Magellon
plugins available for install. Browse from your CoreService deployment's
plugin manager, or download a
.mpn
archive directly and upload it through the admin UI.
Convolutional auto-encoder-based 2D classification of particle stacks. Reads .mrcs + .star produced by the stack-maker plugin; emits class averages + per-particle assignments + FRC curves.
CTF estimation via CTFFIND4. Consumes micrographs from the bus, shells out to the CTFFIND4 binary inside the container, writes the star file under the data plane.
Computes the magnitude spectrum FFT of an input MRC image and writes the result as a PNG. Pure-Python via numpy; no external binaries required. Pairs with the Magellon CTF and MotionCor plugins as the third "always there" image-processing surface.
Reference fixture for end-to-end install-pipeline testing. Pure Python with zero runtime dependencies — installs in seconds via uv. Not intended for real cryo-EM workloads; use FFT, CTF, MotionCor archives for that.
MotionCor2-based beam-induced motion correction for cryo-EM movies. Pins ~11 GB host RAM; production deployments need at least a g4dn.2xlarge per the operator sizing notes.
Ptolemy ONNX models for low-mag square detection + med-mag hole detection. One plugin process serves both categories via separate consumer registrations; manifest declares the square-detection surface as the public face.
FFT-correlation template-matching particle picker. External broker version of the in-process pp/template_picker; deploy this when picker scaling is needed across multiple workers. Two backends now serve PARTICLE_PICKING — operators pick which one to dispatch to.
Topaz CNN-based particle picking (and the companion micrograph denoiser). Two categories share one plugin process — backend_id reflects the picking surface; the denoise category is served by the same image via a second consumer registration.