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
1.6 KiB
1.6 KiB
TT CLIP Text Encode SDXL (Context) TT_ClipTextEncodeSdxlContext
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Context-based SDXL text encoder that extracts prompts and parameters from workflow config.
Inputs
| Parameter | Type | Required | Description |
|---|---|---|---|
context |
TT_CONTEXT | Yes | Context containing CLIP encoder and workflow config with prompts and parameters |
Outputs
| Parameter | Type | Description |
|---|---|---|
CONTEXT |
TT_CONTEXT | Updated context with positive/negative conditioning added |
POSITIVE |
CONDITIONING | Positive conditioning with aesthetic score and dimensions |
NEGATIVE |
CONDITIONING | Negative conditioning with aesthetic score and dimensions |
Usage
Simplified encoder for context-based SDXL workflows. Automatically extracts all encoding parameters from workflow_config:
clip_l_positive,clip_g_positivefor positive promptsclip_l_negative,clip_g_negativefor negative promptsascore_positive,ascore_negativefor aesthetic scoreswidth,height,target_width,target_heightfor dimensions
Updates context with the generated conditioning and also returns them separately for convenient access.