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