Custom JPEG / PNG
Read and write images without depending on Sharp, OpenCV, libvips, or native addons. Supports JPEG, progressive JPEG, PNG, and PPM.
Pure Node.js · Zero Native Dependencies · Custom Codecs
A dependency-free computer vision engine for Node.js. Built with TypedArrays, SharedArrayBuffer, custom JPEG/PNG codecs, optimized kernels, morphology, edge detection, resize, annotation, and pipeline execution.
JPEG progressive · 6720×4480 · grayscale → blur(1) → Sobel edges → PNG. Cervid Vision uses custom codecs, optimized TypedArray kernels, grayscale PNG export, and pipeline execution.
Read and write images without depending on Sharp, OpenCV, libvips, or native addons. Supports JPEG, progressive JPEG, PNG, and PPM.
Grayscale, blur, Sobel edges, threshold, invert, brightness, contrast, gamma, normalize, histogram, and custom convolution.
Resize with nearest, bilinear, and area modes. Crop, scale, flip, rotate, and prepare images for computer vision pipelines.
Thresholding, adaptive threshold, erode, dilate, open, close, color masks, connected components, and bounding boxes.
Draw points, lines, rectangles, circles, filled shapes, and detected boxes directly over images and masks.
Use normal chaining for clarity, or
pipeline().run() for optimized execution paths
on known computer vision workloads.
Cervid Vision is not a wrapper around Sharp. It ships its own codecs and processing kernels.
Built for developers who want computer vision workflows directly inside a pure Node.js environment.
Uses flat memory, SharedArrayBuffer, and optimized loops instead of object-heavy pixel processing.