update README.md
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Dr.Lt.Data
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## Custom Nodes
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* [Detectors](https://github.com/ltdrdata/ComfyUI-extension-tutorials/blob/Main/ComfyUI-Impact-Pack/tutorial/detectors.md)
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* SAMLoader - Loads the SAM model.
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* UltralyticsDetectorProvider - Loads the Ultralystics model to provide SEGM_DETECTOR, BBOX_DETECTOR.
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### [Detector nodes](https://github.com/ltdrdata/ComfyUI-extension-tutorials/blob/Main/ComfyUI-Impact-Pack/tutorial/detectors.md)
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* `SAMLoader` - Loads the SAM model.
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* `UltralyticsDetectorProvider` - Loads the Ultralystics model to provide SEGM_DETECTOR, BBOX_DETECTOR.
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- Unlike `MMDetDetectorProvider`, for segm models, `BBOX_DETECTOR` is also provided.
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- The various models available in UltralyticsDetectorProvider can be downloaded through **ComfyUI-Manager**.
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* ONNXDetectorProvider - Loads the ONNX model to provide BBOX_DETECTOR.
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* CLIPSegDetectorProvider - Wrapper for CLIPSeg to provide BBOX_DETECTOR.
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* `ONNXDetectorProvider` - Loads the ONNX model to provide BBOX_DETECTOR.
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* `CLIPSegDetectorProvider` - Wrapper for CLIPSeg to provide BBOX_DETECTOR.
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* You need to install the ComfyUI-CLIPSeg node extension.
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* SEGM Detector (combined) - Detects segmentation and returns a mask from the input image.
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* BBOX Detector (combined) - Detects bounding boxes and returns a mask from the input image.
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* SAMDetector (combined) - Utilizes the SAM technology to extract the segment at the location indicated by the input SEGS on the input image and outputs it as a unified mask.
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* SAMDetector (Segmented) - It is similar to `SAMDetector (combined)`, but it separates and outputs the detected segments. Multiple segments can be found for the same detected area, and currently, a policy is in place to group them arbitrarily in sets of three. This aspect is expected to be improved in the future.
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* `SEGM Detector (combined)` - Detects segmentation and returns a mask from the input image.
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* `BBOX Detector (combined)` - Detects bounding boxes and returns a mask from the input image.
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* `SAMDetector (combined)` - Utilizes the SAM technology to extract the segment at the location indicated by the input SEGS on the input image and outputs it as a unified mask.
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* `SAMDetector (Segmented)` - It is similar to `SAMDetector (combined)`, but it separates and outputs the detected segments. Multiple segments can be found for the same detected area, and currently, a policy is in place to group them arbitrarily in sets of three. This aspect is expected to be improved in the future.
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* As a result, it outputs the `combined_mask`, which is a unified mask, and `batch_masks`, which are multiple masks grouped together in batch form.
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* While `batch_masks` may not be completely separated, it provides functionality to perform some level of segmentation.
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* Simple Detector (SEGS) - Operating primarily with `BBOX_DETECTOR`, and with the additional provision of `SAM_MODEL` or `SEGM_DETECTOR`, this node internally generates improved SEGS through mask operations on both *bbox* and *silhouette*. It serves as a convenient tool to simplify a somewhat intricate workflow.
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* `Simple Detector (SEGS)` - Operating primarily with `BBOX_DETECTOR`, and with the additional provision of `SAM_MODEL` or `SEGM_DETECTOR`, this node internally generates improved SEGS through mask operations on both *bbox* and *silhouette*. It serves as a convenient tool to simplify a somewhat intricate workflow.
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* ControlNet, IPAdapter
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* ControlNetApply (SEGS) - To apply ControlNet in SEGS, you need to use the Preprocessor Provider node from the Inspire Pack to utilize this node.
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### ControlNet, IPAdapter
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* `ControlNetApply (SEGS)` - To apply ControlNet in SEGS, you need to use the Preprocessor Provider node from the Inspire Pack to utilize this node.
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* `segs_preprocessor` and `control_image` can be selectively applied. If an `control_image` is given, `segs_preprocessor` will be ignored.
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* If set to `control_image`, you can preview the cropped cnet image through `SEGSPreview (CNET Image)`. Images generated by `segs_preprocessor` should be verified through the `cnet_images` output of each Detailer.
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* The `segs_preprocessor` operates by applying preprocessing on-the-fly based on the cropped image during the detailing process, while `control_image` will be cropped and used as input to `ControlNetApply (SEGS)`.
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* ControlNetClear (SEGS) - Clear applied ControlNet in SEGS
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* IPAdapterApply (SEGS) - To apply IPAdapter in SEGS, you need to use the Preprocessor Provider node from the Inspire Pack to utilize this node.
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* `ControlNetClear (SEGS)` - Clear applied ControlNet in SEGS
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* `IPAdapterApply (SEGS)` - To apply IPAdapter in SEGS, you need to use the Preprocessor Provider node from the Inspire Pack to utilize this node.
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* Bitwise(SEGS & SEGS) - Performs a 'bitwise and' operation between two SEGS.
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* Bitwise(SEGS - SEGS) - Subtracts one SEGS from another.
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* Bitwise(SEGS & MASK) - Performs a bitwise AND operation between SEGS and MASK.
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* Bitwise(SEGS & MASKS ForEach) - Performs a bitwise AND operation between SEGS and MASKS.
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* Please note that this operation is performed with batches of MASKS, not just a single MASK.
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* Bitwise(MASK & MASK) - Performs a 'bitwise and' operation between two masks.
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* Bitwise(MASK - MASK) - Subtracts one mask from another.
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* Bitwise(MASK + MASK) - Combine two masks.
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* SEGM Detector (SEGS) - Detects segmentation and returns SEGS from the input image.
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* BBOX Detector (SEGS) - Detects bounding boxes and returns SEGS from the input image.
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### Mask operation
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* `Bitwise(SEGS & SEGS)` - Performs a 'bitwise and' operation between two SEGS.
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* `Bitwise(SEGS - SEGS)` - Subtracts one SEGS from another.
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* `Bitwise(SEGS & MASK)` - Performs a bitwise AND operation between SEGS and MASK.
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* `Bitwise(SEGS & MASKS ForEach)` - Performs a bitwise AND operation between SEGS and MASKS.
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* Please note that this operation is performed with batches of MASKS, not just a single MASK.
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* `Bitwise(MASK & MASK)` - Performs a 'bitwise and' operation between two masks.
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* `Bitwise(MASK - MASK)` - Subtracts one mask from another.
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* `Bitwise(MASK + MASK)` - Combine two masks.
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* `SEGM Detector (SEGS)` - Detects segmentation and returns SEGS from the input image.
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* `BBOX Detector (SEGS)` - Detects bounding boxes and returns SEGS from the input image.
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* `Dilate Mask` - Dilate Mask.
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* Support erosion for negative value.
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* `Gaussian Blur Mask` - Apply Gaussian Blur to Mask. You can utilize this for mask feathering.
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* Detailer
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* Detailer (SEGS) - Refines the image based on SEGS.
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* DetailerDebug (SEGS) - Refines the image based on SEGS. Additionally, it provides the ability to monitor the cropped image and the refined image of the cropped image.
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### [Detailer nodes](https://github.com/ltdrdata/ComfyUI-extension-tutorials/blob/Main/ComfyUI-Impact-Pack/tutorial/detailers.md)
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* `Detailer (SEGS)` - Refines the image based on SEGS.
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* `DetailerDebug (SEGS)` - Refines the image based on SEGS. Additionally, it provides the ability to monitor the cropped image and the refined image of the cropped image.
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* To prevent regeneration caused by the seed that does not change every time when using 'external_seed', please disable the 'seed random generate' option in the 'Detailer...' node.
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* MASK to SEGS - Generates SEGS based on the mask.
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* MASK to SEGS For AnimateDiff - Generates SEGS based on the mask for AnimateDiff.
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* MediaPipe FaceMesh to SEGS - Separate each landmark from the mediapipe facemesh image to create labeled SEGS.
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* `MASK to SEGS` - Generates SEGS based on the mask.
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* `MASK to SEGS For AnimateDiff` - Generates SEGS based on the mask for AnimateDiff.
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* `MediaPipe FaceMesh to SEGS` - Separate each landmark from the mediapipe facemesh image to create labeled SEGS.
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* Usually, the size of images created through the MediaPipe facemesh preprocessor is downscaled. It resizes the MediaPipe facemesh image to the original size given as reference_image_opt for matching sizes during processing.
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* ToBinaryMask - Separates the mask generated with alpha values between 0 and 255 into 0 and 255. The non-zero parts are always set to 255.
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* Masks to Mask List - This node converts the MASKS in batch form to a list of individual masks.
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* Mask List to Masks - This node converts the MASK list to MASK batch form.
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* EmptySEGS - Provides an empty SEGS.
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* MaskPainter - Provides a feature to draw masks.
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* FaceDetailer - Easily detects faces and improves them.
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* FaceDetailer (pipe) - Easily detects faces and improves them (for multipass).
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* MaskDetailer (pipe) - This is a simple inpaint node that applies the Detailer to the mask area.
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* `ToBinaryMask` - Separates the mask generated with alpha values between 0 and 255 into 0 and 255. The non-zero parts are always set to 255.
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* `Masks to Mask List` - This node converts the MASKS in batch form to a list of individual masks.
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* `Mask List to Masks` - This node converts the MASK list to MASK batch form.
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* `EmptySEGS` - Provides an empty SEGS.
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* `MaskPainter` - Provides a feature to draw masks.
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* `FaceDetailer` - Easily detects faces and improves them.
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* `FaceDetailer (pipe)` - Easily detects faces and improves them (for multipass).
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* `MaskDetailer (pipe)` - This is a simple inpaint node that applies the Detailer to the mask area.
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* `FromDetailer (SDXL/pipe), BasicPipe -> DetailerPipe (SDXL), Edit DetailerPipe (SDXL)` - These are pipe functions used in Detailer for utilizing the refiner model of SDXL.
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* `FromDetailer (SDXL/pipe)`, `BasicPipe -> DetailerPipe (SDXL)`, `Edit DetailerPipe (SDXL)` - These are pipe functions used in Detailer for utilizing the refiner model of SDXL.
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* SEGS Manipulation nodes
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* SEGSDetailer - Performs detailed work on SEGS without pasting it back onto the original image.
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* SEGSPaste - Pastes the results of SEGS onto the original image.
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### SEGS Manipulation nodes
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* `SEGSDetailer` - Performs detailed work on SEGS without pasting it back onto the original image.
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* `SEGSPaste` - Pastes the results of SEGS onto the original image.
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* If `ref_image_opt` is present, the images contained within SEGS are ignored. Instead, the image within `ref_image_opt` corresponding to the crop area of SEGS is taken and pasted. The size of the image in `ref_image_opt` should be the same as the original image size.
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* This node can be used in conjunction with the processing results of AnimateDiff.
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* SEGSPreview - Provides a preview of SEGS.
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* `SEGSPreview` - Provides a preview of SEGS.
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* This option is used to preview the improved image through `SEGSDetailer` before merging it into the original. Prior to going through ```SEGSDetailer```, SEGS only contains mask information without image information. If fallback_image_opt is connected to the original image, SEGS without image information will generate a preview using the original image. However, if SEGS already contains image information, fallback_image_opt will be ignored.
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* This node can be used in conjunction with the processing results of AnimateDiff.
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* SEGSPreview (CNET Image) - Show images configured with `ControlNetApply (SEGS)` for debugging purposes.
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* SEGSToImageList - Convert SEGS To Image List
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* SEGSToMaskList - Convert SEGS To Mask List
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* SEGS Filter (label) - This node filters SEGS based on the label of the detected areas.
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* SEGS Filter (ordered) - This node sorts SEGS based on size and position and retrieves SEGs within a certain range.
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* SEGS Filter (range) - This node retrieves only SEGs from SEGS that have a size and position within a certain range.
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* SEGS Assign (label) - Assign labels sequentially to SEGS. This node is useful when used with `[LAB]` of FaceDetailer.
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* SEGSConcat - Concatenate segs1 and segs2. If source shape of segs1 and segs2 are different from segs2 will be ignored.
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* Picker (SEGS) - Among the input SEGS, you can select a specific SEG through a dialog. If no SEG is selected, it outputs an empty SEGS. Increasing the batch_size of SEGSDetailer can be used for the purpose of selecting from the candidates.
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* Set Default Image For SEGS - Set a default image for SEGS. SEGS with images set this way do not need to have a fallback image set. When override is set to false, the original image is preserved.
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* Remove Image from SEGS - Remove the image set for the SEGS that has been configured by "Set Default Image for SEGS" or SEGSDetailer. When the image for the SEGS is removed, the Detailer node will operate based on the currently processed image instead of the SEGS.
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* Make Tile SEGS - [experimental] Create SEGS in the form of tiles from an image to facilitate experiments for Tiled Upscale using the Detailer.
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* `SEGSPreview (CNET Image)` - Show images configured with `ControlNetApply (SEGS)` for debugging purposes.
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* `SEGSToImageList` - Convert SEGS To Image List
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* `SEGSToMaskList` - Convert SEGS To Mask List
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* `SEGS Filter (label)` - This node filters SEGS based on the label of the detected areas.
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* `SEGS Filter (ordered)` - This node sorts SEGS based on size and position and retrieves SEGs within a certain range.
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* `SEGS Filter (range)` - This node retrieves only SEGs from SEGS that have a size and position within a certain range.
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* `SEGS Assign (label)` - Assign labels sequentially to SEGS. This node is useful when used with `[LAB]` of FaceDetailer.
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* `SEGSConcat` - Concatenate segs1 and segs2. If source shape of segs1 and segs2 are different from segs2 will be ignored.
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* `Picker (SEGS)` - Among the input SEGS, you can select a specific SEG through a dialog. If no SEG is selected, it outputs an empty SEGS. Increasing the batch_size of SEGSDetailer can be used for the purpose of selecting from the candidates.
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* `Set Default Image For SEGS` - Set a default image for SEGS. SEGS with images set this way do not need to have a fallback image set. When override is set to false, the original image is preserved.
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* `Remove Image from SEGS` - Remove the image set for the SEGS that has been configured by "Set Default Image for SEGS" or SEGSDetailer. When the image for the SEGS is removed, the Detailer node will operate based on the currently processed image instead of the SEGS.
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* `Make Tile SEGS` - [experimental] Create SEGS in the form of tiles from an image to facilitate experiments for Tiled Upscale using the Detailer.
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* The `filter_in_segs_opt` and `filter_out_segs_opt` are optional inputs. If these inputs are provided, when creating the tiles, the mask for each tile is generated by overlapping with the mask of `filter_in_segs_opt` and excluding the overlap with the mask of `filter_out_segs_opt`. Tiles with an empty mask will not be created as SEGS.
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* Dilate Mask (SEGS) - Dilate/Erosion Mask in SEGS
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* Gaussian Blur Mask (SEGS) - Apply Gaussian Blur to Mask in SEGS
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* SEGS_ELT Manipulation - experimental nodes
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* DecomposeSEGS - Decompose SEGS to allow for detailed manipulation.
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* AssembleSEGS - Reassemble the decomposed SEGS.
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* From SEG_ELT - Extract detailed information from SEG_ELT.
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* Edit SEG_ELT - Modify some of the information in SEG_ELT.
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* Dilate SEG_ELT - Dilate the mask of SEG_ELT.
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* From SEG_ELT bbox - Extract coordinate from bbox in SEG_ELT
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* From SEG_ELT crop_region - Extract coordinate from crop_region in SEG_ELT
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* Mask Manipulation
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* Dilate Mask - Dilate Mask.
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* Support erosion for negative value.
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* Gaussian Blur Mask - Apply Gaussian Blur to Mask. You can utilize this for mask feathering.
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* `Dilate Mask (SEGS)` - Dilate/Erosion Mask in SEGS
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* `Gaussian Blur Mask (SEGS)` - Apply Gaussian Blur to Mask in SEGS
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* `SEGS_ELT Manipulation` - experimental nodes
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* `DecomposeSEGS` - Decompose SEGS to allow for detailed manipulation.
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* `AssembleSEGS` - Reassemble the decomposed SEGS.
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* `From SEG_ELT` - Extract detailed information from SEG_ELT.
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* `Edit SEG_ELT` - Modify some of the information in SEG_ELT.
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* `Dilate SEG_ELT` - Dilate the mask of SEG_ELT.
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* `From SEG_ELT` bbox - Extract coordinate from bbox in SEG_ELT
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* `From SEG_ELT` crop_region - Extract coordinate from crop_region in SEG_ELT
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* Pipe nodes
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* ToDetailerPipe, FromDetailerPipe - These nodes are used to bundle multiple inputs used in the detailer, such as models and vae, ..., into a single DETAILER_PIPE or extract the elements that are bundled in the DETAILER_PIPE.
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* ToBasicPipe, FromBasicPipe - These nodes are used to bundle model, clip, vae, positive conditioning, and negative conditioning into a single BASIC_PIPE, or extract each element from the BASIC_PIPE.
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* EditBasicPipe, EditDetailerPipe - These nodes are used to replace some elements in BASIC_PIPE or DETAILER_PIPE.
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* FromDetailerPipe_v2, FromBasicPipe_v2 - It has the same functionality as `FromDetailerPipe` and `FromBasicPipe`, but it has an additional output that directly exports the input pipe. It is useful when editing EditBasicPipe and EditDetailerPipe.
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* Latent Scale (on Pixel Space) - This node converts latent to pixel space, upscales it, and then converts it back to latent.
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### Pipe nodes
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* `ToDetailerPipe`, `FromDetailerPipe` - These nodes are used to bundle multiple inputs used in the detailer, such as models and vae, ..., into a single DETAILER_PIPE or extract the elements that are bundled in the DETAILER_PIPE.
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* `ToBasicPipe`, `FromBasicPipe` - These nodes are used to bundle model, clip, vae, positive conditioning, and negative conditioning into a single BASIC_PIPE, or extract each element from the BASIC_PIPE.
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* `EditBasicPipe`, `EditDetailerPipe` - These nodes are used to replace some elements in BASIC_PIPE or DETAILER_PIPE.
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* `FromDetailerPipe_v2`, `FromBasicPipe_v2` - It has the same functionality as `FromDetailerPipe` and `FromBasicPipe`, but it has an additional output that directly exports the input pipe. It is useful when editing EditBasicPipe and EditDetailerPipe.
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* `Latent Scale (on Pixel Space)` - This node converts latent to pixel space, upscales it, and then converts it back to latent.
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* If upscale_model_opt is provided, it uses the model to upscale the pixel and then downscales it using the interpolation method provided in scale_method to the target resolution.
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* PixelKSampleUpscalerProvider - An upscaler is provided that converts latent to pixels using VAEDecode, performs upscaling, converts back to latent using VAEEncode, and then performs k-sampling. This upscaler can be attached to nodes such as 'Iterative Upscale' for use.
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* Similar to 'Latent Scale (on Pixel Space)', if upscale_model_opt is provided, it performs pixel upscaling using the model.
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* PixelTiledKSampleUpscalerProvider - It is similar to PixelKSampleUpscalerProvider, but it uses ComfyUI_TiledKSampler and Tiled VAE Decoder/Encoder to avoid GPU VRAM issues at high resolutions.
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* `PixelKSampleUpscalerProvider` - An upscaler is provided that converts latent to pixels using VAEDecode, performs upscaling, converts back to latent using VAEEncode, and then performs k-sampling. This upscaler can be attached to nodes such as `Iterative Upscale` for use.
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* Similar to `Latent Scale (on Pixel Space)`, if upscale_model_opt is provided, it performs pixel upscaling using the model.
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* `PixelTiledKSampleUpscalerProvider` - It is similar to `PixelKSampleUpscalerProvider`, but it uses `ComfyUI_TiledKSampler` and Tiled VAE Decoder/Encoder to avoid GPU VRAM issues at high resolutions.
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* You need to install the [BlenderNeko/ComfyUI_TiledKSampler](https://github.com/BlenderNeko/ComfyUI_TiledKSampler) node extension.
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* PK_HOOK
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* DenoiseScheduleHookProvider - IterativeUpscale provides a hook that gradually changes the denoise to target_denoise as the iterative-step progresses.
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* CfgScheduleHookProvider - IterativeUpscale provides a hook that gradually changes the cfg to target_cfg as the iterative-step progresses.
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* StepsScheduleHookProvider - IterativeUpscale provides a hook that gradually changes the sampling-steps to target_steps as the iterative-step progresses.
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* NoiseInjectionHookProvider - During each iteration of IterativeUpscale, noise is injected into the latent space while varying the strength according to a schedule.
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### PK_HOOK
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* `DenoiseScheduleHookProvider` - IterativeUpscale provides a hook that gradually changes the denoise to target_denoise as the iterative-step progresses.
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* `CfgScheduleHookProvider` - IterativeUpscale provides a hook that gradually changes the cfg to target_cfg as the iterative-step progresses.
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* `StepsScheduleHookProvider` - IterativeUpscale provides a hook that gradually changes the sampling-steps to target_steps as the iterative-step progresses.
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* `NoiseInjectionHookProvider` - During each iteration of IterativeUpscale, noise is injected into the latent space while varying the strength according to a schedule.
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* You need to install the [BlenderNeko/ComfyUI_Noise](https://github.com/BlenderNeko/ComfyUI_Noise) node extension.
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* The seed serves as the initial value required for generating noise, and it increments by 1 with each iteration as the process unfolds.
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* The source determines the types of CPU noise and GPU noise to be configured.
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* Currently, there is only a simple schedule available, where the strength of the noise varies from start_strength to end_strength during the progression of each iteration.
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* UnsamplerHookProvider - Apply Unsampler during each iteration. To use this node, ComfyUI_Noise must be installed.
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* PixelKSampleHookCombine - This is used to connect two PK_HOOKs. hook1 is executed first and then hook2 is executed.
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* `UnsamplerHookProvider` - Apply Unsampler during each iteration. To use this node, ComfyUI_Noise must be installed.
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* `PixelKSampleHookCombine` - This is used to connect two PK_HOOKs. hook1 is executed first and then hook2 is executed.
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* If you want to simultaneously change cfg and denoise, you can combine the PK_HOOKs of CfgScheduleHookProvider and PixelKSampleHookCombine.
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* DETAILER_HOOK
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* NoiseInjectionDetailerHookProvider - The `detailer_hook` is a hook in the `Detailer` that injects noise during the processing of each SEGS.
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* UnsamplerDetailerHookProvider - Apply Unsampler during each cycle. To use this node, ComfyUI_Noise must be installed.
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* DenoiseSchedulerDetailerHookProvider - During the progress of the cycle, the detailer's denoise is altered up to the `target_denoise`.
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* CoreMLDetailerHookProvider - CoreML supports only 512x512, 512x768, 768x512, 768x768 size sampling. CoreMLDetailerHookProvider precisely fixes the upscale of the crop_region to this size. When using this hook, it will always be selected size, regardless of the guide_size. However, if the guide_size is too small, skipping will occur.
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* DetailerHookCombine - This is used to connect two DETAILER_HOOKs. Similar to PixelKSampleHookCombine.
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* SEGSOrderedFilterDetailerHook, SEGSRangeFilterDetailerHook, SEGSLabelFilterDetailerHook - There are a wrapper node that provides SEGSFilter nodes to be applied in FaceDetailer or Detector by creating DETAILER_HOOK.
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* PreviewDetailerHook - Connecting this hook node helps provide assistance for viewing previews whenever SEGS Detailing tasks are completed. When working with a large number of SEGS, such as Make Tile SEGS, it allows for monitoring the situation as improvements progress incrementally.
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### DETAILER_HOOK
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* `NoiseInjectionDetailerHookProvider` - The `detailer_hook` is a hook in the `Detailer` that injects noise during the processing of each SEGS.
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* `UnsamplerDetailerHookProvider` - Apply Unsampler during each cycle. To use this node, ComfyUI_Noise must be installed.
|
||||
* `DenoiseSchedulerDetailerHookProvider` - During the progress of the cycle, the detailer's denoise is altered up to the `target_denoise`.
|
||||
* `CoreMLDetailerHookProvider` - CoreML supports only 512x512, 512x768, 768x512, 768x768 size sampling. CoreMLDetailerHookProvider precisely fixes the upscale of the crop_region to this size. When using this hook, it will always be selected size, regardless of the guide_size. However, if the guide_size is too small, skipping will occur.
|
||||
* `DetailerHookCombine` - This is used to connect two DETAILER_HOOKs. Similar to PixelKSampleHookCombine.
|
||||
* `SEGSOrderedFilterDetailerHook`, SEGSRangeFilterDetailerHook, SEGSLabelFilterDetailerHook - There are a wrapper node that provides SEGSFilter nodes to be applied in FaceDetailer or Detector by creating DETAILER_HOOK.
|
||||
* `PreviewDetailerHook` - Connecting this hook node helps provide assistance for viewing previews whenever SEGS Detailing tasks are completed. When working with a large number of SEGS, such as Make Tile SEGS, it allows for monitoring the situation as improvements progress incrementally.
|
||||
* Since this is the hook applied when pasting onto the original image, it has no effect on nodes like `SEGSDetailer`.
|
||||
* VariationNoiseDetailerHookProvider - Apply variation seed to the detailer. It can be applied in multiple stages through combine.
|
||||
* `VariationNoiseDetailerHookProvider` - Apply variation seed to the detailer. It can be applied in multiple stages through combine.
|
||||
|
||||
* Iterative Upscale (Latent/on Pixel Space) - The upscaler takes the input upscaler and splits the scale_factor into steps, then iteratively performs upscaling.
|
||||
This takes latent as input and outputs latent as the result.
|
||||
* Iterative Upscale (Image) - The upscaler takes the input upscaler and splits the scale_factor into steps, then iteratively performs upscaling. This takes image as input and outputs image as the result.
|
||||
* Internally, this node uses 'Iterative Upscale (Latent)'.
|
||||
### Iterative Upscale nodes
|
||||
* `Iterative Upscale (Latent/on Pixel Space)` - The upscaler takes the input upscaler and splits the scale_factor into steps, then iteratively performs upscaling.
|
||||
This takes latent as input and outputs latent as the result.
|
||||
* `Iterative Upscale (Image)` - The upscaler takes the input upscaler and splits the scale_factor into steps, then iteratively performs upscaling. This takes image as input and outputs image as the result.
|
||||
* Internally, this node uses 'Iterative Upscale (Latent)'.
|
||||
|
||||
* TwoSamplersForMask - This node can apply two samplers depending on the mask area. The base_sampler is applied to the area where the mask is 0, while the mask_sampler is applied to the area where the mask is 1.
|
||||
### TwoSamplers nodes
|
||||
* `TwoSamplersForMask` - This node can apply two samplers depending on the mask area. The base_sampler is applied to the area where the mask is 0, while the mask_sampler is applied to the area where the mask is 1.
|
||||
* Note: The latent encoded through VAEEncodeForInpaint cannot be used.
|
||||
* KSamplerProvider - This is a wrapper that enables KSampler to be used in TwoSamplersForMask TwoSamplersForMaskUpscalerProvider.
|
||||
* TiledKSamplerProvider - ComfyUI_TiledKSampler is a wrapper that provides KSAMPLER.
|
||||
* `KSamplerProvider` - This is a wrapper that enables KSampler to be used in TwoSamplersForMask TwoSamplersForMaskUpscalerProvider.
|
||||
* `TiledKSamplerProvider` - ComfyUI_TiledKSampler is a wrapper that provides KSAMPLER.
|
||||
* You need to install the [BlenderNeko/ComfyUI_TiledKSampler](https://github.com/BlenderNeko/ComfyUI_TiledKSampler) node extension.
|
||||
|
||||
* TwoAdvancedSamplersForMask - TwoSamplersForMask is similar to TwoAdvancedSamplersForMask, but they differ in their operation. TwoSamplersForMask performs sampling in the mask area only after all the samples in the base area are finished. On the other hand, TwoAdvancedSamplersForMask performs sampling in both the base area and the mask area sequentially at each step.
|
||||
* KSamplerAdvancedProvider - This is a wrapper that enables KSampler to be used in TwoAdvancedSamplersForMask, RegionalSampler.
|
||||
* `TwoAdvancedSamplersForMask` - TwoSamplersForMask is similar to TwoAdvancedSamplersForMask, but they differ in their operation. TwoSamplersForMask performs sampling in the mask area only after all the samples in the base area are finished. On the other hand, TwoAdvancedSamplersForMask performs sampling in both the base area and the mask area sequentially at each step.
|
||||
* `KSamplerAdvancedProvider` - This is a wrapper that enables KSampler to be used in TwoAdvancedSamplersForMask, RegionalSampler.
|
||||
* sigma_factor: By multiplying the denoise schedule by the sigma_factor, you can adjust the amount of denoising based on the configured denoise.
|
||||
|
||||
* TwoSamplersForMaskUpscalerProvider - This is an Upscaler that extends TwoSamplersForMask to be used in Iterative Upscale.
|
||||
* `TwoSamplersForMaskUpscalerProvider` - This is an Upscaler that extends TwoSamplersForMask to be used in Iterative Upscale.
|
||||
* TwoSamplersForMaskUpscalerProviderPipe - pipe version of TwoSamplersForMaskUpscalerProvider.
|
||||
|
||||
* Image Utils
|
||||
* PreviewBridge (image) - This custom node can be used with a bridge for image when using the MaskEditor feature of Clipspace.
|
||||
* PreviewBridge (latent) - This custom node can be used with a bridge for latent image when using the MaskEditor feature of Clipspace.
|
||||
### Image Utils
|
||||
* `PreviewBridge (image)` - This custom node can be used with a bridge for image when using the MaskEditor feature of Clipspace.
|
||||
* `PreviewBridge (latent)` - This custom node can be used with a bridge for latent image when using the MaskEditor feature of Clipspace.
|
||||
* If a latent with a mask is provided as input, it displays the mask. Additionally, the mask output provides the mask set in the latent.
|
||||
* If a latent without a mask is provided as input, it outputs the original latent as is, but the mask output provides an output with the entire region set as a mask.
|
||||
* When set mask through MaskEditor, a mask is applied to the latent, and the output includes the stored mask. The same mask is also output as the mask output.
|
||||
* When connected to `vae_opt`, it takes higher priority than the `preview_method`.
|
||||
* ImageSender, ImageReceiver - The images generated in ImageSender are automatically sent to the ImageReceiver with the same link_id.
|
||||
* LatentSender, LatentReceiver - The latent generated in LatentSender are automatically sent to the LatentReceiver with the same link_id.
|
||||
* `ImageSender`, `ImageReceiver` - The images generated in ImageSender are automatically sent to the ImageReceiver with the same link_id.
|
||||
* `LatentSender`, `LatentReceiver` - The latent generated in LatentSender are automatically sent to the LatentReceiver with the same link_id.
|
||||
* Furthermore, LatentSender is implemented with PreviewLatent, which stores the latent in payload form within the image thumbnail.
|
||||
* Due to the current structure of ComfyUI, it is unable to distinguish between SDXL latent and SD1.5/SD2.1 latent. Therefore, it generates thumbnails by decoding them using the SD1.5 method.
|
||||
|
||||
|
||||
* Switch nodes
|
||||
* Switch (image,mask), Switch (latent), Switch (SEGS) - Among multiple inputs, it selects the input designated by the selector and outputs it. The first input must be provided, while the others are optional. However, if the input specified by the selector is not connected, an error may occur.
|
||||
* Switch (Any) - This is a Switch node that takes an arbitrary number of inputs and produces a single output. Its type is determined when connected to any node, and connecting inputs increases the available slots for connections.
|
||||
* Inversed Switch (Any) - In contrast to `Switch (Any)`, it takes a single input and outputs one of many. Due to ComfyUI's functional limitations, the value of `select` must be determined at the time of queuing a prompt, and while it can serve as a `Primitive Node` or `ImpactInt`, it cannot function properly when connected through other nodes.
|
||||
### Switch nodes
|
||||
* `Switch (image,mask)`, `Switch (latent)`, `Switch (SEGS)` - Among multiple inputs, it selects the input designated by the selector and outputs it. The first input must be provided, while the others are optional. However, if the input specified by the selector is not connected, an error may occur.
|
||||
* `Switch (Any)` - This is a Switch node that takes an arbitrary number of inputs and produces a single output. Its type is determined when connected to any node, and connecting inputs increases the available slots for connections.
|
||||
* `Inversed Switch (Any)` - In contrast to `Switch (Any)`, it takes a single input and outputs one of many. Due to ComfyUI's functional limitations, the value of `select` must be determined at the time of queuing a prompt, and while it can serve as a `Primitive Node` or `ImpactInt`, it cannot function properly when connected through other nodes.
|
||||
* Guide
|
||||
* When the `Switch (Any)` and `Inversed Switch (Any)` selects are transformed into primitives, it's important to be cautious because the select range is not appropriately constrained, potentially leading to unintended behavior.
|
||||
* `Switch (image,mask)`, `Switch (latent)`, `Switch (SEGS)`, `Switch (Any)` supports `sel_mode` param. The `sel_mode` sets the moment at which the `select` parameter is determined. `select_on_prompt` determines the `select` at the time of queuing the prompt, while `select_on_execution` determines it during the execution of the workflow. While `select_on_execution` offers more flexibility, it can potentially trigger workflow execution errors due to running nodes that may be impossible to execute within the limitations of ComfyUI. `select_on_prompt` bypasses this constraint by treating any inputs not selected as if they were disconnected. However, please note that when using `select_on_prompt`, the `select` can only be used with widgets or `Primitive Nodes` determined at the queue prompt.
|
||||
* There is an issue when connecting the built-in reroute node with the switch's input/output slots. it can lead to forced disconnections during workflow loading. Therefore, it is advisable not to use reroute for making connections in such cases. However, there are no issues when using the reroute node in Pythongossss.
|
||||
|
||||
* [Wildcards](https://github.com/ltdrdata/ComfyUI-extension-tutorials/blob/Main/ComfyUI-Impact-Pack/tutorial/ImpactWildcard.md) - These are nodes that supports syntax in the form of `__wildcard-name__` and dynamic prompt syntax like `{a|b|c}`.
|
||||
### [Wildcards](http://github.com/ltdrdata/ComfyUI-extension-tutorials/blob/Main/ComfyUI-Impact-Pack/tutorial/ImpactWildcard.md) nodes
|
||||
* These are nodes that supports syntax in the form of `__wildcard-name__` and dynamic prompt syntax like `{a|b|c}`.
|
||||
* Wildcard files can be used by placing `.txt` or `.yaml` files under either `ComfyUI-Impact-Pack/wildcards` or `ComfyUI-Impact-Pack/custom_wildcards` paths.
|
||||
* You can download and use [Wildcard YAML](https://civitai.com/models/138970/billions-of-wildcards-all-in-one) files in this format.
|
||||
* After the first execution, you can change the custom wildcards path in the `custom_wildcards` entry within the `ComfyUI-Impact-Pack/impact-pack.ini` file created.
|
||||
* ImpactWildcardProcessor - The text is generated by processing the wildcard in the Text. If the mode is set to "populate", a dynamic prompt is generated with each execution and the input is filled in the second textbox. If the mode is set to "fixed", the content of the second textbox remains unchanged.
|
||||
* `ImpactWildcardProcessor` - The text is generated by processing the wildcard in the Text. If the mode is set to "populate", a dynamic prompt is generated with each execution and the input is filled in the second textbox. If the mode is set to "fixed", the content of the second textbox remains unchanged.
|
||||
* When an image is generated with the "fixed" mode, the prompt used for that particular generation is stored in the metadata.
|
||||
* ImpactWildcardEncode - Similar to ImpactWildcardProcessor, this provides the loading functionality of LoRAs (e.g. `<lora:some_awesome_lora:0.7:1.2>`). Populated prompts are encoded using the clip after all the lora loading is done.
|
||||
* `ImpactWildcardEncode` - Similar to ImpactWildcardProcessor, this provides the loading functionality of LoRAs (e.g. `<lora:some_awesome_lora:0.7:1.2>`). Populated prompts are encoded using the clip after all the lora loading is done.
|
||||
* If the `Inspire Pack` is installed, you can use **Lora Block Weight** in the form of `LBW=lbw spec;`
|
||||
* `<lora:chunli:1.0:1.0:LBW=B11:0,0,0,0,0,0,0,0,0,0,A,0,0,0,0,0,0;A=0.;>`, `<lora:chunli:1.0:1.0:LBW=0,0,0,0,0,0,0,0,0,0,A,B,0,0,0,0,0;A=0.5;B=0.2;>`, `<lora:chunli:1.0:1.0:LBW=SD-MIDD;>`
|
||||
|
||||
* Regional Sampling - These nodes offer the capability to divide regions and perform partial sampling using a mask. Unlike TwoSamplersForMask, sampling for each region is applied during each step.
|
||||
* RegionalPrompt - This node combines a **mask** for specifying regions and the **sampler** to apply to each region to create `REGIONAL_PROMPTS`.
|
||||
* CombineRegionalPrompts - Combine multiple `REGIONAL_PROMPTS` to create a single `REGIONAL_PROMPTS`.
|
||||
* RegionalSampler - This node performs sampling using a base sampler and regional prompts. Sampling by the base sampler is executed at each step, while sampling for each region is performed through the sampler bound to each region.
|
||||
### Regional Sampling
|
||||
* These nodes offer the capability to divide regions and perform partial sampling using a mask. Unlike TwoSamplersForMask, sampling for each region is applied during each step.
|
||||
* `RegionalPrompt` - This node combines a **mask** for specifying regions and the **sampler** to apply to each region to create `REGIONAL_PROMPTS`.
|
||||
* `CombineRegionalPrompts` - Combine multiple `REGIONAL_PROMPTS` to create a single `REGIONAL_PROMPTS`.
|
||||
* `RegionalSampler` - This node performs sampling using a base sampler and regional prompts. Sampling by the base sampler is executed at each step, while sampling for each region is performed through the sampler bound to each region.
|
||||
* overlap_factor - Specifies the amount of overlap for each region to blend well with the area outside the mask.
|
||||
* restore_latent - When sampling each region, restore the areas outside the mask to the base latent, preventing additional noise from being introduced outside the mask during region sampling.
|
||||
* RegionalSamplerAdvanced - This is the Advanced version of the RegionalSampler. You can control it using `step` instead of `denoise`.
|
||||
* NOTE: The `sde` sampler and `uni_pc` sampler introduce additional noise during each step of the sampling process. To mitigate this, when sampling each region, the `uni_pc` sampler applies additional `dpmpp_fast`, and the sde sampler applies the `dpmpp_2m` sampler as an additional measure.
|
||||
* `RegionalSamplerAdvanced` - This is the Advanced version of the RegionalSampler. You can control it using `step` instead of `denoise`.
|
||||
> NOTE: The `sde` sampler and `uni_pc` sampler introduce additional noise during each step of the sampling process. To mitigate this, when sampling each region, the `uni_pc` sampler applies additional `dpmpp_fast`, and the sde sampler applies the `dpmpp_2m` sampler as an additional measure.
|
||||
|
||||
* KSampler (pipe), KSampler (advanced/pipe)
|
||||
### Impact KSampler
|
||||
* These samplers supports basic_pipe and AYS scheduler
|
||||
* `KSampler (pipe)` - pipe version of KSampler
|
||||
* `KSampler (advanced/pipe)` - pipe version of KSamplerAdvacned
|
||||
|
||||
* Image batch To Image List - Convert Image batch to Image List
|
||||
- You can use images generated in a multi batch to handle them
|
||||
* Make Image List - Convert multiple images into a single image list
|
||||
* Make Image Batch - Convert multiple images into a single image batch
|
||||
- The input of images can be scaled up as needed
|
||||
### Batch/List Util
|
||||
* `Image batch To Image List` - Convert Image batch to Image List
|
||||
- You can use images generated in a multi batch to handle them
|
||||
* `Make Image List` - Convert multiple images into a single image list
|
||||
* `Make Image Batch` - Convert multiple images into a single image batch
|
||||
- The input of images can be scaled up as needed
|
||||
|
||||
* String Selector - It selects and returns a portion of the string. When `multiline` mode is disabled, it simply returns the string of the line pointed to by the selector. When `multiline` mode is enabled, it divides the string based on lines that start with `#` and returns them. If the `select` value is larger than the number of items, it will start counting from the first line again and return accordingly.
|
||||
* Combine Conditionings - It takes multiple conditionings as input and combines them into a single conditioning.
|
||||
* Concat Conditionings - It takes multiple conditionings as input and concat them into a single conditioning.
|
||||
|
||||
* Logics (experimental) - These nodes are experimental nodes designed to implement the logic for loops and dynamic switching.
|
||||
* ImpactCompare, ImpactConditionalBranch, ImpactConditionalBranchSelMode, ImpactInt, ImpactValueSender, ImpactValueReceiver, ImpactImageInfo, ImpactMinMax, ImpactNeg, ImpactConditionalStopIteration
|
||||
* ImpactIsNotEmptySEGS - This node returns `true` only if the input SEGS is not empty.
|
||||
* Queue Trigger - When this node is executed, it adds a new queue to assist with repetitive tasks. It will only execute if the signal's status changes.
|
||||
* Queue Trigger (Countdown) - Like the Queue Trigger, it adds a queue, but only adds it if it's greater than 1, and decrements the count by one each time it runs.
|
||||
* Sleep - Waits for the specified time (in seconds).
|
||||
* Set Widget Value - This node sets one of the optional inputs to the specified node's widget. An error may occur if the types do not match.
|
||||
* Set Mute State - This node changes the mute state of a specific node.
|
||||
* Control Bridge - This node modifies the state of the connected control nodes based on the `mode` and `behavior` . If there are nodes that require a change, the current execution is paused, the mute status is updated, and a new prompt queue is inserted.
|
||||
### Logics (experimental)
|
||||
* These nodes are experimental nodes designed to implement the logic for loops and dynamic switching.
|
||||
* `ImpactCompare`, `ImpactConditionalBranch`, `ImpactConditionalBranchSelMode`, `ImpactInt`, `ImpactValueSender`, `ImpactValueReceiver`, `ImpactImageInfo`, `ImpactMinMax`, `ImpactNeg`, `ImpactConditionalStopIteration`
|
||||
* `ImpactIsNotEmptySEGS` - This node returns `true` only if the input SEGS is not empty.
|
||||
* `Queue Trigger` - When this node is executed, it adds a new queue to assist with repetitive tasks. It will only execute if the signal's status changes.
|
||||
* `Queue Trigger (Countdown)` - Like the Queue Trigger, it adds a queue, but only adds it if it's greater than 1, and decrements the count by one each time it runs.
|
||||
* `Sleep` - Waits for the specified time (in seconds).
|
||||
* `Set Widget Value` - This node sets one of the optional inputs to the specified node's widget. An error may occur if the types do not match.
|
||||
* `Set Mute State` - This node changes the mute state of a specific node.
|
||||
* `Control Bridge` - This node modifies the state of the connected control nodes based on the `mode` and `behavior` . If there are nodes that require a change, the current execution is paused, the mute status is updated, and a new prompt queue is inserted.
|
||||
* When the `mode` is `active`, it makes the connected control nodes active regardless of the behavior.
|
||||
* When the `mode` is `Bypass/Mute`, it changes the state of the connected nodes based on whether the behavior is `Bypass` or `Mute`.
|
||||
* **Limitation**: Due to these characteristics, it does not function correctly when the batch count exceeds 1. Additionally, it does not guarantee proper operation when the seed is randomized or when the state of nodes is altered by actions such as `Queue Trigger`, `Set Widget Value`, `Set Mute`, before the Control Bridge.
|
||||
* When utilizing this node, please structure the workflow in such a way that `Queue Trigger`, `Set Widget Value`, `Set Mute State`, and similar actions are executed at the end of the workflow.
|
||||
* If you want to change the value of the seed at each iteration, please ensure that Set Widget Value is executed at the end of the workflow instead of using randomization.
|
||||
* It is not a problem if the seed changes due to randomization as long as it occurs after the Control Bridge section.
|
||||
* Remote Boolean (on prompt), Remote Int (on prompt) - At the start of the prompt, this node forcibly sets the `widget_value` of `node_id`. It is disregarded if the target widget type is different.
|
||||
* `Remote Boolean (on prompt)`, `Remote Int (on prompt)` - At the start of the prompt, this node forcibly sets the `widget_value` of `node_id`. It is disregarded if the target widget type is different.
|
||||
* You can find the `node_id` by checking through [ComfyUI-Manager](https://github.com/ltdrdata/ComfyUI-Manager) using the format `Badge: #ID Nickname`.
|
||||
* Experimental set of nodes for implementing loop functionality (tutorial to be prepared later / [example workflow](test/loop-test.json)).
|
||||
|
||||
* HuggingFace - These nodes provide functionalities based on HuggingFace repository models.
|
||||
### HuggingFace nodes
|
||||
* These nodes provide functionalities based on HuggingFace repository models.
|
||||
* `HF Transformers Classifier Provider` - This is a node that provides a classifier based on HuggingFace's transformers models.
|
||||
* The 'repo id' parameter should contain HuggingFace's repo id. When `preset_repo_id` is set to `Manual repo id`, use the manually entered repo id in `manual_repo_id`.
|
||||
* e.g. 'rizvandwiki/gender-classification-2' is a repository that provides a model for gender classification.
|
||||
@@ -255,21 +261,27 @@ This takes latent as input and outputs latent as the result.
|
||||
* For supported labels, please refer to the `config.json` of the respective HuggingFace repository.
|
||||
* `#Female` and `#Male` are symbols that group multiple labels such as `Female, women, woman, ...`, for convenience, rather than being single labels.
|
||||
|
||||
* Etc
|
||||
### Etc nodes
|
||||
* `Impact Scheduler Adapter` - With the addition of AYS to the scheduler of the Impact Pack and Inspire Pack, there is an issue of incompatibility when the existing scheduler widget is converted to input. The Impact Scheduler Adapter allows for an indirect connection to be possible.
|
||||
* `StringListToString` - Convert String List to String
|
||||
* `WildcardPromptFromString` - Create labeled wildcard for detailer from string.
|
||||
* This node works well when used with MakeTileSEGS. [[Link](https://github.com/ltdrdata/ComfyUI-Impact-Pack/pull/536#discussion_r1586060779)]
|
||||
|
||||
## MMDet nodes
|
||||
* `String Selector` - It selects and returns a portion of the string. When `multiline` mode is disabled, it simply returns the string of the line pointed to by the selector. When `multiline` mode is enabled, it divides the string based on lines that start with `#` and returns them. If the `select` value is larger than the number of items, it will start counting from the first line again and return accordingly.
|
||||
* `Combine Conditionings` - It takes multiple conditionings as input and combines them into a single conditioning.
|
||||
* `Concat Conditionings` - It takes multiple conditionings as input and concat them into a single conditioning.
|
||||
|
||||
|
||||
## MMDet nodes (DEPRECATED) - Don't use these nodes
|
||||
* MMDetDetectorProvider - Loads the MMDet model to provide BBOX_DETECTOR and SEGM_DETECTOR.
|
||||
* To use the existing MMDetDetectorProvider, you need to enable the MMDet usage configuration.
|
||||
|
||||
|
||||
## Feature
|
||||
* Interactive SAM Detector (Clipspace) - When you right-click on a node that has 'MASK' and 'IMAGE' outputs, a context menu will open. From this menu, you can either open a dialog to create a SAM Mask using 'Open in SAM Detector', or copy the content (likely mask data) using 'Copy (Clipspace)' and generate a mask using 'Impact SAM Detector' from the clipspace menu, and then paste it using 'Paste (Clipspace)'.
|
||||
* `Interactive SAM Detector (Clipspace)` - When you right-click on a node that has 'MASK' and 'IMAGE' outputs, a context menu will open. From this menu, you can either open a dialog to create a SAM Mask using 'Open in SAM Detector', or copy the content (likely mask data) using 'Copy (Clipspace)' and generate a mask using 'Impact SAM Detector' from the clipspace menu, and then paste it using 'Paste (Clipspace)'.
|
||||
* Providing a feature to detect errors that occur when mixing models and clips from checkpoints such as `SDXL Base`, `SDXL Refiner`, `SD1.x`, `SD2.x` during sample execution, and reporting appropriate errors.
|
||||
|
||||
|
||||
## Deprecated
|
||||
* The following nodes have been kept only for compatibility with existing workflows, and are no longer supported. Please replace them with new nodes.
|
||||
* ONNX Detector (SEGS) - BBOX Detector (SEGS)
|
||||
@@ -288,7 +300,7 @@ This takes latent as input and outputs latent as the result.
|
||||
* ultralytics/[assets](https://github.com/ultralytics/assets/releases/) - You can download various types of detection models other than faces or people.
|
||||
* civitai/[adetailer](https://civitai.com/search/models?sortBy=models_v5&query=adetailer) - You can download various types detection models....Many models are associated with NSFW content.
|
||||
|
||||
## How to activate 'MMDet usage'
|
||||
## How to activate 'MMDet usage' (DEPRECATED)
|
||||
* Upon the initial execution, an `impact-pack.ini` file will be generated in the custom_nodes/ComfyUI-Impact-Pack directory.
|
||||
```
|
||||
[default]
|
||||
@@ -332,7 +344,7 @@ mmdet_skip = False
|
||||
* (optional) pycocotools
|
||||
* (optional) onnxruntime
|
||||
|
||||
* mim install (optional)
|
||||
* mim install (deprecated)
|
||||
* mmcv==2.0.0, mmdet==3.0.0, mmengine==0.7.2
|
||||
|
||||
* linux packages (ubuntu)
|
||||
|
||||
Reference in New Issue
Block a user