Type: mlx.image_to_image.MFluxControlNet

Namespace: mlx.image_to_image

Description

Generate images with MFlux ControlNet guidance using local MLX acceleration. mlx, flux, controlnet, conditioning, edge-detection

Use cases:
- Apply edge-aware guidance via ControlNet canny models
- Leverage local Apple Silicon acceleration for conditioned generations
- Upscale images using ControlNet upscaler weights

Properties

Property Type Description Default
prompt str Primary text prompt for image generation. Highly detailed cinematic portrait
control_image image Reference image used by ControlNet for conditioning. {'type': 'image', 'uri': '', 'asset_id': None, 'data': None}
model hf.flux Base Flux model to load for conditioned generation. {'type': 'hf.flux', 'repo_id': 'dhairyashil/FLUX.1-dev-mflux-4bit', 'path': None, 'variant': None, 'allow_patterns': None, 'ignore_patterns': None}
controlnet_model hf.controlnet_flux ControlNet weights that match the selected Flux base model. {'type': 'hf.controlnet_flux', 'repo_id': 'InstantX/FLUX.1-dev-Controlnet-Canny', 'path': None, 'variant': None, 'allow_patterns': None, 'ignore_patterns': None}
quantize Optional[Enum[3, 4, 5, 6, 8]] Optional quantization level for model weights (reduces memory usage). 4
steps int Number of denoising steps for diffusion. 8
guidance Optional[float] Classifier-free guidance scale when supported by the selected model. 3.5
controlnet_strength float Blend factor between ControlNet conditioning and base model prior. 0.5
height int Height of the generated image in pixels. 1024
width int Width of the generated image in pixels. 1024
seed int Seed for deterministic generation. Leave 0 for random. 0

Outputs

Output Type Description
output image  

Metadata

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