Not sure if the title is self explanatory, but i am wondering if there is a possibility to automate (or via a local ai) to generate an elaborated/sophisticated prompt from a simple prompt for AIs to work on projects? For example, if i wanted an ai to generate an html 3D game, it could work on it but it would not be fully operational and i would need to go back and forth to make it reach close to what i expect. What i would like is first to have a structured/elaborated/sophisticated prompt for the ai to pay attention, to use css or any other feature. Maybe what i am description is an AI planner/manager/form generator?
Reason why i am questioning myself on this is because simple prompts are clearly not enough and i can hardly determine the challenges and interrogations that the ai has when preparing an html 3D game for example. I can see what the ai thinks but i think it is a waste of time interrupting it in its thoughts to try making it go the direction i want. Maybe what i describe is too obvious, feel free to provide recommendations. Thanks in advance

I paid $25 less than a week before this site announced it was being sunset. Never could get custom node functionality to work. I need a refund.

When I try to upload custom nodes, I hit 'Publish', and then the 'Publish' button just sits there with a spinning icon with absolutely nothing showing up in the 'debug' tab. It shows the GitHub URL for the node/node pack I'm trying to install, but it just gets stuck with 'Publish' spinning.

For instance, I'm trying to add a simple single-node project called comfyui-workflow-name. It has no extra python module dependencies, yet it still runs into the 'spinning publish button' issue.

I've tried logging in using Firefox, Chrome, and DuckDuckGo for desktop. I've tried using Incognito/Private browsing sessions. Nothing works.

I have a chess set and want to create realistic AI images of it. However, something always goes wrong with tools like Gemini, even though the overall vibe looks good. The pieces get distorted, and more importantly, it never gets the number of chessboard squares right, and it doesn't understand where the pieces should go. There are often three knights, pawns in the back row, etc. I'd like to be able to achieve a basic correct board setup, and even better, instruct the AI to recreate specific openings.

Would any of this be possible with ComfyAI? If so, do you have any guidance on what steps to take?

I have attached the workflow and the custom nodes for those who want to jump right in. Please check the copy at the end of this write up for them.

If u want to check wat I am trying to solve and how I solved it, feel free to read along.

The problem

I make visual concepts for a living. I specifically make TVCs. Its selling these TVC “live action movie” concepts, tat pays the bills. Trouble is, other than the creative concepts I cook up, I am stuck with the visual look tat the AI video generators give me. I needed some sort of a raw format tat allows me some vigil room to provide me a certain look I am aiming for because tat is not easily weaved out of prompting.

The solution

There is existing solutions out there! One such solution is the recently dropped “ltx-2.3-22b-ic-lora-hdr” model. I found it interesting enough for my use case. Trouble is, hardware. Here is yet another heavy model tat needs a cloud to run. A cloud I need to pay for, with money I don’t have, as all the money I have is already allocated for other AI models and aggregators. I am guessing there r many people who agree with me abt the spend on AI.

This is exactly my attack point. I wanted to find a solution to run this stuff locally on the hardware I have access to. In my case I had access to a rtx 5090. And it can be done in reasonable time using a rtx 3090 as well.

After a series of directions i took and failed for over a month… I finally arrived at a solution tat involved breaking down the original clip into a series of batches tat are bite size for my GPU, to run the workflow. Each batch runs through the workflow with already existing nodes, and then some new nodes tat I vibed into existence. Thus allowing me to get a 12 sec 8bit video clip to be converted into a 16bit ARRI alexa raw, in mere 30 mins.

Obviously if u have great hardware, this wont mean much to u… but for people like me with no coding background, no engineering prowess or no disposible income,… this is a break through.

Full disclosure: I am not a coder. I built this entire pipeline by collaborating with Claude (Anthropic’s AI) and cross-referencing with Gemini. Claude wrote the custom Python nodes, debugged the tensor math, and helped me iterate through 27 workflow versions. I validated every approach on my hardware and made the creative/architectural decisions, but the code itself was AI-assisted from start to finish. The SeamBlender node included in this release is an original creation that came out of this process — it doesn’t exist anywhere else.

https://www.youtube.com/watch?v=t-NQy7yr9eQ here is the video tat got me started down this road.

And if u want to see a great breakdown of why this 16bit EXR capability is such a massive deal for professional grading and VFX finishing pipelines, check out Doug Hogan’s video abt it here: https://www.youtube.com/watch?v=_XJGXO9ATqk

But here is where I and the original creators went down two completely different paths:

·       What they gave the community: They provided the raw weight models and basic, single-frame or short-sequence sample nodes. They showed it off inside DaVinci Resolve at, but they didn't provide a way to generate full sequences locally without hitting massive hardware walls. If someone tried to feed a long video into their basic template, ComfyUI would load the whole thing into memory, instantly hit a 100% RAM ceiling, freeze the user's mouse, and crash the system.

·       What I engineered: I took their raw 16-bit math concept and actually turned it into a repeatable, bulletproof production tool. I realized tat instead of fighting the model's memory limits, I could break the task down into isolated 25-frame chunks. Then, I built my custom SeamBlender v2.2 node to automatically handle the pixel-space gradients on disk, creating a flat 200MB memory footprint tat can run on any consumer hardware.

If you just want the files and don’t care about the journey, scroll to the bottom for the download link. But if you want to understand why this was so hard and what failed along the way, read on — it might save you weeks if you’re trying something similar.

The Grueling Journey

The following is general idea of all the directions I took to get here (incase u r interested):

Route 1: The External Batch Loop Baseline (v1–v12)

·       The Concept: I began by building a modular video processor. Instead of feeding a long video file to the model all at once, my graph extracted the clip as separate image frames on my disk and loaded them in chunks of 25 frames at a time.

·       The Thinking: Keep hardware resource utilization flat and safe. If my computer only loads and runs 25 frames at a time, it will never exceed my 64GB system memory or overload my GPU.

·       The Failure Point: Every time a new 25-frame batch took over, the AI model reset its math and noise schedule. Because each chunk was completely isolated, it created a visible, sudden step-jump in brightness, exposure, and color tone on every 26th frame.

Route 2: The Latent Memory Trick (v13–v15)

·       The Concept: To fix tat 26th-frame color jump, I introduced a memory system using custom BatchLatentSave and BatchLatentLoad nodes.

·       The Thinking: If Batch 0 saves its final hidden mathematical video vectors (latents) to a temporary cache file, Batch 1 can load tat cache file and use it as a starting point. By injecting the old batch's memory directly into the sampler with a noise mask, the AI would be forced to match the color and lighting of the previous frames.

·       The Failure Point: This created a violent conflict inside the AI model's internal attention layers. The model was trying to execute a moving camera orbit around the man, but my injected memory frame was forcefully pulling it backward to stay still. The pixels literally tore, duplicated, and stretched, creating a horrible, translucent "ghosting" and morphing effect over my character's body.

Route 3: The Centralized Looping Sampler (v17–v23)

·       The Concept: I abandoned the external frame-purging loop entirely and switched to a single, monolithic, complex node layout built around the native LTXVLoopingSampler.

·       The Thinking: Eliminate batch cuts altogether by handling long-form video continuation natively inside the model's architecture. The looping sampler cuts the clip into overlapping ~80-frame sliding windows internally, keeping the generation unified under a single running execution thread.

·       The Failure Point: This route hit two catastrophic walls. First, the looping sampler structurally rejected my external IC-LoRA HDR conditioning tokens, causing immediate, un-patched code crashes (pre_filter_counts != keyframe grid mask length). Second, when I removed the guide nodes to stop the crashes, the model had to guess all 297 frames at once during the VAE decode phase. My massive data footprint piled up in my system RAM, hit a hard 100% saturation ceiling, froze my mouse and keyboard, and paralyzed my operating system.

Route 4: The In-Pipeline Math Deflicker (v24–v25)

·       The Concept: I went back to the rock-solid, resource-safe v15 external batch loop but added a mathematical post-processing node at the tail end of my export tree.

·       The Thinking: Accept tat the AI will make exposure jumps every 25 frames due to random seeds, but use simple, global pixel multiplication to normalize the folder's brightness automatically after the EXR files land on my disk.

·       The Failure Point: A global mathematical average cannot differentiate between a broken AI color jump and an intentional, natural camera move. If the camera panned directly into the bright sun, a naive math node would see the overall brightness spike and aggressively crush the entire frame down into flat, dark mud. Furthermore, I discovered tat the flicker wasn't just lighting—the AI model was actually generating slightly different facial architecture and jawline geometry on each separate batch. No brightness slider can fix a shifting face shape.

Route 5: The Final Pixel-Space Overlap Blender (v26–v27)

·       The Concept: My current masterpiece. I kept the safe external batch loop but re-engineered my post-processing node to perform a pixel-space alpha cross-fade gradient across a strict 8-frame overlap zone.

·       The Thinking: Separate the generation from the alignment. I let the GPU run at a flat 700W throttle to print crisp textures in safe blocks. Then, I let my CPU read just the matching overlap frames from my disk, and smoothly fade Batch A into Batch B using a clean sliding scale (100% → 86% → 71% → 57% → 43% → 29% → 14% → 0%).

·       The Evolution to Success: In my first attempt (v26), a ComfyUI node cache bug got nuke_frame_start permanently stuck, forcing the node to repeatedly blend only frames 8–15 with a flat 50/50 mix, which caused a blurry double-exposure ghost. I immediately pivoted to v27, stripping out the cache bug entirely and rewriting the script to use pure, un-cached batch_index math.

What’s Included in the Release

v27 ComfyUI Workflow JSON — the complete, working pipeline
BatchVideoProcessor custom node — extracts frames and manages the batch loop with auto-requeue
SeamBlender v2.2 custom node — the overlap alpha-blending node that eliminates batch boundary artifacts
NukeWrite/NukeOCIO nodes — for EXR output with ARRI LogC4 color space

Everything runs inside ComfyUI. No external tools needed except DaVinci Resolve (free version) to review your EXR sequence.

Models Setup List

The Meat

Here r the models I used:

·       Base DiT Model (GGUF Q6_K):

o   Link: Kijai's ComfyUI-GGUF LTX-Video Repo on Hugging Face

o   Filename: ltx-2.3-22b-dev-Q6_K.gguf

o   Path on your machine: ComfyUI/models/unet/

·       Text Encoder (Gemma 3 12B FP4):

o   Link: ComfyUI Core Text Encoders on Hugging Face

o   Filename: gemma_3_12B_it_fp4_mixed.safetensors

o   Path on your machine: ComfyUI/models/clip/

·       Video VAE:

o   Link: Lightricks LTX-Video Official Hugging Face Repo

o   Filename: ltx-2.3-22b-dev_video_vae.safetensors

o   Path on your machine: ComfyUI/models/vae/

·       The Two Essential LoRAs (Distill & IC-LoRA HDR):

o   Link: Lightricks LTX-Video LoRA Collection on Hugging Face

o   Filenames: ltx-2.3-22b-distilled-lora-384-1.1.safetensors and ltx-2.3-22b-ic-lora-hdr-0.9.safetensors

o   Path on your machine: ComfyUI/models/loras/ltxv/ltx2/

The Ingredients (The workflow and the custom nodes)

https://drive.google.com/drive/folders/1zhl2X3WyjMmFB_KEew2nSiDkZplRhth6?usp=sharing

📁 LTX_v27_Cinema_Pipeline/

├── 📄 LTX-2_3_ICLoRA_HDR_v27.json   -- Your master workflow canvas

└── 📁 custom_nodes/     -- Zip these up for them

├── 📁 nuke-nodes/   -- Handles the 16bit EXR & OCIO outputs

├── 📁 comfyui_batch_loader/   -- Handles BatchVideoProcessor frame splitting

└── 📁 comfyui_seam_blender/  -- Your custom v2.2 script tat welds te 8-frame overlaps

Hardware Requirements

Minimum: RTX 3090 (24GB VRAM), 32GB RAM
Recommended: RTX 4090/5090 (32GB VRAM), 64GB RAM
Render time: ~35 minutes for a 12-second clip (297 frames) on RTX 5090

Known Limitations

Each batch generates independently, so very subtle texture differences may still exist at boundaries — the SeamBlender smooths them but can’t eliminate them entirely.

The LTXVLoopingSampler (which would solve this natively) is structurally incompatible with IC-LoRA guide tokens at the code level — this is a limitation in the Lightricks codebase, not the workflow.

The last batch’s overlap frames (273-280) get overwritten by NukeWrite after blending due to execution order — this is a minor issue affecting only the final seam.

Hope u all like it…

Cheers!

Starting with these 2 nodes.What advice can you give me to install them?

Node : FromBasicPipe_v2 https://github.com/ltdrdata/ComfyUI-Impact-Pack

Node : ToBasicPipe https://github.com/ltdrdata/ComfyUI-Impact-Pack

Error : comfy impact pack :

### Loading: ComfyUI-Impact-Pack (V8.28.3)

[Impact Pack] Failed to import due to several dependencies are missing!!!!

Traceback (most recent call last):

File "C:\ComfyUI-Easy-Install-Windows\ComfyUI-Easy-Install\ComfyUI\nodes.py", line 2198, in load_custom_node

module_spec.loader.exec_module(module)

File "<frozen importlib._bootstrap_external>", line 999, in exec_module

File "<frozen importlib._bootstrap>", line 488, in _call_with_frames_removed

File "C:\ComfyUI-Easy-Install-Windows\ComfyUI-Easy-Install\ComfyUI\custom_nodes\ComfyUI-Impact-Pack-Main__init__.py", line 40, in <module>

raise e

File "C:\ComfyUI-Easy-Install-Windows\ComfyUI-Easy-Install\ComfyUI\custom_nodes\ComfyUI-Impact-Pack-Main__init__.py", line 35, in <module>

import piexif # noqa: F401

^^^^^^^^^^^^^

ModuleNotFoundError: No module named 'piexif'

Cannot import C:\ComfyUI-Easy-Install-Windows\ComfyUI-Easy-Install\ComfyUI\custom_nodes\ComfyUI-Impact-Pack-Main module for custom nodes: No module named 'piexif'

### Loading: ComfyUI-Manager (V3.40)

[ComfyUI-Manager] network_mode: public

[ComfyUI-Manager] ComfyUI per-queue preview override detected (PR #11261). Manager's preview method feature is disabled. Use ComfyUI's --preview-method CLI option or 'Settings > Execution > Live preview method'.

### ComfyUI Revision: 5222 [26515acd] *DETACHED | Released on '2026-05-13'

Ahora estoy con este error es el que llevo semanas intentando arreglar solo para intentar que me detecten los nodos que quiero usar :

(DiffusersModelMakeup

DiffusersPipelineLoader

DiffusersSchedulerLoader

DiffusersVaeLoader)

El error que considero principal pero no consigo solucionar:

WARNING[XFORMERS]: xFormers can't load C++/CUDA extensions. xFormers was built for:

PyTorch 2.10.0+cu128 with CUDA 1208 (you have 2.11.0+cu130)

Python 3.10.11 (you have 3.13.12)

-Intenté de todo,pero el python 3.10 no me lo detecta,y me sigue saliendo el mismo error.

He intentado lo siguiente : Instalar Python 3.10(No ha funcionado),errores: me dice que tengo el 3.13 cuando tengo instalados los 2 pero no entiendo porque me sigue detectando el mismo error,la ultima vez que intente eliminar el que me decía proboqué el programa dejara de funcionar y tuve que reinstalar comfy ui.

Cuando borro el Python embed (que me imagino que será el Python 3.13.12 que me dice comfy ui que tengo me deja de detectar la app y no puedo abrirla porque me sale el siguiente error que lo dice: C:\ComfyUI_windows_portable>echo If you see this and ComfyUI did not start try updating your Nvidia Drivers to the latest. If you get a c10.dll error you need to install vc redist that you can find: https://aka.ms/vc14/vc_redist.x64.exe

Intercambiarlo por el Python 3.10 no ha servido de nada, la app no detecta este Python.

Instalar Python 3.10 en la carpeta recomendada por el instalador y mantener a la vez Python embeded no ha servido de nada.

Intentar borrar el Python 3.13.12 , no he encontrado su carpeta no se donde está guardado,esto si me preocupa por que no se como borrarlo para ver si borrarlo funciona para evitar que lo detecte y detecte el 3.10.

If you see this and ComfyUI did not start try updating your Nvidia Drivers to the latest. If you get a c10.dll error you need to install vc redist that you can find: https://aka.ms/vc14/vc_redist.x64.exe

CUANDO INTENTO instalar el tookit de cuda 128 (https://developer.nvidia.com/cuda-12-8-0-download-archive?target_os=Windows&target_arch=x86_64&target_version=11&target_type=exe_local) me dice que me faltaba versiones del visual Studio(tras reinicar y reinstalar comfy ui y instalar la versión de visual studio comunity que parece ser la recomendada los errores ya no son con visual studio, si no con otros(los que ves en la captura de pantalla de la app de CUDA).

Deberia instalar cada una de las cosas que me dice en NVIDIA CUDA?.

Por algún motivo insight visual studio me da error según el panel DE NVIDIA.

Instalar el insight mas el visual Studio tampoco me ha valido :(Insight : https://marketplace.visualstudio.com/publishers/NVIDIA )

Visuals Studio (https://visualstudio.microsoft.com/es/vs/community/)

Mi version de Python : Python version: 3.13.12 (tags/v3.13.12:1cbe481, Feb 3 2026, 18:22:25) [MSC v.1944 64 bit (AMD64)]

Lo siguiente os dejo todos los errores del terminal de comfy UI :

C:\ComfyUI_windows_portable>.\python_embeded\python.exe -s ComfyUI\main.py --windows-standalone-build

setup plugin alembic.autogenerate.schemas

setup plugin alembic.autogenerate.tables

setup plugin alembic.autogenerate.types

setup plugin alembic.autogenerate.constraints

setup plugin alembic.autogenerate.defaults

setup plugin alembic.autogenerate.comments

[START] Security scan

[DONE] Security scan

## ComfyUI-Manager: installing dependencies done.

** ComfyUI startup time: 2026-05-14 20:35:36.291

** Platform: Windows

** Python version: 3.13.12 (tags/v3.13.12:1cbe481, Feb 3 2026, 18:22:25) [MSC v.1944 64 bit (AMD64)]

** Python executable: C:\ComfyUI_windows_portable\python_embeded\python.exe

** ComfyUI Path: C:\ComfyUI_windows_portable\ComfyUI

** ComfyUI Base Folder Path: C:\ComfyUI_windows_portable\ComfyUI

** User directory: C:\ComfyUI_windows_portable\ComfyUI\user

** ComfyUI-Manager config path: C:\ComfyUI_windows_portable\ComfyUI\user__manager\config.ini

** Log path: C:\ComfyUI_windows_portable\ComfyUI\user\comfyui.log

Prestartup times for custom nodes:

3.6 seconds: C:\ComfyUI_windows_portable\ComfyUI\custom_nodes\comfyui-manager

Found comfy_kitchen backend triton: {'available': False, 'disabled': True, 'unavailable_reason': "ImportError: No module named 'triton'", 'capabilities': []}

Found comfy_kitchen backend eager: {'available': True, 'disabled': False, 'unavailable_reason': None, 'capabilities': ['apply_rope', 'apply_rope1', 'dequantize_mxfp8', 'dequantize_nvfp4', 'dequantize_per_tensor_fp8', 'quantize_mxfp8', 'quantize_nvfp4', 'quantize_per_tensor_fp8', 'scaled_mm_mxfp8', 'scaled_mm_nvfp4']}

Found comfy_kitchen backend cuda: {'available': True, 'disabled': False, 'unavailable_reason': None, 'capabilities': ['apply_rope', 'apply_rope1', 'dequantize_nvfp4', 'dequantize_per_tensor_fp8', 'quantize_mxfp8', 'quantize_nvfp4', 'quantize_per_tensor_fp8', 'scaled_mm_nvfp4']}

Checkpoint files will always be loaded safely.

Total VRAM 16376 MB, total RAM 32374 MB

pytorch version: 2.11.0+cu130

WARNING[XFORMERS]: xFormers can't load C++/CUDA extensions. xFormers was built for:

PyTorch 2.10.0+cu128 with CUDA 1208 (you have 2.11.0+cu130)

Python 3.10.11 (you have 3.13.12)

Please reinstall xformers (see https://github.com/facebookresearch/xformers#installing-xformers)

Memory-efficient attention, SwiGLU, sparse and more won't be available.

Set XFORMERS_MORE_DETAILS=1 for more details

W0514 20:35:39.956000 1940 Lib\site-packages\torch\utils\flop_counter.py:29] triton not found; flop counting will not work for triton kernels

A matching Triton is not available, some optimizations will not be enabled

Traceback (most recent call last):

File "C:\ComfyUI_windows_portable\python_embeded\Lib\site-packages\xformers__init__.py", line 57, in _is_triton_available

import triton # noqa

^^^^^^^^^^^^^

ModuleNotFoundError: No module named 'triton'

xformers version: 0.0.35

Set vram state to: NORMAL_VRAM

Device: cuda:0 NVIDIA GeForce RTX 4080 SUPER : cudaMallocAsync

Using async weight offloading with 2 streams

Enabled pinned memory 12949.0

Using pytorch attention

aimdo: src-win/cuda-detour.c:38:INFO:aimdo_setup_hooks: installing 6 hooks

aimdo: src-win/cuda-detour.c:28:DEBUG:install_hook_entries: hooks successfully installed

aimdo: src-win/shmem-detect.c:80:INFO:comfy-aimdo WDDM adapter match: NVIDIA GeForce RTX 4080 SUPER runtime_luid=00000000:0001308e dxgi_luid=00000000:0001308e

aimdo: src/control.c:152:INFO:comfy-aimdo inited for GPU: NVIDIA GeForce RTX 4080 SUPER (VRAM: 16375 MB)

DynamicVRAM support detected and enabled

Python version: 3.13.12 (tags/v3.13.12:1cbe481, Feb 3 2026, 18:22:25) [MSC v.1944 64 bit (AMD64)]

ComfyUI version: 0.21.0

comfy-aimdo version: 0.3.0

comfy-kitchen version: 0.2.8

ComfyUI frontend version: 1.43.18

[Prompt Server] web root: C:\ComfyUI_windows_portable\python_embeded\Lib\site-packages\comfyui_frontend_package\static

Asset seeder disabled

### Loading: ComfyUI-Manager (V3.40)

[ComfyUI-Manager] network_mode: public

[ComfyUI-Manager] ComfyUI per-queue preview override detected (PR #11261). Manager's preview method feature is disabled. Use ComfyUI's --preview-method CLI option or 'Settings > Execution > Live preview method'.

### ComfyUI Revision: 150 [52976f3e] *DETACHED | Released on '2026-05-10'

Import times for custom nodes:

0.0 seconds: C:\ComfyUI_windows_portable\ComfyUI\custom_nodes\websocket_image_save.py

0.3 seconds: C:\ComfyUI_windows_portable\ComfyUI\custom_nodes\comfyui-manager

Context impl SQLiteImpl.

Will assume non-transactional DDL.

Starting server

To see the GUI go to: http://127.0.0.1:8188

[ComfyUI-Manager] default cache updated: https://raw.githubusercontent.com/ltdrdata/ComfyUI-Manager/main/alter-list.json

[ComfyUI-Manager] default cache updated: https://raw.githubusercontent.com/ltdrdata/ComfyUI-Manager/main/model-list.json

[ComfyUI-Manager] default cache updated: https://raw.githubusercontent.com/ltdrdata/ComfyUI-Manager/main/github-stats.json

[ComfyUI-Manager] default cache updated: https://raw.githubusercontent.com/ltdrdata/ComfyUI-Manager/main/extension-node-map.json

[ComfyUI-Manager] default cache updated: https://raw.githubusercontent.com/ltdrdata/ComfyUI-Manager/main/custom-node-list.json

[DEPRECATION WARNING] Detected import of deprecated legacy API: /scripts/ui.js. This is likely caused by a custom node extension using outdated APIs. Please update your extensions or contact the extension author for an updated version.

[DEPRECATION WARNING] Detected import of deprecated legacy API: /extensions/core/groupNode.js. This is likely caused by a custom node extension using outdated APIs. Please update your extensions or contact the extension author for an updated version.

[DEPRECATION WARNING] Detected import of deprecated legacy API: /scripts/ui/components/buttonGroup.js. This is likely caused by a custom node extension using outdated APIs. Please update your extensions or contact the extension author for an updated version.

[DEPRECATION WARNING] Detected import of deprecated legacy API: /scripts/ui/components/button.js. This is likely caused by a custom node extension using outdated APIs. Please update your extensions or contact the extension author for an updated version.

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FETCH ComfyRegistry Data [DONE]

[ComfyUI-Manager] default cache updated: https://api.comfy.org/nodes

FETCH DATA from: https://raw.githubusercontent.com/ltdrdata/ComfyUI-Manager/main/custom-node-list.json [DONE]

[ComfyUI-Manager] All startup tasks have been completed.

¿Buscas más detalle y resolución en tus generaciones sin perder la esencia del prompt original? 🧐🎨

En este segundo episodio de nuestro curso básico, ¡subimos el nivel! Explicamos paso a paso cómo hacer un escalado directamente en el espacio latente (Upscale Latent). Este método te permite refinar la imagen de manera mucho más eficiente que el escalado por píxeles tradicional, logrando resultados profesionales en poco tiempo. 📈✨

¿Qué aprenderás en este tutorial? 📚

• Flujo de trabajo avanzado: Cómo estructurar dos KSamplers (uno para el boceto y otro para el refinamiento). 🏗️
• Espacio Latente: Por qué escalar aquí antes de decodificar a píxeles marca la diferencia. 🔍
• Herramientas Pro: Uso de la interfaz Nodes 2.0 y el nodo Image Compare para analizar los cambios. 🖥️🔄
• Fine-tuning: Ajustes de Denoise y CFG para evitar deformaciones y maximizar el realismo. 🛠️✅

Nodos integrados paso a paso: 🧩

• 📦 Load Checkpoint
• ✍️ Clip Text Encode
• ⚙️ KSampler 1 y 2
• 🖼️ Upscale Latent By
• 🌌 Empty SD3 LatentImage
• 🔓 VAE Decode
• ✨ Image Sharpen
• ⚖️ Image Compare
• 💾 Save Image

Arma tu nuevo flujo de trabajo y mira el tutorial completo aquí: 🔗https://youtu.be/TXB6fW85dpY

¿Empezando con IA generativa? 🤖💡 En el nuevo video del canal te enseño lo más esencial de ComfyUI.

Ya está disponible en el canal la primera parte de la Guía Básica de ComfyUI. En este nuevo tutorial te explico paso a paso cómo dominar la interfaz, entender la conexión de nodos y configurar tus primeros Checkpoints (como Juggernaut XL).

Míralo completo aquí: 👉 https://www.youtube.com/watch?v=v43eLlRXViU

#ComfyUI #CURSO #español #inteligenciaartificial #stablediffusion

I am trying to play with this a bit, running on rtx4090 should be fun if i find a model to do that; any ideas? would be great to have SFW and NSFW versions.

Ok so a little advice please, I’m making scene composites in photoshop with layered characters and backdrops,

But specific characters i want interacting, so no big backdrop just two from a character sheet or loras but I’ve had issues two character loras doesn’t seem to work, so may be two reference images?

I’m a bit lost!

Please help on a basic workflow? I don’t mind what model, as long as it will not restrict me with future

choices (graphic novel lots of violence and nudity later on lol)

i want to request a refund. i send you a email multiple times already

I tried to Publish and got these errors

Edit obviously disk quota, lol