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Improved documentation, fixed nodes counter

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TenserTensor
2026-03-03 17:34:43 +03:00
parent 92c793de78
commit faefd6a0f3
7 changed files with 151 additions and 41 deletions
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README.md
+9 -14
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@@ -19,20 +19,15 @@ combining frequently used node chains into single, convenient loaders.
## Features
- **Workflow settings nodes** - configure entire workflow parameters (basic and advanced variants)
- **All-in-one model loaders** - load checkpoint, LoRAs, CLIP, and VAE in single nodes
- **Latent factory** - generate latents with aspect ratio, megapixel count, orientation, and type selection (Flux/SDXL)
- **Context nodes** - from Basic to Even Larger Context
- Basic: combines latent, model, CLIP, VAE, and workflow config into context
- Others: pass-through nodes that modify specific context values while preserving the rest
- **CLIP text encoders** - context-based and prompt-based encoding with model-specific controls
- **KSamplers** - Different implementations of KSampler for generating images. Accepts all common sampling parameters
and returns a denoised latent ready for VAE decoding.
- **VAE decoders** - basic, context-based, extended, and two-pass (draft + refinement)
- **Post-production tools** - image adjustments (brightness, contrast, saturation), color correction (apply LUT), film
grain, upscaler
- All-in-one post-production node combining all tools
- Simplified version without adjustments
- **Workflow settings** — configure global workflow parameters for FLUX and SDXL
- **Model loaders** — all-in-one loaders for checkpoint, LoRA, CLIP, and VAE
- **Context nodes** — pass pipeline state between nodes as a single context object
- **Latent factory** — create latents with aspect ratio, megapixel, and model type selection
- **CLIP text encoders** — prompt encoding with model-specific controls for FLUX and SDXL
- **Samplers** — KSampler variants including guided sampling with Guider/Sigmas support
- **Image tools** — load, resize, upscale, preview, and save images
- **VAE** — encode and decode with tiled and context-based variants
- **Post-production** — brightness, contrast, saturation, LUT, film grain, and upscaling
## Installation
node_mappings.py
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@@ -11,10 +11,10 @@ WHITE = "\033[37m"
BRIGHT_GREEN = "\033[92m"
BRIGHT_CYAN = "\033[96m"
NODES_COUNT = 0
import inspect
import sys
try:
before = set(dir())
from .nodes_context import *
from .nodes.context.base_context import TT_BaseContext
from .nodes.context.context import TT_Context
@@ -25,41 +25,30 @@ try:
from .nodes.context.even_larger_context import TT_EvenLargerContext
from .nodes.context.large_context_flux import TT_LargeContextFlux
from .nodes.context.large_context_sdxl import TT_LargeContextSdxl
NODES_COUNT += len(set(dir()) - before)
except ImportError:
print(f"{YELLOW}TenserTensor: {RED}ERROR: Image nodes unavailable{RESET}")
try:
before = set(dir())
from .nodes.image.image_preview_save import TT_ImagePreviewSave
from .nodes.image.image_preview_upscale_save import TT_ImagePreviewUpscaleSave
from .nodes.image.guider_image_reference import TT_GuiderImageReference
from .nodes_image import *
NODES_COUNT += len(set(dir()) - before)
except ImportError:
print(f"{YELLOW}TenserTensor: {RED}ERROR: Image nodes unavailable{RESET}")
try:
before = set(dir())
from .nodes.latent.latent_factory import TT_LatentFactory
from .nodes_latent import *
NODES_COUNT += len(set(dir()) - before)
except ImportError:
print(f"{YELLOW}TenserTensor: {RED}ERROR: Latent nodes unavailable{RESET}")
try:
before = set(dir())
from .nodes.loaders.flux_models_loader import TT_FluxModelsLoader
from .nodes.loaders.flux_models_loader_advanced import TT_FluxModelsLoaderAdvanced
from .nodes.loaders.gguf_models_loader import TT_Flux2GgufModelsLoader
from .nodes.loaders.gguf_models_loader_advanced import TT_Flux2GgufModelsLoaderAdvanced
from .nodes.loaders.sdxl_models_loader import TT_SdxlModelsLoader
from .nodes.loaders.sdxl_models_loader_advanced import TT_SdxlModelsLoaderAdvanced
NODES_COUNT += len(set(dir()) - before)
except ImportError:
print(f"{YELLOW}TenserTensor: {RED}ERROR: Loader nodes unavailable{RESET}")
@@ -71,44 +60,33 @@ try:
from .nodes.postproduction.postproduction import TT_Postproduction
from .nodes.postproduction.postproduction_advanced import TT_PostproductionAdvanced
from .nodes.postproduction.quick_image_upscaler import TT_QuickImageUpscaler
NODES_COUNT += len(set(dir()) - before)
except ImportError:
print(f"{YELLOW}TenserTensor: {RED}ERROR: Postproduction nodes unavailable{RESET}")
try:
before = set(dir())
from .nodes.sampling.ksampler import TT_KSampler
from .nodes.sampling.ksampler_advanced import TT_KSamplerAdvanced
from .nodes.sampling.ksampler_context import TT_KSamplerContext
from .nodes.sampling.ksampler_two_stage import TT_KSamplerTwoStage
from .nodes.sampling.ksampler_guided import TT_KSamplerGuided
NODES_COUNT += len(set(dir()) - before)
except ImportError:
print("f{YELLOW}TenserTensor: {RED}ERROR: Sampler nodes unavailable{RESET}")
try:
before = set(dir())
from .nodes.text_encoders.clip_text_encode_flux import TT_ClipTextEncodeFlux
from .nodes.text_encoders.clip_text_encode_flux_context import TT_ClipTextEncodeFluxContext
from .nodes.text_encoders.clip_text_encode_sdxl import TT_ClipTextEncodeSdxl
from .nodes.text_encoders.clip_text_encode_sdxl_context import TT_ClipTextEncodeSdxlContext
from .nodes.text_encoders.clip_text_encode_flux2 import TT_ClipTextEncodeFlux2
from .nodes.text_encoders.clip_text_encode_flux2_context import TT_ClipTextEncodeFlux2Context
NODES_COUNT += len(set(dir()) - before)
except ImportError:
print(f"{YELLOW}TenserTensor: {RED}ERROR: Text Encoder nodes unavailable{RESET}")
try:
before = set(dir())
from .nodes.vae.vae_decode_context import TT_VaeDecodeContext
from .nodes.vae.vae_decode_tiled import TT_VaeDecodeTiled
from .nodes.vae.vae_encode_context import TT_VaeEncodeContext
from .nodes.vae.vae_encode_tiled import TT_VaeEncodeTiled
NODES_COUNT += len(set(dir()) - before)
except ImportError:
print(f"{YELLOW}TenserTensor: {RED}ERROR: VAE nodes unavailable{RESET}")
@@ -121,11 +99,17 @@ try:
from .nodes.workflow.flux2_workflow_settings import TT_Flux2WorkflowSettings
from .nodes.workflow.flux2_workflow_settings_advanced import TT_Flux2WorkflowSettingsAdvanced
from .nodes_workflow import *
NODES_COUNT += len(set(dir()) - before)
except ImportError:
print(f"{YELLOW}TenserTensor: {RED}ERROR: Workflow nodes unavailable{RESET}")
ADDED = {
name
for name, obj
in inspect.getmembers(sys.modules[__name__], inspect.isclass)
if name.startswith("TT_")
}
NODES_COUNT = len(ADDED)
NODE_CLASS_MAPPINGS = {
# Context Deprecated
"TT_BaseContext": TT_BaseContext,
web/docs/TT_BaseContextPassthroughNode.md → web/docs/TT_ContextPassthroughNode.md
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@@ -1,4 +1,4 @@
## TT Base Context Passthrough *TT_BaseContextPassthroughNode*
## TT Context Passthrough *TT_ContextPassthroughNode*
*This description was generated with AI assistance. If you spot any errors, please create an issue on GitHub.*
web/docs/TT_GuiderImageReferenceNode.md
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@@ -0,0 +1,31 @@
## TT Guider Image Reference *TT_GuiderImageReferenceNode*
*This description was generated with AI assistance. If you spot any errors, please create an issue on GitHub.*
Encodes a reference image into latent space and injects it into a guider's conditioning as reference latents. Useful for image-guided sampling workflows.
### Inputs
| Parameter | Type | Required | Description |
|---|---|---|---|
| `vae` | VAE | Yes | VAE model for encoding the reference image |
| `guider` | GUIDER | Yes | Guider to inject reference latents into |
| `megapixels` | COMBO | Yes | Target resolution for resizing before encoding |
| `resize_method` | COMBO | No | Interpolation method for resizing (advanced) |
| `dimension_step` | INT | No | Align output dimensions to this step size, 1-256 (advanced) |
| `image` | COMBO | Yes | Reference image file to load, with upload support |
### Outputs
| Parameter | Type | Description |
|---|---|---|
| `VAE` | VAE | Passthrough of the input VAE |
| `GUIDER` | GUIDER | Guider with reference latents injected into conditioning |
### Usage
Load a reference image, resize it to the target resolution, encode it with the VAE, and inject the resulting latents into the guider's conditioning. Connect the output `GUIDER` to a sampler to use image-guided sampling.
---
[View on GitHub](https://github.com/tenser-tensor/ComfyUI-TenserTensor)
web/docs/TT_ImageLoaderResizerNode.md
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@@ -0,0 +1,32 @@
## TT Image Loader / Resizer *TT_ImageLoaderResizerNode*
*This description was generated with AI assistance. If you spot any errors, please create an issue on GitHub.*
Loads an image from the input directory with optional resizing to a target megapixel count and alpha mask extraction.
### Inputs
| Parameter | Type | Required | Description |
|------------------|---------|----------|-----------------------------------------------------------------------|
| `resize_image` | BOOLEAN | Yes | Scale image to target megapixels (Scale) or keep original size (Keep) |
| `resize_method` | COMBO | No | Interpolation method for resizing (advanced) |
| `dimension_step` | INT | No | Align output dimensions to this step size, 1–256 (advanced) |
| `megapixels` | COMBO | No | Target resolution in megapixels (advanced) |
| `create_mask` | BOOLEAN | Yes | Extract alpha channel as mask (Mask) or return empty mask (Empty) |
| `image` | COMBO | Yes | Image file to load, with upload support |
### Outputs
| Parameter | Type | Description |
|-----------|-------|----------------------------------------------------|
| `IMAGE` | IMAGE | Loaded (and optionally resized) image tensor |
| `MASK` | MASK | Alpha channel mask, or empty mask if not extracted |
### Usage
Load an image from the input directory and optionally resize it to a target megapixel count. When resizing is enabled, both the image and mask are
scaled together. Use `dimension_step` to snap output dimensions to a specific grid — useful for models that require dimensions divisible by 8 or 64.
---
[View on GitHub](https://github.com/tenser-tensor/ComfyUI-TenserTensor)
web/docs/TT_ImagePreviewSaveNode.md
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## TT Image Preview / Save *TT_ImagePreviewSaveNode*
*This description was generated with AI assistance. If you spot any errors, please create an issue on GitHub.*
Previews an image in the node graph and optionally saves it to the output directory.
### Inputs
| Parameter | Type | Required | Description |
|---------------------|---------|----------|----------------------------------------------------------------|
| `image` | IMAGE | Yes | Image to preview and optionally save |
| `save_image` | BOOLEAN | Yes | Save image to disk (Save image) or preview only (Only preview) |
| `filename_prefix` | STRING | Yes | Prefix for the output filename (default: TT) |
| `filename_format` | COMBO | No | Filename format pattern (advanced) |
| `subfolder` | STRING | No | Subfolder within the output directory (advanced) |
| `image_format` | COMBO | No | Output file format: PNG, JPEG, WEBP (advanced) |
| `image_quality` | INT | No | JPEG quality, 1-100 (advanced) |
| `compression_level` | INT | No | PNG compression level, 0-9 (advanced) |
### Outputs
This node has no outputs. It is a terminal output node.
### Usage
Place at the end of a workflow to preview the result and optionally save it to disk. When saving is disabled, the image is still visible in the node
graph as a preview. Use `subfolder` to organize outputs into subdirectories, and `filename_format` to control how files are named.
---
[View on GitHub](https://github.com/tenser-tensor/ComfyUI-TenserTensor)
web/docs/TT_ImagePreviewUpscaleSaveNode.md
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@@ -0,0 +1,37 @@
## TT Image Preview / Upscale / Save *TT_ImagePreviewUpscaleSaveNode*
*This description was generated with AI assistance. If you spot any errors, please create an issue on GitHub.*
Previews an image in the node graph with optional upscaling via a dedicated upscale model and optional saving to the output directory.
### Inputs
| Parameter | Type | Required | Description |
|---------------------|---------|----------|-------------------------------------------------------------------------------|
| `image` | IMAGE | Yes | Image to preview, upscale, and optionally save |
| `save_image` | BOOLEAN | Yes | Save image to disk (Save image) or preview only (Only preview) |
| `upscale_image` | BOOLEAN | Yes | Upscale image before saving (Upscale image) or keep original size (Keep size) |
| `filename_prefix` | STRING | Yes | Prefix for the output filename (default: TT) |
| `filename_format` | COMBO | No | Filename format pattern (advanced) |
| `subfolder` | STRING | No | Subfolder within the output directory (advanced) |
| `image_format` | COMBO | No | Output file format: PNG, JPEG, WEBP (advanced) |
| `image_quality` | INT | No | JPEG quality, 1-100 (advanced) |
| `compression_level` | INT | No | PNG compression level, 0-9 (advanced) |
| `upscaler_device` | COMBO | No | Device to run the upscale model on (advanced) |
| `upscale_model` | COMBO | No | Upscale model to use (advanced) |
| `upscale_tile` | INT | No | Tile size for tiled upscaling, 128-4096 (advanced) |
| `upscale_overlap` | INT | No | Overlap between tiles in pixels, 8-256 (advanced) |
### Outputs
This node has no outputs. It is a terminal output node.
### Usage
Place at the end of a workflow to upscale, preview, and optionally save the result. When upscaling is enabled, the image is processed through the
selected upscale model before saving. Tiled upscaling is used to handle large images with limited VRAM — reduce `upscale_tile` if you run into
out-of-memory errors.
---
[View on GitHub](https://github.com/tenser-tensor/ComfyUI-TenserTensor)