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 FLUX TT_ClipTextEncodeFlux
This description was generated with AI assistance. If you spot any errors, please create an issue on GitHub.
Flux text encoder with separate CLIP-L and T5-XXL prompt inputs.
Inputs
| Parameter | Type | Required | Description |
|---|---|---|---|
clip |
CLIP | Yes | CLIP text encoder (dual CLIP-L + T5-XXL) |
clip_l_positive |
STRING | Yes | CLIP-L positive prompt (multiline) |
t5xxl_positive |
STRING | Yes | T5-XXL positive prompt (multiline) |
clip_l_negative |
STRING | Yes | CLIP-L negative prompt (multiline) |
t5xxl_negative |
STRING | Yes | T5-XXL negative prompt (multiline) |
guidance |
FLOAT | Yes | Guidance scale for Flux (1.0-10.0, default: 3.5) |
Outputs
| Parameter | Type | Description |
|---|---|---|
POSITIVE |
CONDITIONING | Positive conditioning from both encoders |
NEGATIVE |
CONDITIONING | Negative conditioning from both encoders |
Usage
Encode text prompts for Flux with fine-grained control over CLIP-L and T5-XXL inputs separately. Useful when you want different prompts for each encoder or need precise control over the conditioning process.