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
1.5 KiB
1.5 KiB
TT CLIP Text Encode FLUX (Context) TT_ClipTextEncodeFluxContext
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Context-based Flux text encoder that extracts prompts from workflow config.
Inputs
| Parameter | Type | Required | Description |
|---|---|---|---|
context |
TT_CONTEXT | Yes | Context containing CLIP encoder and workflow config with prompts |
Outputs
| Parameter | Type | Description |
|---|---|---|
CONTEXT |
TT_CONTEXT | Updated context with positive/negative conditioning added |
POSITIVE |
CONDITIONING | Positive conditioning from both encoders |
NEGATIVE |
CONDITIONING | Negative conditioning from both encoders |
Usage
Simplified encoder for context-based workflows. Automatically extracts CLIP-L and T5-XXL prompts plus guidance from workflow_config:
clip_l_positive,t5xxl_positivefor positive promptsclip_l_negative,t5xxl_negativefor negative promptsguidancefor Flux guidance scale
Updates context with the generated conditioning and also returns them separately for convenient access.