Warning

This experimental LoRA was trained on very little data, without adequate regularization, and at a rank that is low for the number and complexity of its tasks. Training a new LoRA for your specific goal is recommended. An image-edit-capable base model should produce better results when trained on fixed-integer-upscaled pixel art with consistent trigger words and a deliberate mixture of text-to-image and image-edit examples.

An experimental rank-16 LoRA for editing female LPC characters and 4×2 walking sprite sheets with FLUX.2 [klein] Base 9B.

Project repository: iljung1106/LPC-FourDirection-Walk-Flux-Klein-9B

Result samples

These GIFs are direct GUI exports. Samples 1, 2, and 5 contain 24 frames; samples 3 and 4 contain one 8-frame walking cycle.

Outputs may be inconsistent, as samples 2–4 demonstrate. Poorly written training captions made this LoRA highly prompt-sensitive, so small prompt changes can produce results that are difficult to predict.

Sample 1	Sample 2	Sample 3
Blonde character walking south	Brown-haired character walking west	Green-headed character walking north

Sample 4	Sample 5
Blue-haired character walking east	Mint-twintail character walking south

Supported tasks

Task token	Input	Output
`TASK_ROTATE_STANDING`	South-facing dressed character	Same character facing north, east, or west
`TASK_STANDING_TO_WALK_FIRST_FRAME`	Standing character	First walking frame in the same direction
`TASK_PROPAGATE_APPEARANCE`	4×2 sheet with frame 1 dressed	The same appearance applied to frames 2–8
`TASK_DRESS_WALK_SHEET`	Female base 4×2 walk sheet	All eight frames dressed from a text description
`TASK_DRESS_STANDING`	South-facing female base	Standing character dressed from a text description

Use the exact task token and sentence structure used during training:

TASK_ROTATE_STANDING: Turn the south-facing standing female LPC character to face north. Preserve the exact hairstyle, hair color, clothing, shoes and accessories. Keep the character centered on a pure white background.

TASK_STANDING_TO_WALK_FIRST_FRAME: Convert this west-facing standing LPC character into the first frame of the west-facing walking animation. Preserve the exact appearance and pure white background.

TASK_PROPAGATE_APPEARANCE: Use frame 1 as the appearance reference. Apply exactly the same hairstyle, hair color, clothing, shoes and accessories to frames 2 through 8. Preserve every walking pose, frame order, 4 by 2 layout and pure white background.

TASK_DRESS_WALK_SHEET: Dress the female LPC character in all 8 east-facing walking frames with blue bob hair, a red long-sleeve shirt, navy pants, brown boots, and gold glasses. Preserve every pose, frame order, 4 by 2 layout and pure white background.

TASK_DRESS_STANDING: Dress the south-facing standing female LPC character with blue bob hair, a red long-sleeve shirt, navy pants, brown boots, and gold glasses. Preserve the pose and pure white background.

Recommended inference settings

Diffusion model: black-forest-labs/FLUX.2-klein-base-9B
ComfyUI model file: flux-2-klein-base-9b-fp8.safetensors
LoRA strength: 1.2
Steps: 11
Known-good seed: 981958406821486
CFG: 3.5
PAG: 1.5
Sampler: Euler
Standing tasks: 1024×1024
4×2 sheet tasks: 2048×1024
Background: white

ComfyUI workflow

The workflow uses only ComfyUI core nodes and has been tested on Comfy Cloud. Because the LoRA is undertrained, using it with PAG is recommended. A LoRA strength of 1.2 can produce better results than 1.0 for the same reason; these values are starting points rather than guarantees.

Install LPC_FourDirection_Walk_ComfyUI.safetensors as a LoRA.
Import workflows/LPC_FourDirection_Walk_ComfyUI.json.
Select an input image and paste one of the task prompts above.
Resize standing/frame inputs to exactly 1024×1024 and 4×2 inputs to exactly 2048×1024 with nearest-exact.
Generate with LoRA strength 1.2, 11 steps, CFG 3.5, PAG 1.5, and Euler.

Use this negative prompt:

random composition, low quality, scattered, dynamic movement, out of position

The graph uses:

flux-2-klein-base-9b-fp8.safetensors
qwen_3_8b_fp8mixed.safetensors
full_encoder_small_decoder.safetensors

Keep the input reference latent connected to both positive and negative conditioning. This matches the official FLUX.2 Klein edit graph.

An API-format version is available at workflows/LPC_FourDirection_Walk_API.json.

GUI

The included Korean-language Gradio workbench turns the five trained tasks into a guided character-production flow. It works with Comfy Cloud or a local ComfyUI server.

powershell

python -m venv .venv
.\.venv\Scripts\python -m pip install --upgrade pip
.\.venv\Scripts\python -m pip install -r requirements.txt
.\.venv\Scripts\python app.py

For Comfy Cloud, copy .env.example to .env and set:

dotenv

COMFY_URL=https://cloud.comfy.org
COMFY_API_KEY=your_api_key

The API key is read at runtime and is not written to the repository or output files.

Use the virtual-environment commands above even if Anaconda base is active. Gradio 5.x imports the removed huggingface_hub.HfFolder API and is not supported by this GUI.

Guided workflow

Quick build: dress the bundled standing base, create selected standing directions, and build each direction's 4×2 walking sheet stage by stage. Run-all is a separate action and shows its Comfy job count first. Each stage can be regenerated immediately with a new recorded seed.
LoRA strength: the always-visible shared slider applies 0–1.5 to every generation task; 0 disables the LoRA and 1.2 is the default.
Standing: upload a character or start from the bundled female LPC base, then create a dressed standing proof and its 32-color palette.
Directions: inspect north, west, south, and east standing results on one turnaround board. Up to four direction jobs run concurrently, and each result appears as soon as it finishes.
Walking: create a first walking frame from the standing-character latent at 0.9 denoise, without blending in a base-walk latent. Insert that frame into the matching bundled 4×2 pose base, then propagate the appearance to all eight frames. Each completed sheet gets an immediate looping animation preview.
Dressing: character-design tasks use the supplied LPC base latent at 0.9 denoise. Other tasks use an empty latent at full denoise.
Stage handoff: every generated image is flattened onto pure white before reuse. Colors clearly present in both the input and output are softly matched; newly introduced design colors remain available.
Pixel and palette: snap to native LPC pixels, align 4×2 foot anchors, lock or rebuild a 32-color palette, and export indexed PNG or GIF.
Results and settings: review local session outputs, test the Comfy connection, tune generation settings, or access the exact English task prompts in the advanced single-task panel.

Generated files are saved under the ignored local outputs/ directory. The bundled bases match the fixed feminine thin body and head used during training; other body types are outside this toy model's supported scope.

Pixel and palette output

The GUI includes deterministic sprite post-processing:

Lock reference palette: maps every output pixel to the nearest color in the input image or an optional shared palette-reference image. Select the same reference for north, south, east, and west to keep one palette across all directions.
Allow new colors (32): builds a new adaptive 32-color palette from the generated result. Use this when the prompt adds hair, clothing, or accessories whose colors are absent from the base.
Align 4×2 frames: detects the white background and aligns each generated frame's foot anchor with the corresponding input frame on the native 64×64 logical grid.
Pixel snap: uses perfectPixel to detect and refine each of the eight frames separately. Each native frame is fitted back to its generated source by a small nearest-neighbor scale and position search before the sheet is reassembled.
Shared direction palette: once every selected direction is complete, one 32-color palette is calculated from all completed images and applied back to every direction without dithering.
Resolution: returns either native 64×64 single frames / 256×128 4×2 sheets or exact 1024×1024 / 2048×1024 nearest-neighbor upscaled output.
Output: returns an indexed PNG sheet or a 24-frame looping GIF. The eight row-major sheet frames repeat three times.

Both palette modes write a 32-entry indexed palette without dithering. The background remains white.

Verified Comfy Cloud examples

Task	Input	Output
Dress standing character	Standing input	Standing output
Propagate frame 1 appearance	Propagation input	Propagation output

Files

LPC_FourDirection_Walk.safetensors: original fal/PEFT format
LPC_FourDirection_Walk_ComfyUI.safetensors: ComfyUI-compatible key names
LoRA rank: 16
Tensors: 176, float32
Original SHA-256: 5e092a1451be9565862c491e58cfd85514869433570e85f2d2661ff613cbab6c
ComfyUI SHA-256: 272ed2f178dc205b016d5783757ff0ee7ddaec834f95bdd7fc061d08e3dc2afe

Use the original file with fal. Use the _ComfyUI file with ComfyUI. The conversion only renames the fal PEFT prefix base_model.model. to ComfyUI's FLUX model prefix diffusion_model.; tensor values are unchanged. The reproducible converter is included as convert_fal_lora_to_comfy.py.

Limitations

This is a toy-project LoRA trained on one female LPC body type. It may alter silhouettes, frame spacing, or poses, especially for appearances outside the training distribution. Generated sheets are not guaranteed to be pixel-perfect and may need alignment or nearest-neighbor cleanup.

License and attribution

The weights are a derivative of FLUX.2 [klein] Base 9B and are distributed under the FLUX Non-Commercial License v2.1. Read LICENSE.md and NOTICE before downloading or using them. Commercial or production use of the model requires appropriate permission from Black Forest Labs.

Training assets are derived from ElizaWy/LPC and retain their respective LPC asset licenses and attribution requirements. See THIRD_PARTY_NOTICES.txt.

This project is not affiliated with or endorsed by Black Forest Labs or the LPC contributors.

Baragi-AI/LPC-FourDirection-Walk-Flux-Klein-9B

LPC Four-Direction Walk — FLUX.2 Klein 9B