Nodes/comfyui_cv/CV Compute Descriptors
ComfyUI Node

CV Compute Descriptors

Describes keypoints that were found by a DESCRIPTOR-FREE detector ('CV Detect Corners', 'CV Detect Blobs', annotated points...) so they can be matched. This is the compute()-only half of the cv2 Feature2D class API, which no raw wrapper exposes: detection and description are separate steps in OpenCV, and splitting them lets you pair any detector with any descriptor (FAST corners + SIFT descriptors, blobs + ORB, ...). Wire the outputs into 'CV Match Features' exactly like 'CV Detect Features'. NOTE the descriptor DROPS keypoints too close to the border, so always use the 'keypoints' output here - not the original list - or the descriptors and keypoints go out of step.

By bmad4ever·Created 3 months ago·Updated 2 days ago· 0
CV Compute Descriptors
  • image
  • keypoints
  • keypoints
  • descriptors
  • count
descriptorORB (binary, fast)
Categoryimage/CV/features

Inputs (3)

NameTypeDefaultDescription
imageNPARRAY,IMAGEThe image the keypoints were detected in (converted to grayscale internally). Accepts a ComfyUI IMAGE/MASK directly (frame 0 of a batch) or an NPARRAY. Arithmetic ops (add, multiply, etc.) process the full IMAGE batch when both inputs have the same batch size.
keypointsCV_KEYPOINTSKeypoints to describe, from any detector node.
descriptorCOMBOORB (binary, fast)ORB/BRISK give binary descriptors (match with Hamming), SIFT gives 128-D float descriptors (match with L2). The matcher node must use the norm that goes with the descriptor.

Outputs (3)

NameTypeDescription
keypointsCV_KEYPOINTSThe keypoints that COULD be described (border keypoints are dropped) - row-aligned with the descriptors.
descriptorsNPARRAYNxD descriptor matrix; uint8 for ORB/BRISK, float32 for SIFT. Empty with the right dtype when nothing survives.
countINTHow many keypoints kept a descriptor.