diff --git a/comfy/taesd/taesd.py b/comfy/taesd/taesd.py new file mode 100644 index 00000000..e6406745 --- /dev/null +++ b/comfy/taesd/taesd.py @@ -0,0 +1,65 @@ +#!/usr/bin/env python3 +""" +Tiny AutoEncoder for Stable Diffusion +(DNN for encoding / decoding SD's latent space) +""" +import torch +import torch.nn as nn + +def conv(n_in, n_out, **kwargs): + return nn.Conv2d(n_in, n_out, 3, padding=1, **kwargs) + +class Clamp(nn.Module): + def forward(self, x): + return torch.tanh(x / 3) * 3 + +class Block(nn.Module): + def __init__(self, n_in, n_out): + super().__init__() + self.conv = nn.Sequential(conv(n_in, n_out), nn.ReLU(), conv(n_out, n_out), nn.ReLU(), conv(n_out, n_out)) + self.skip = nn.Conv2d(n_in, n_out, 1, bias=False) if n_in != n_out else nn.Identity() + self.fuse = nn.ReLU() + def forward(self, x): + return self.fuse(self.conv(x) + self.skip(x)) + +def Encoder(): + return nn.Sequential( + conv(3, 64), Block(64, 64), + conv(64, 64, stride=2, bias=False), Block(64, 64), Block(64, 64), Block(64, 64), + conv(64, 64, stride=2, bias=False), Block(64, 64), Block(64, 64), Block(64, 64), + conv(64, 64, stride=2, bias=False), Block(64, 64), Block(64, 64), Block(64, 64), + conv(64, 4), + ) + +def Decoder(): + return nn.Sequential( + Clamp(), conv(4, 64), nn.ReLU(), + Block(64, 64), Block(64, 64), Block(64, 64), nn.Upsample(scale_factor=2), conv(64, 64, bias=False), + Block(64, 64), Block(64, 64), Block(64, 64), nn.Upsample(scale_factor=2), conv(64, 64, bias=False), + Block(64, 64), Block(64, 64), Block(64, 64), nn.Upsample(scale_factor=2), conv(64, 64, bias=False), + Block(64, 64), conv(64, 3), + ) + +class TAESD(nn.Module): + latent_magnitude = 3 + latent_shift = 0.5 + + def __init__(self, encoder_path="taesd_encoder.pth", decoder_path="taesd_decoder.pth"): + """Initialize pretrained TAESD on the given device from the given checkpoints.""" + super().__init__() + self.encoder = Encoder() + self.decoder = Decoder() + if encoder_path is not None: + self.encoder.load_state_dict(torch.load(encoder_path, map_location="cpu")) + if decoder_path is not None: + self.decoder.load_state_dict(torch.load(decoder_path, map_location="cpu")) + + @staticmethod + def scale_latents(x): + """raw latents -> [0, 1]""" + return x.div(2 * TAESD.latent_magnitude).add(TAESD.latent_shift).clamp(0, 1) + + @staticmethod + def unscale_latents(x): + """[0, 1] -> raw latents""" + return x.sub(TAESD.latent_shift).mul(2 * TAESD.latent_magnitude) diff --git a/comfy/utils.py b/comfy/utils.py index 4e84e870..291c62e4 100644 --- a/comfy/utils.py +++ b/comfy/utils.py @@ -197,14 +197,14 @@ class ProgressBar: self.current = 0 self.hook = PROGRESS_BAR_HOOK - def update_absolute(self, value, total=None): + def update_absolute(self, value, total=None, preview=None): if total is not None: self.total = total if value > self.total: value = self.total self.current = value if self.hook is not None: - self.hook(self.current, self.total) + self.hook(self.current, self.total, preview) def update(self, value): self.update_absolute(self.current + value) diff --git a/main.py b/main.py index 50d3b9a6..908ff7af 100644 --- a/main.py +++ b/main.py @@ -26,6 +26,7 @@ import yaml import execution import folder_paths import server +from server import BinaryEventTypes from nodes import init_custom_nodes @@ -40,8 +41,11 @@ async def run(server, address='', port=8188, verbose=True, call_on_start=None): await asyncio.gather(server.start(address, port, verbose, call_on_start), server.publish_loop()) def hijack_progress(server): - def hook(value, total): + def hook(value, total, preview_bytes_jpeg): server.send_sync("progress", { "value": value, "max": total}, server.client_id) + if preview_bytes_jpeg is not None: + server.send_sync(BinaryEventTypes.PREVIEW_IMAGE, preview_bytes_jpeg, server.client_id) + pass comfy.utils.set_progress_bar_global_hook(hook) def cleanup_temp(): diff --git a/nodes.py b/nodes.py index 90444a92..a80f8193 100644 --- a/nodes.py +++ b/nodes.py @@ -7,6 +7,8 @@ import hashlib import traceback import math import time +import struct +from io import BytesIO from PIL import Image, ImageOps from PIL.PngImagePlugin import PngInfo @@ -22,6 +24,7 @@ import comfy.samplers import comfy.sample import comfy.sd import comfy.utils +from comfy.taesd.taesd import TAESD import comfy.clip_vision @@ -38,6 +41,7 @@ def interrupt_processing(value=True): comfy.model_management.interrupt_current_processing(value) MAX_RESOLUTION=8192 +MAX_PREVIEW_RESOLUTION = 512 class CLIPTextEncode: @classmethod @@ -171,6 +175,21 @@ class VAEDecodeTiled: def decode(self, vae, samples): return (vae.decode_tiled(samples["samples"]), ) +class TAESDDecode: + @classmethod + def INPUT_TYPES(s): + return {"required": { "samples": ("LATENT", ), "taesd": ("TAESD", )}} + RETURN_TYPES = ("IMAGE",) + FUNCTION = "decode" + + CATEGORY = "latent" + + def decode(self, taesd, samples): + device = comfy.model_management.get_torch_device() + # [B, C, H, W] -> [B, H, W, C] + pixels = taesd.decoder(samples["samples"].to(device)).permute(0, 2, 3, 1).detach().clamp(0, 1) + return (pixels, ) + class VAEEncode: @classmethod def INPUT_TYPES(s): @@ -248,6 +267,21 @@ class VAEEncodeForInpaint: return ({"samples":t, "noise_mask": (mask_erosion[:,:,:x,:y].round())}, ) +class TAESDEncode: + @classmethod + def INPUT_TYPES(s): + return {"required": { "pixels": ("IMAGE", ), "taesd": ("TAESD", )}} + RETURN_TYPES = ("LATENT",) + FUNCTION = "encode" + + CATEGORY = "latent" + + def encode(self, taesd, pixels): + device = comfy.model_management.get_torch_device() + # [B, H, W, C] -> [B, C, H, W] + samples = taesd.encoder(pixels.permute(0, 3, 1, 2).to(device)).to(device) + return ({"samples": samples}, ) + class SaveLatent: def __init__(self): @@ -464,6 +498,26 @@ class VAELoader: vae = comfy.sd.VAE(ckpt_path=vae_path) return (vae,) +class TAESDLoader: + @classmethod + def INPUT_TYPES(s): + model_list = folder_paths.get_filename_list("taesd") + return {"required": { + "encoder_name": (model_list, { "default": "taesd_encoder.pth" }), + "decoder_name": (model_list, { "default": "taesd_decoder.pth" }) + }} + RETURN_TYPES = ("TAESD",) + FUNCTION = "load_taesd" + + CATEGORY = "loaders" + + def load_taesd(self, encoder_name, decoder_name): + device = comfy.model_management.get_torch_device() + encoder_path = folder_paths.get_full_path("taesd", encoder_name) + decoder_path = folder_paths.get_full_path("taesd", decoder_name) + taesd = TAESD(encoder_path, decoder_path).to(device) + return (taesd,) + class ControlNetLoader: @classmethod def INPUT_TYPES(s): @@ -931,7 +985,37 @@ class SetLatentNoiseMask: s["noise_mask"] = mask.reshape((-1, 1, mask.shape[-2], mask.shape[-1])) return (s,) -def common_ksampler(model, seed, steps, cfg, sampler_name, scheduler, positive, negative, latent, denoise=1.0, disable_noise=False, start_step=None, last_step=None, force_full_denoise=False): + +def decode_latent_to_preview_image(taesd, device, preview_format, x0): + x_sample = taesd.decoder(x0.to(device))[0].detach() + x_sample = taesd.unscale_latents(x_sample) # returns value in [-2, 2] + x_sample = x_sample * 0.5 + + x_sample = torch.clamp((x_sample + 1.0) / 2.0, min=0.0, max=1.0) + x_sample = 255. * np.moveaxis(x_sample.cpu().numpy(), 0, 2) + x_sample = x_sample.astype(np.uint8) + + preview_image = Image.fromarray(x_sample) + + if preview_image.size[0] > MAX_PREVIEW_RESOLUTION or preview_image.size[1] > MAX_PREVIEW_RESOLUTION: + preview_image.thumbnail((MAX_PREVIEW_RESOLUTION, MAX_PREVIEW_RESOLUTION), Image.ANTIALIAS) + + preview_type = 1 + if preview_format == "JPEG": + preview_type = 1 + elif preview_format == "PNG": + preview_type = 2 + + bytesIO = BytesIO() + header = struct.pack(">I", preview_type) + bytesIO.write(header) + preview_image.save(bytesIO, format=preview_format) + preview_bytes = bytesIO.getvalue() + + return preview_bytes + + +def common_ksampler(model, seed, steps, cfg, sampler_name, scheduler, positive, negative, latent, denoise=1.0, disable_noise=False, start_step=None, last_step=None, force_full_denoise=False, taesd=None): device = comfy.model_management.get_torch_device() latent_image = latent["samples"] @@ -945,9 +1029,16 @@ def common_ksampler(model, seed, steps, cfg, sampler_name, scheduler, positive, if "noise_mask" in latent: noise_mask = latent["noise_mask"] + preview_format = "JPEG" + if preview_format not in ["JPEG", "PNG"]: + preview_format = "JPEG" + pbar = comfy.utils.ProgressBar(steps) def callback(step, x0, x, total_steps): - pbar.update_absolute(step + 1, total_steps) + preview_bytes = None + if taesd: + preview_bytes = decode_latent_to_preview_image(taesd, device, preview_format, x0) + pbar.update_absolute(step + 1, total_steps, preview_bytes) samples = comfy.sample.sample(model, noise, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=denoise, disable_noise=disable_noise, start_step=start_step, last_step=last_step, @@ -970,15 +1061,18 @@ class KSampler: "negative": ("CONDITIONING", ), "latent_image": ("LATENT", ), "denoise": ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.0, "step": 0.01}), - }} + }, + "optional": { + "taesd": ("TAESD",) + }} RETURN_TYPES = ("LATENT",) FUNCTION = "sample" CATEGORY = "sampling" - def sample(self, model, seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=1.0): - return common_ksampler(model, seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=denoise) + def sample(self, model, seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=1.0, taesd=None): + return common_ksampler(model, seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=denoise, taesd=taesd) class KSamplerAdvanced: @classmethod @@ -997,21 +1091,24 @@ class KSamplerAdvanced: "start_at_step": ("INT", {"default": 0, "min": 0, "max": 10000}), "end_at_step": ("INT", {"default": 10000, "min": 0, "max": 10000}), "return_with_leftover_noise": (["disable", "enable"], ), - }} + }, + "optional": { + "taesd": ("TAESD",) + }} RETURN_TYPES = ("LATENT",) FUNCTION = "sample" CATEGORY = "sampling" - def sample(self, model, add_noise, noise_seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, start_at_step, end_at_step, return_with_leftover_noise, denoise=1.0): + def sample(self, model, add_noise, noise_seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, start_at_step, end_at_step, return_with_leftover_noise, denoise=1.0, taesd=None): force_full_denoise = True if return_with_leftover_noise == "enable": force_full_denoise = False disable_noise = False if add_noise == "disable": disable_noise = True - return common_ksampler(model, noise_seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=denoise, disable_noise=disable_noise, start_step=start_at_step, last_step=end_at_step, force_full_denoise=force_full_denoise) + return common_ksampler(model, noise_seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=denoise, disable_noise=disable_noise, start_step=start_at_step, last_step=end_at_step, force_full_denoise=force_full_denoise, taesd=taesd) class SaveImage: def __init__(self): @@ -1270,6 +1367,9 @@ NODE_CLASS_MAPPINGS = { "VAEEncode": VAEEncode, "VAEEncodeForInpaint": VAEEncodeForInpaint, "VAELoader": VAELoader, + "TAESDDecode": TAESDDecode, + "TAESDEncode": TAESDEncode, + "TAESDLoader": TAESDLoader, "EmptyLatentImage": EmptyLatentImage, "LatentUpscale": LatentUpscale, "LatentUpscaleBy": LatentUpscaleBy, @@ -1324,6 +1424,7 @@ NODE_DISPLAY_NAME_MAPPINGS = { "CheckpointLoader": "Load Checkpoint (With Config)", "CheckpointLoaderSimple": "Load Checkpoint", "VAELoader": "Load VAE", + "TAESDLoader": "Load TAESD", "LoraLoader": "Load LoRA", "CLIPLoader": "Load CLIP", "ControlNetLoader": "Load ControlNet Model", @@ -1346,6 +1447,8 @@ NODE_DISPLAY_NAME_MAPPINGS = { "SetLatentNoiseMask": "Set Latent Noise Mask", "VAEDecode": "VAE Decode", "VAEEncode": "VAE Encode", + "TAESDDecode": "TAESD Decode", + "TAESDEncode": "TAESD Encode", "LatentRotate": "Rotate Latent", "LatentFlip": "Flip Latent", "LatentCrop": "Crop Latent", diff --git a/server.py b/server.py index c0b4729d..174d38af 100644 --- a/server.py +++ b/server.py @@ -7,6 +7,7 @@ import execution import uuid import json import glob +import struct from PIL import Image from io import BytesIO @@ -25,6 +26,11 @@ from comfy.cli_args import args import comfy.utils import comfy.model_management + +class BinaryEventTypes: + PREVIEW_IMAGE = 1 + + @web.middleware async def cache_control(request: web.Request, handler): response: web.Response = await handler(request) @@ -457,16 +463,37 @@ class PromptServer(): return prompt_info async def send(self, event, data, sid=None): + if isinstance(data, (bytes, bytearray)): + await self.send_bytes(event, data, sid) + else: + await self.send_json(event, data, sid) + + def encode_bytes(self, event, data): + if not isinstance(event, int): + raise RuntimeError(f"Binary event types must be integers, got {event}") + + packed = struct.pack(">I", event) + message = bytearray(packed) + message.extend(data) + return message + + async def send_bytes(self, event, data, sid=None): + message = self.encode_bytes(event, data) + + if sid is None: + for ws in self.sockets.values(): + await ws.send_bytes(message) + elif sid in self.sockets: + await self.sockets[sid].send_bytes(message) + + async def send_json(self, event, data, sid=None): message = {"type": event, "data": data} - - if isinstance(message, str) == False: - message = json.dumps(message) if sid is None: for ws in self.sockets.values(): - await ws.send_str(message) + await ws.send_json(message) elif sid in self.sockets: - await self.sockets[sid].send_str(message) + await self.sockets[sid].send_json(message) def send_sync(self, event, data, sid=None): self.loop.call_soon_threadsafe( diff --git a/web/extensions/core/colorPalette.js b/web/extensions/core/colorPalette.js index bfcd847a..84c2a3d1 100644 --- a/web/extensions/core/colorPalette.js +++ b/web/extensions/core/colorPalette.js @@ -21,6 +21,7 @@ const colorPalettes = { "MODEL": "#B39DDB", // light lavender-purple "STYLE_MODEL": "#C2FFAE", // light green-yellow "VAE": "#FF6E6E", // bright red + "TAESD": "#DCC274", // cheesecake }, "litegraph_base": { "NODE_TITLE_COLOR": "#999", diff --git a/web/scripts/api.js b/web/scripts/api.js index 378165b3..780c74b3 100644 --- a/web/scripts/api.js +++ b/web/scripts/api.js @@ -42,6 +42,7 @@ class ComfyApi extends EventTarget { this.socket = new WebSocket( `ws${window.location.protocol === "https:" ? "s" : ""}://${location.host}/ws${existingSession}` ); + this.socket.binaryType = "arraybuffer"; this.socket.addEventListener("open", () => { opened = true; @@ -70,39 +71,66 @@ class ComfyApi extends EventTarget { this.socket.addEventListener("message", (event) => { try { - const msg = JSON.parse(event.data); - switch (msg.type) { - case "status": - if (msg.data.sid) { - this.clientId = msg.data.sid; - window.name = this.clientId; + if (event.data instanceof ArrayBuffer) { + const view = new DataView(event.data); + const eventType = view.getUint32(0); + const buffer = event.data.slice(4); + console.error("BINARY", eventType); + switch (eventType) { + case 1: + const view2 = new DataView(event.data); + const imageType = view2.getUint32(0) + let imageMime + switch (imageType) { + case 1: + default: + imageMime = "image/jpeg"; + break; + case 2: + imageMime = "image/png" } - this.dispatchEvent(new CustomEvent("status", { detail: msg.data.status })); - break; - case "progress": - this.dispatchEvent(new CustomEvent("progress", { detail: msg.data })); - break; - case "executing": - this.dispatchEvent(new CustomEvent("executing", { detail: msg.data.node })); - break; - case "executed": - this.dispatchEvent(new CustomEvent("executed", { detail: msg.data })); - break; - case "execution_start": - this.dispatchEvent(new CustomEvent("execution_start", { detail: msg.data })); - break; - case "execution_error": - this.dispatchEvent(new CustomEvent("execution_error", { detail: msg.data })); + const jpegBlob = new Blob([buffer.slice(4)], { type: imageMime }); + this.dispatchEvent(new CustomEvent("b_preview", { detail: jpegBlob })); break; default: - if (this.#registered.has(msg.type)) { - this.dispatchEvent(new CustomEvent(msg.type, { detail: msg.data })); - } else { - throw new Error("Unknown message type"); - } + throw new Error(`Unknown binary websocket message of type ${eventType}`); + } + } + else { + const msg = JSON.parse(event.data); + switch (msg.type) { + case "status": + if (msg.data.sid) { + this.clientId = msg.data.sid; + window.name = this.clientId; + } + this.dispatchEvent(new CustomEvent("status", { detail: msg.data.status })); + break; + case "progress": + this.dispatchEvent(new CustomEvent("progress", { detail: msg.data })); + break; + case "executing": + this.dispatchEvent(new CustomEvent("executing", { detail: msg.data.node })); + break; + case "executed": + this.dispatchEvent(new CustomEvent("executed", { detail: msg.data })); + break; + case "execution_start": + this.dispatchEvent(new CustomEvent("execution_start", { detail: msg.data })); + break; + case "execution_error": + this.dispatchEvent(new CustomEvent("execution_error", { detail: msg.data })); + break; + default: + if (this.#registered.has(msg.type)) { + this.dispatchEvent(new CustomEvent(msg.type, { detail: msg.data })); + } else { + throw new Error(`Unknown message type ${msg.type}`); + } + } } } catch (error) { - console.warn("Unhandled message:", event.data); + console.warn("Unhandled message:", event.data, error); } }); } diff --git a/web/scripts/app.js b/web/scripts/app.js index 95447ffa..495d43e1 100644 --- a/web/scripts/app.js +++ b/web/scripts/app.js @@ -44,6 +44,12 @@ export class ComfyApp { */ this.nodeOutputs = {}; + /** + * Stores the preview image data for each node + * @type {Record} + */ + this.nodePreviewImages = {}; + /** * If the shift key on the keyboard is pressed * @type {boolean} @@ -367,29 +373,52 @@ export class ComfyApp { node.prototype.onDrawBackground = function (ctx) { if (!this.flags.collapsed) { + let imgURLs = [] + let imagesChanged = false + const output = app.nodeOutputs[this.id + ""]; if (output && output.images) { if (this.images !== output.images) { this.images = output.images; - this.imgs = null; - this.imageIndex = null; + imagesChanged = true; + imgURLs = imgURLs.concat(output.images.map(params => { + return "/view?" + new URLSearchParams(src).toString() + app.getPreviewFormatParam(); + })) + } + } + + const preview = app.nodePreviewImages[this.id + ""] + if (this.preview !== preview) { + this.preview = preview + imagesChanged = true; + if (preview != null) { + imgURLs.push(preview); + } + } + + if (imagesChanged) { + this.imageIndex = null; + if (imgURLs.length > 0) { Promise.all( - output.images.map((src) => { + imgURLs.map((src) => { return new Promise((r) => { const img = new Image(); img.onload = () => r(img); img.onerror = () => r(null); - img.src = "/view?" + new URLSearchParams(src).toString() + app.getPreviewFormatParam(); + img.src = src }); }) ).then((imgs) => { - if (this.images === output.images) { + if ((!output || this.images === output.images) && (!preview || this.preview === preview)) { this.imgs = imgs.filter(Boolean); this.setSizeForImage?.(); app.graph.setDirtyCanvas(true); } }); } + else { + this.imgs = null; + } } if (this.imgs && this.imgs.length) { @@ -901,17 +930,20 @@ export class ComfyApp { this.progress = null; this.runningNodeId = detail; this.graph.setDirtyCanvas(true, false); + delete this.nodePreviewImages[this.runningNodeId] }); api.addEventListener("executed", ({ detail }) => { this.nodeOutputs[detail.node] = detail.output; const node = this.graph.getNodeById(detail.node); - if (node?.onExecuted) { - node.onExecuted(detail.output); + if (node) { + if (node.onExecuted) + node.onExecuted(detail.output); } }); api.addEventListener("execution_start", ({ detail }) => { + this.runningNodeId = null; this.lastExecutionError = null }); @@ -922,6 +954,16 @@ export class ComfyApp { this.canvas.draw(true, true); }); + api.addEventListener("b_preview", ({ detail }) => { + const id = this.runningNodeId + if (id == null) + return; + + const blob = detail + const blobUrl = URL.createObjectURL(blob) + this.nodePreviewImages[id] = [blobUrl] + }); + api.init(); } @@ -1465,8 +1507,10 @@ export class ComfyApp { */ clean() { this.nodeOutputs = {}; + this.nodePreviewImages = {} this.lastPromptError = null; this.lastExecutionError = null; + this.runningNodeId = null; } }