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eval3d

nextpyp/prismpyp

`prismpyp eval3d`¶

Purpose¶

Generate metadata for visualizing the embeddings interactively in 3D.

This command can:

Run 3D embedding evaluation on real-space or Fourier-space inputs
Optionally resume from precomputed embeddings
Save a .parquet file and thumbnail image `.zip file for visualizing embedding points using Phoenix

Usage¶

usage: prismpyp eval3d [-h] [--output-path DIR] [--metadata-path METADATA_PATH] [--embedding-path [EMBEDDING_PATH]] [-a ARCH] [-j N] [--epochs N]
                       [--start-epoch N] [-b N] [--lr LR] [--momentum M] [--wd W] [-p N] [--resume PATH] [--feature-extractor-weights PATH]
                       [--world-size WORLD_SIZE] [--rank RANK] [--dist-url DIST_URL] [--dist-backend DIST_BACKEND] [--seed SEED] [--gpu GPU]
                       [--multiprocessing-distributed] [--dim DIM] [--pred-dim PRED_DIM] [--fix-pred-lr] [--use-fft] [--downsample DOWNSAMPLE]
                       [--pixel-size PIXEL_SIZE] [--size SIZE] [--evaluate] [--n-clusters N_CLUSTERS] [--num-neighbors NUM_NEIGHBORS]
                       [--min-dist-umap MIN_DIST_UMAP] [--n-components N_COMPONENTS] [--nextpyp-preproc NEXTPYP_PREPROC] [--zip-images]

Named Arguments¶

Commonly Changed¶

Argument	Description	Default
`--output-path DIR`	Path to output directory	—
`--metadata-path METADATA_PATH`	Path to metadata file	—
`--embedding-path EMBEDDING_PATH`	Optional path to precomputed embeddings	—
`--feature-extractor-weights PATH`	Path to pre-trained feature extractor weights	`none`
`--dim DIM`	Feature dimension	`512`
`--pred-dim PRED_DIM`	Hidden dimension of the predictor	`256`
`--fix-pred-lr`	Fix learning rate for the predictor	—
`--use-fft`	Use FFT of the image as input	`False`
`--evaluate`	Evaluate model on validation set	`True`
`--n-clusters N_CLUSTERS`	Number of clusters for KMeans	—
`--num-neighbors NUM_NEIGHBORS`	Number of neighbors for UMAP	—
`--min-dist-umap MIN_DIST_UMAP`	Minimum distance for UMAP	`0`
`--n-components N_COMPONENTS`	Number of UMAP components	—
`--zip-images`	Save zipped image thumbnails	—

Available Architectures:
resnet18, resnet34, resnet50