
|
|
"seed": ("INT", {"default": -1}),
|
|
"max_tokens": ("INT", {"default": 128, "min": 0}),
|
|
"presence_penalty": ("FLOAT", {"default": 0, "min": 0}),
|
|
"frequency_penalty": ("FLOAT", {"default": 0, "min": 0}),
|
|
"repeat_penalty": ("FLOAT", {"default": 1.0, "min": 0})
|
|
},
|
|
"optional": {
|
|
"chat_model": ("CHAT_MODEL",),
|
|
"messages": ("MESSAGES",)
|
|
}
|
|
}
|
|
|
|
RETURN_TYPES = ("CHAT_MODEL", "STRING", "MESSAGES")
|
|
RETURN_NAMES =("chat_model", "response", "messages")
|
|
FUNCTION = "run"
|
|
CATEGORY = "FlipStreamViewer"
|
|
|
|
def __init__(self):
|
|
self.model = None
|
|
self.messages = []
|
|
self.system = None
|
|
|
|
def load_model(self, model_file, n_ctx, n_gpu_layers):
|
|
h = hash((model_file, n_ctx, n_gpu_layers))
|
|
if self.model is None or self.model._FlipStreamChat_is_closed or self.model._FlipStreamChat_last_hash != h:
|
|
model_path = Path(folder_paths.models_dir, "LLM", model_file)
|
|
if not model_path.exists():
|
|
raise RuntimeError(f"FlipStreamChat: {model_path} not found.")
|
|
if Llama is None:
|
|
raise RuntimeError("FlipStreamChat: llama-cpp-python required.")
|
|
self.model = Llama(str(model_path), chat_format="llama-2", n_ctx=n_ctx, n_gpu_layers=n_gpu_layers, verbose=False)
|
|
self.model._FlipStreamChat_is_closed = False
|
|
self.model._FlipStreamChat_last_hash = h
|
|
|
|
def close_model(self):
|
|
self.model.close()
|
|
self.model._FlipStreamChat_is_closed = True
|
|
|
|
def chat(self, system, user, stop, messages, **kwargs):
|
|
if system != self.system:
|
|
self.system = system
|
|
messages.clear()
|
|
if system and len(messages) == 0:
|
|
messages.append(dict(role="system", content=system))
|
|
if system and messages[0]["role"] != "system":
|
|
messages[0] = dict(role="system", content=system)
|
|
if user:
|
|
messages.append(dict(role="user", content=user))
|
|
return self.model.create_chat_completion(messages, stop=list(filter(str.strip, stop.split(","))), **kwargs)["choices"][0]["message"]
|
|
|
|
def run(self, model_file, n_ctx, n_gpu_layers, unload_other_models, close_after_use, system, user, instant, max_history, stop, chat_model=None, messages=None, **kwargs):
|
|
if unload_other_models:
|
|
comfy.model_management.unload_all_models()
|
|
comfy.model_management.soft_empty_cache(True)
|
|
try:
|
|
comfy.gc.collect()
|
|
torch.cuda.empty_cache()
|
|
torch.cuda.ipc_collect()
|
|
except:
|
|
pass
|
|
if chat_model is not None:
|
|
self.model = chat_model
|
|
if messages is None:
|
|
messages = self.messages
|
|
if max_history == 0:
|
|
messages.clear()
|
|
elif max_history >= 1:
|
|
messages[:] = messages[-max_history:]
|
|
self.load_model(model_file, n_ctx, n_gpu_layers)
|
|
if instant:
|
|
res = self.chat(system, user, stop, messages.copy(), **kwargs)
|
|
output = res["content"]
|
|
else:
|
|
res = self.chat(system, user, stop, messages, **kwargs)
|
|
output = res["content"]
|
|
if res["role"] == "assistant":
|
|
messages.append(dict(role="assistant", content=output))
|
|
self.messages = messages
|
|
if close_after_use:
|
|
self.close_model()
|
|
return (self.model, output, messages)
|
|
|
|
|
|
class FlipStreamBatchPrompt:
|
|
@classmethod
|
|
def INPUT_TYPES(s):
|
|
return {
|
|
"required": {
|
|
"prompt": ("STRING", {"default": "", "multiline": True}),
|
|
"clip": ("CLIP",),
|
|
"frames": ("INT",),
|
|
}
|
|
}
|
|
|
|
RETURN_TYPES = ("CONDITIONING",)
|
|
FUNCTION = "run"
|
|
CATEGORY = "FlipStreamViewer"
|
|
|
|
def run(self, prompt, clip, frames):
|
|
cond_buf = []
|
|
pooled_buf = []
|
|
|
|
buf = prompt.split("----")
|
|
prompt = buf[0].strip()
|
|
batchPrompt = buf[1].strip() if len(buf) > 1 else ""
|
|
appPrompt = buf[2].strip() if len(buf) > 2 else ""
|
|
count = len(batchPrompt.split("\n"))
|
|
batchPrompt = ",\n".join([f'"{int(frames * n / count)}":"{item.lstrip("-").strip()}"' for n, item in enumerate(batchPrompt.split("\n"))])
|
|
|
|
tokens = clip.tokenize(prompt)
|
|
cond, pooled = clip.encode_from_tokens(tokens, return_pooled=True)
|
|
s = json.loads("{" + batchPrompt + "}")
|
|
for i in range(frames):
|
|
if str(i) in s:
|
|
tokens = clip.tokenize(" ".join([prompt, s[str(i)], appPrompt]).strip())
|
|
cond, pooled = clip.encode_from_tokens(tokens, return_pooled=True)
|
|
cond_buf.append(cond)
|
|
pooled_buf.append(pooled)
|
|
|
|
max_length = max([t.size(1) for t in cond_buf])
|
|
cond_buf = [
|
|
NNF.pad(t, (0, 0, 0, max_length - t.size(1))) if t.size(1) < max_length else t[:, :max_length, :]
|
|
for t in cond_buf
|
|
]
|
|
return ([[torch.cat(cond_buf, dim=0), {"pooled_output":torch.cat(pooled_buf, dim=0)}]],)
|
|
|
|
|
|
class FlipStreamFilmVfi:
|
|
@classmethod
|
|
def INPUT_TYPES(s):
|
|
return {
|
|
"required": {
|
|
"frames": ("IMAGE",),
|
|
"multiplier": ("INT", {"default": 1, "min": 1, "max": 16}),
|
|
"clear_cache_after_n_frames": ("INT", {"default": 10, "min": 1, "max": 1000}),
|
|
},
|
|
}
|
|
|
|
RETURN_TYPES = ("IMAGE",)
|
|
FUNCTION = "run"
|
|
CATEGORY = "FlipStreamViewer"
|
|
|
|
model = None
|
|
|
|
def run(self, frames, multiplier, clear_cache_after_n_frames):
|
|
if frames.shape[0] < 2 or multiplier < 2:
|
|
return (frames,)
|
|
|
|
if film is None:
|
|
raise RuntimeError("FlipStreamFilmVfi: ComfyUI-Frame-Interpolation must be installed to use this function.")
|
|
|
|
if FlipStreamFilmVfi.model is None:
|
|
model_path = film.load_file_from_github_release("film", "film_net_fp32.pt")
|
|
model = torch.jit.load(model_path, map_location="cpu")
|
|
model.eval()
|
|
FlipStreamFilmVfi.model = model
|
|
model = FlipStreamFilmVfi.model
|
|
model = model.to(comfy.model_management.get_torch_device())
|
|
dtype = torch.float32
|
|
|
|
frames = film.preprocess_frames(frames)
|
|
number_of_frames_processed_since_last_cleared_cuda_cache = 0
|
|
output_frames = []
|
|
|
|
for frame_itr in range(len(frames) - 1):
|
|
frame_0 = frames[frame_itr:frame_itr+1].to(comfy.model_management.get_torch_device()).float()
|
|
frame_1 = frames[frame_itr+1:frame_itr+2].to(comfy.model_management.get_torch_device()).float()
|
|
relust = film.inference(model, frame_0, frame_1, multiplier - 1)
|
|
output_frames.extend([frame.detach().cpu().to(dtype=dtype) for frame in relust[:-1]])
|
|
|
|
number_of_frames_processed_since_last_cleared_cuda_cache += 1
|
|
if number_of_frames_processed_since_last_cleared_cuda_cache >= clear_cache_after_n_frames:
|
|
film.soft_empty_cache()
|
|
number_of_frames_processed_since_last_cleared_cuda_cache = 0
|
|
|
|
output_frames.append(frames[-1:].to(dtype=dtype))
|
|
output_frames = [frame.cpu() for frame in output_frames]
|
|
out = torch.cat(output_frames, dim=0)
|
|
film.soft_empty_cache()
|
|
model.to(torch.device("cpu"))
|
|
return (film.postprocess_frames(out),)
|
|
|
|
|
|
class FlipStreamViewer:
|
|
@classmethod
|
|
def INPUT_TYPES(s):
|
|
return {
|
|
"required": {
|
|
"tensor": ("IMAGE",),
|
|
"allowip": ("STRING", {"default": ""}),
|
|
"wd14exc": ("STRING", {"default": ""}),
|
|
"idle": ("FLOAT", {"default": 1.0, "min": 0.0}),
|
|
"fps": ("INT", {"default": 8, "min": 1, "max": 30}),
|
|
"loramode": ("STRING", {"default": ""}),
|
|
},
|
|
}
|
|
|
|
@classmethod
|
|
def IS_CHANGED(cls, allowip, wd14exc, idle, loramode, **kwargs):
|
|
global allowed_ips
|
|
global exclude_tags
|
|
allowed_ips = ["127.0.0.1"] + list(map(str.strip, allowip.split(",")))
|
|
exclude_tags = wd14exc
|
|
state["loraMode"] = loramode
|
|
time.sleep(idle)
|
|
return None
|
|
|
|
RETURN_TYPES = ()
|
|
OUTPUT_NODE = True
|
|
FUNCTION = "run"
|
|
CATEGORY = "FlipStreamViewer"
|
|
|
|
def run(self, tensor, fps, **kwargs):
|
|
global frame_updating
|
|
global frame_buffer
|
|
global frame_mtime
|
|
buf = (tensor.detach().cpu().numpy() * 255).astype(np.uint8)
|
|
buf = np.concatenate([buf, np.flip(buf, axis=0)])
|
|
with BytesIO() as output:
|
|
iio.imwrite(output, buf, format='png', extension=".apng", compression=STREAM_COMPRESSION, fps=fps)
|
|
frame_buffer = output.getvalue()
|
|
frame_mtime = time.time()
|
|
frame_updating = False
|
|
return ()
|
|
|
|
NODE_CLASS_MAPPINGS = {
|
|
"FlipStreamSection": FlipStreamSection,
|
|
"FlipStreamSlider": FlipStreamSlider,
|
|
"FlipStreamTextBox": FlipStreamTextBox,
|
|
"FlipStreamInputBox": FlipStreamInputBox,
|
|
"FlipStreamSelectBox_Samplers": FlipStreamSelectBox_Samplers,
|
|
"FlipStreamSelectBox_Scheduler": FlipStreamSelectBox_Scheduler,
|
|
"FlipStreamFileSelect_Checkpoints": FlipStreamFileSelect_Checkpoints,
|
|
"FlipStreamFileSelect_VAE": FlipStreamFileSelect_VAE,
|
|
"FlipStreamFileSelect_ControlNetModel": FlipStreamFileSelect_ControlNetModel,
|
|
"FlipStreamFileSelect_TensorRT": FlipStreamFileSelect_TensorRT,
|
|
"FlipStreamFileSelect_AnimateDiffModel": FlipStreamFileSelect_AnimateDiffModel,
|
|
"FlipStreamFileSelect_Input": FlipStreamFileSelect_Input,
|
|
"FlipStreamFileSelect_Output": FlipStreamFileSelect_Output,
|
|
"FlipStreamPreviewBox": FlipStreamPreviewBox,
|
|
"FlipStreamSetUpdateAndReload": FlipStreamSetUpdateAndReload,
|
|
"FlipStreamSetMessage": FlipStreamSetMessage,
|
|
"FlipStreamSetParam": FlipStreamSetParam,
|
|
"FlipStreamGetParam": FlipStreamGetParam,
|
|
"FlipStreamGetPreviewRoi": FlipStreamGetPreviewRoi,
|
|
"FlipStreamImageSize": FlipStreamImageSize,
|
|
"FlipStreamTextReplace": FlipStreamTextReplace,
|
|
"FlipStreamScreenGrabber": FlipStreamScreenGrabber,
|
|
"FlipStreamVideoInput": FlipStreamVideoInput,
|
|
"FlipStreamSource": FlipStreamSource,
|
|
"FlipStreamSwitch": FlipStreamSwitch,
|
|
"FlipStreamSwitchImage": FlipStreamSwitchImage,
|
|
"FlipStreamSwitchLatent": FlipStreamSwitchLatent,
|
|
"FlipStreamGate": FlipStreamGate,
|
|
"FlipStreamRembg": FlipStreamRembg,
|
|
"FlipStreamSegMask": FlipStreamSegMask,
|
|
"FlipStreamChat": FlipStreamChat,
|
|
"FlipStreamBatchPrompt": FlipStreamBatchPrompt,
|
|
"FlipStreamFilmVfi": FlipStreamFilmVfi,
|
|
"FlipStreamViewer": FlipStreamViewer,
|
|
}
|
|
|
|
NODE_DISPLAY_NAME_MAPPINGS = {
|
|
"FlipStreamSection": "FlipStreamSection",
|
|
"FlipStreamSlider": "FlipStreamSlider",
|
|
"FlipStreamTextBox": "FlipStreamTextBox",
|
|
"FlipStreamInputBox": "FlipStreamInputBox",
|
|
"FlipStreamSelectBox_Samplers": "FlipStreamSelectBox_Samplers",
|
|
"FlipStreamSelectBox_Scheduler": "FlipStreamSelectBox_Scheduler",
|
|
"FlipStreamFileSelect_Checkpoints": "FlipStreamFileSelect_Checkpoints",
|
|
"FlipStreamFileSelect_VAE": "FlipStreamFileSelect_VAE",
|
|
"FlipStreamFileSelect_ControlNetModel": "FlipStreamFileSelect_ControlNetModel",
|
|
"FlipStreamFileSelect_TensorRT": "FlipStreamFileSelect_TensorRT",
|
|
"FlipStreamFileSelect_AnimateDiffModel": "FlipStreamFileSelect_AnimateDiffModel",
|
|
"FlipStreamFileSelect_Input": "FlipStreamFileSelect_Input",
|
|
"FlipStreamFileSelect_Output": "FlipStreamFileSelect_Output",
|
|
"FlipStreamPreviewBox": "FlipStreamPreviewBox",
|
|
"FlipStreamSetUpdateAndReload": "FlipStreamSetUpdateAndReload",
|
|
"FlipStreamSetMessage": "FlipStreamSetMessage",
|
|
"FlipStreamSetParam": "FlipStreamSetParam",
|
|
"FlipStreamGetParam": "FlipStreamGetParam",
|
|
"FlipStreamGetPreviewRoi": "FlipStreamGetPreviewRoi",
|
|
"FlipStreamImageSize": "FlipStreamImageSize",
|
|
"FlipStreamTextReplace": "FlipStreamTextReplace",
|
|
"FlipStreamScreenGrabber": "FlipStreamScreenGrabber",
|
|
"FlipStreamVideoInput": "FlipStreamVideoInput",
|
|
"FlipStreamSource": "FlipStreamSource",
|
|
"FlipStreamSwitch": "FlipStreamSwitch",
|
|
"FlipStreamSwitchImage": "FlipStreamSwitchImage",
|
|
"FlipStreamSwitchLatent": "FlipStreamSwitchLatent",
|
|
"FlipStreamGate": "FlipStreamGate",
|
|
"FlipStreamRembg": "FlipStreamRembg",
|
|
"FlipStreamSegMask": "FlipStreamSegMask",
|
|
"FlipStreamChat": "FlipStreamChat",
|
|
"FlipStreamBatchPrompt": "FlipStreamBatchPrompt",
|
|
"FlipStreamFilmVfi": "FlipStreamFilmVfi",
|
|
"FlipStreamViewer": "FlipStreamViewer",
|
|
}
|