TenserTensor
22c3d146bd
Implement post-production processing nodes: - add_film_grain.py: procedural film grain effect - apply_lut.py: LUT-based color grading - image_enhancer.py: comprehensive image adjustments (brightness, contrast, gamma, hue, saturation, sharpness, posterize, solarize) - postproduction.py: all-in-one pipeline (LUT + film grain + upscaling) - postproduction_advanced.py: extended pipeline with image enhancement controls - quick_image_upscaler.py: simple tiled AI upscaler Add markdown documentation for all post-production nodes
1.1 KiB
1.1 KiB
TT KSampler (Context) TT_KSamplerContext
Context-based sampler that extracts parameters from workflow context.
Inputs
| Parameter | Type | Required | Description |
|---|---|---|---|
context |
TT_CONTEXT | Yes | Context containing model, latent, conditioning, and workflow config |
Outputs
| Parameter | Type | Description |
|---|---|---|
CONTEXT |
TT_CONTEXT | Pass-through context |
LATENT |
LATENT | Denoised latent image |
Usage
Simplified sampler for context-based workflows. Automatically extracts all sampling parameters from the context object:
- Model, positive/negative conditioning, and latent from context
- Seed, steps, cfg, sampler_name, and scheduler from workflow_config
Requires context to contain: model, latent, and workflow_config. Raises error if any required component is missing.