OpenCV phaseCorrelate_0

phaseCorrelate_0 answers one specific, very useful question: how far has this image shifted relative to that one? It's a port of cv2.phaseCorrelate, which measures global translational motion between two images down to sub-pixel accuracy. No models, no training, no API - just two arrays and a Fourier transform.

This node comes from opencv-comfyui, the pack that auto-generated ~635 nodes from OpenCV's Python type stubs. The author (Gerold Meisinger, who launched it on r/comfyui in April 2025) frames the whole pack honestly: these are thin wrappers for "small and quick transformations", not full-blown OpenCV apps, and the README warns you to "expect dragons". phaseCorrelate_0 is one of the more genuinely useful dragons, though.

How it works

Phase correlation is a frequency-domain trick. The node runs a discrete Fourier transform on both images, computes the cross-power spectrum, and the inverse transform of that spectrum produces a sharp peak whose location tells you the sub-pixel shift (dx, dy) between the two inputs. The float output is the response - the height of that peak, in [0, 1]. Higher response means a confident match; a low response means the two images don't line up well (or don't share much content).

What's it for? The classic jobs: aligning a denoised or upscaled frame back onto the original so you can compare them pixel-for-pixel, measuring camera shake between consecutive video frames, or registering two shots of the same scene before blending. If your workflow has a "did this pass actually preserve the framing?" moment, this is the cheap way to check it.

The inputs and outputs

• src1, src2 - the two NPARRAY images to compare. Both must be single-channel and floating point (CV_32FC1). That means grayscale, and likely a cvtColor node (code 6 for BGR2GRAY) in front of this.
• window - optional NPARRAY, a Hann/tapering window you can build to suppress edge effects. In OpenCV's API the window overload is separate; here it's just optional. Most beginners should leave it unconnected and accept a little edge ringing.
• Outputs are literal (STRING) and float. Here's the gotcha: the (dx, dy) shift is a Point2f, and since the pack can't express composite types as a proper socket, it comes out as a string - you read the shift in the node, you don't wire it into anything numeric. The float response is the usable signal.

Install and the usual pack gotchas

Install once per pack: ComfyUI Manager → search "opencv-comfyui", or

cd ComfyUI/custom_nodes
git clone https://github.com/geroldmeisinger/opencv-comfyui

restart ComfyUI, and make sure OpenCV is present (pip install opencv-contrib-python). You work in NPARRAY space: Image2Nparray in, Nparrays2Image out, batch size 1 only - use ImageFromBatch (length 1) if you get the batch error.

Two traps bite people here. First, feeding uint8 RGB images straight in - phaseCorrelate wants float, single-channel, so convert first or you'll hit an assertion error. Second, expecting to use the shift value downstream. The string output means this node is really an observation tool: it tells you the shift and the confidence, and you act on that information manually or through a branching node, rather than feeding the numbers straight into a warp.

It's niche, but it's the kind of niche that saves you an hour of squinting at misaligned comparisons.