| --- |
| license: mit |
| task_categories: |
| - image-classification |
| tags: |
| - spacr |
| - microscopy |
| - annotation |
| - toxoplasma |
| pretty_name: spaCR Annotate and Classify example data |
| --- |
| |
| # spaCR — Annotate and Classify example data |
|
|
| Example input for the **Annotate** and **Classify** modules of |
| [spaCR](https://github.com/EinarOlafsson/spacr). It is the output of a Measure |
| run, so both modules can be exercised without segmenting or measuring anything |
| first. |
|
|
| ## What is here |
|
|
| | Path | What it is | |
| |---|---| |
| | `data/` | 2,341 single-cell PNG crops, foldered by phenotype | |
| | `measurements.db` | The measurements, plus `png_list` and the annotation tables | |
| | `measurements/active_learning/` | The model card from the first annotation round | |
| | `settings/annotate_settings.csv` | Settings for the Annotate module | |
| | `settings/classify_settings.csv` | Settings for the Classify module | |
|
|
| ## Labels: infected or not, by rule |
|
|
| `png_list.infected` holds a label for **every one of the 2,341 crops**, derived |
| from the measurements rather than by hand: |
|
|
| | Value | Meaning | The gesture that would produce it | |
| |---|---|---| |
| | `1` | no parasite in this cell | left click | |
| | `2` | at least one parasite | right click | |
|
|
| 1,173 infected against 1,168 uninfected — 50.1%, which is about as balanced as |
| a binary training set gets without being resampled. |
|
|
| **How it was derived.** The `pathogen` table names the parent cell of every |
| detected parasite, so a cell is infected exactly when at least one pathogen row |
| points at it. That is a rule anyone can re-run and check, which a hand pass over |
| a subset is not. |
|
|
| **Independently cross-checked.** All 1,173 also have |
| `cell_pathogen_overlap_fraction > 0` — a column Measure computes by a different |
| route entirely. The two agree on every cell. |
|
|
| `annotate` is deliberately empty, so the module opens on a clean column and the |
| rule-based labels stay as a reference rather than as something to overwrite. |
|
|
| ## Paths are RELATIVE, deliberately |
|
|
| Every path in `measurements.db` and in both settings files is relative to the |
| dataset root: |
|
|
| ``` |
| data/single_nucleus/uninfected/plate1_E01/cell_png/plate1_E01_19_1_12.png |
| ``` |
|
|
| A measurements database normally stores absolute paths, which name the machine |
| that made it and resolve nowhere else. spaCR's downloader rewrites these to |
| absolute on arrival, so the database works wherever it is unpacked. If you |
| unpack it by hand, do the same, or point spaCR at the folder and let it. |
|
|
| `<dataset>` in the settings files is a placeholder for the unpack location and |
| is substituted the same way. |
|
|
| ## Plate layout |
|
|
| Four wells (E01, E02, L01, L02) from the plate published as |
| [`einarolafsson/spacr-example-measure`](https://huggingface.co/datasets/einarolafsson/spacr-example-measure), |
| which holds the merged arrays these crops were cut from. |
|
|
| ## How spaCR downloads it |
|
|
| Everything here is also published as a single uncompressed **`spacr-example-annotate.tar`**, and |
| that is what spaCR fetches: one request instead of 2,365, a progress figure |
| that means something, and a download that stops when you press Cancel. It is |
| unpacked with tar's `data` filter, which refuses any member that would write |
| outside the destination folder. |
|
|
| The individual files are kept beside it so the set can be browsed and previewed |
| on this page. They are the same bytes; either is fine to use. |
|
|
| ## Provenance |
|
|
| Produced by spaCR's Mask module and then its Measure module, from spaCR's own |
| example images, with `cpsam` for cells and nuclei and a Toxoplasma-specific |
| CPSAM checkpoint for pathogens. One field of fifty-two (`plate1_E02_20_1`) |
| failed to measure — a nucleus label spanning two cells — so the crops come from |
| 51 fields. Absolute paths have been rewritten to relative throughout. |
|
|
