Model zoo¶

spaCR ships a catalogue of trained models and fetches them on demand. Name a key in a settings file — pathogen_model: toxoplasma_pv_v1 — and the model is downloaded and checksum-verified the first time it is needed, or open Model Zoo from the Make Masks masthead to browse and install them.

Every published entry carries a SHA-256. An entry without one is refused rather than installed, because a truncated or substituted checkpoint cannot be told from the real one.

For temporal model training, see Timeflows training data and supervision for annotation assignment, crop supervision and checkpoint provenance. Changes to those training rules do not replace an existing downloaded checkpoint.

Model	Training data	Hold-out performance
`toxoplasma_pv_v1` (Cellpose-SAM (cpsam_v2))	anti-Toxoplasma-biotin and DsRed PV lumen; 229 images from 2 datasets, 104 round-1 and 125 newly curated	F1 0.864 against 0.713 for stock cpsam on 11 held-out in-house wells, at IoU 0.5; literature hold-out pending
`toxoplasma_plaque_v1` (Cellpose-SAM (cpsam))	crystal violet plaque wells; 184 wells from 3 datasets, 95 in-house and 89 literature	F1 0.856 in-domain; 0.806 on literature (3-fold cross-validated, SD 0.020)
`toxoplasma_plaque_v2` (Cellpose-SAM (cpsam_v2))	488 curated fields across four domains – 298 wells cropped from published figures, 96 phone-camera wells, 67 PFA and 27 methanol-fixed whole-well microscope scans; 27,582 plaques	not scored against stock; on 81 held-out fields it ties round 3 on literature (0.819 vs 0.820) and beats it by 0.166 on phone-camera wells (0.415 vs 0.249)
`toxoplasma_well_detector_v1` (YOLO11n)	whole-plate and multi-well crystal violet images; 562 images from 1 dataset, 190 of them with no well in them	mAP50 0.993 on its own held-out split; on the test set shared with v2 it scores mAP50 0.8838, against v2’s 0.9457
`toxoplasma_well_detector_v2` (YOLO26n (ultralytics 8.4.155))	plate images and literature figures; 1,070 train / 254 val / 129 test, split by PMC article so no paper is in two sets; training data at einarolafsson/toxoplasma-plaque-well-detector-dataset	mAP50 0.9457 and mAP50-95 0.8341 against v1’s (yolo_welldetect_v3.pt) 0.8838 and 0.7630 on the SAME test set; stock YOLO has no plaque-well class, so v1 is the baseline
`toxoplasma_from_cellmask_v1` (Cellpose-SAM (cpsam_v2))	Toxoplasma PV masks predicted from the HOST CELL MASK channel alone; 2567 training and 463 held-out fields, split by well, hosts HFF/HeLa/THP1	F1 0.606 against 0.021 for stock cpsam_v2 on 463 well-grouped held-out fields, at IoU 0.5
`toxoplasma_pv_v2` (Cellpose-SAM (cpsam_v2))	anti-Toxoplasma-biotin and DsRed PV lumen; 556 curated images accumulated over five rounds	F1 0.817 +/- 0.036 by 5-fold cross-validation over 619 pairs; ~0.86 against 0.713 for stock on the 11 in-house held-out wells
`toxoplasma_pv_v3` (Cellpose-SAM (cpsam_v2))	the 556 curated PV fields of round 5, split 437 train / 108 validation / 11 test; training data at einarolafsson/toxoplasma-pv-segmentation-dataset	F1 0.860 against stock cpsam_v2’s 0.765 on the 11 anchor wells at IoU 0.5; AJI 0.803 against 0.505
`live_cell_v1` (Cellpose-SAM (cpsam_v2))	11,007 transmitted-light fields from 14 public datasets, split by acquisition 6,778 train / 2,030 validation / 2,199 test; training data at einarolafsson/live-cell-segmentation-dataset	on the datasets stock cpsam_v2 never trained on, F1 0.960 against 0.885 at IoU 0.5; over all 2,199 test fields, 0.694 against 0.738, because stock trained on LIVECell and YeaZ and wins on LIVECell
`nuclei_from_cellmask_v1` (Cellpose-SAM (cpsam_v2))	nuclei predicted from the HOST CELL MASK channel alone; 453 well-grouped held-out fields, hosts HFF/HeLa/THP1	F1 0.888 against 0.201 for stock cpsam_v2 on 453 well-grouped held-out fields, at IoU 0.5
`cell_from_hoechst_v1` (Cellpose-SAM (cpsam_v2))	the HOST CELL outline predicted from the Hoechst (nuclear) channel alone; 2,578 training fields and 451 held-out test fields, split by well so no well is on both sides	F1 0.870 against stock cpsam_v2’s 0.301 on 451 held-out fields at IoU 0.5 – a delta of 0.569
`toxoplasma_from_hoechst_v1` (Cellpose-SAM (cpsam_v2))	Toxoplasma PV masks predicted from the HOECHST channel alone; 2567 training and 463 held-out fields, split by well, hosts HFF/HeLa/THP1	F1 0.569 against 0.002 for stock cpsam_v2 on 463 well-grouped held-out fields, at IoU 0.5

Models are hosted on their author’s own Hugging Face account, so contributing one does not mean handing write access to anyone else’s. spacr.model_zoo’s publish_model performs the upload and prints the catalogue row to add.

Per-model detail¶

Toxoplasma PV v1¶

Architecture. Cellpose-SAM (cpsam_v2)

Trained on. Toxoplasma tachyzoite parasitophorous vacuoles stained with goat anti-Toxoplasma-biotin, and tachyzoites expressing DsRed in the PV lumen. Round 2: 229 training images (round 1’s 104 plus 125 newly curated RH and ME49 fields), 100 epochs, base cpsam_v2

Measured. F1 0.864 against 0.713 for stock cpsam on 11 held-out in-house wells, at IoU 0.5; literature hold-out pending

F1 0.864 at IoU 0.5 against 0.713 for stock cpsam on the 11 wells round 1 also held out (round 1 scored 0.867); AJI 0.809 against 0.426
accuracy falls sharply above IoU 0.8 – suited to counting and area rather than precise morphometry
the held-out literature scorecard is pending a stock-seeded re-curation; on the current literature set, whose truth leans toward this model’s lineage, it ties stock Cellpose-SAM on detection (F1 0.403 against 0.400)

Published as einarolafsson/toxoplasma-pv-segmentation-cpsam, as cpsam_v2_toxo_r2.

SHA-256 182d8cf6b32c7b9ef2917c85870d188486e5e119f05e9c5c1f07652f6859f2d0.

Toxoplasma Plaque v1¶

Architecture. Cellpose-SAM (cpsam)

Trained on. Toxoplasma gondii plaque assays; round 3, evaluated in-domain (NAS) and against a literature generalisation set

Measured. F1 0.856 in-domain; 0.806 on literature (3-fold cross-validated, SD 0.020)

F1 0.856 in-domain and 0.806 on the literature set (3-fold cross-validated, SD 0.020), against 0.718 for round 1
round 3 trades precision (0.939 down to 0.858) for recall (0.631 up to 0.811) on the literature set, which is the right direction for a counting assay
PREFER THIS ONE FOR MICROSCOPE-ONLY WORK. On the round-5 test split it scores 0.836 on PFA-fixed wells against round 5’s 0.808, at precision 0.93 against 0.81. For mixed sources, or any phone-camera image, use toxoplasma_plaque_v2, which round 3 cannot handle at all (0.249 there)

Published as einarolafsson/toxoplasma-plaque-segmentation-cpsam, as cpsam_plaque_r3.

SHA-256 eeecd2d6cd5cbb4dddee71564d5f460d26bb07ac125e0b494b7502fea4292d5d.

Toxoplasma Plaque v2 (round 5)¶

Architecture. Cellpose-SAM (cpsam_v2)

Trained on. Toxoplasma plaque assays stained with crystal violet, from three microscopes and from published figures. Round 5: 332 training fields grouped by figure and by plate so none straddles the split, 100 epochs, base cpsam_v2, empty wells kept as negatives

Measured. not scored against stock; on 81 held-out fields it ties round 3 on literature (0.819 vs 0.820) and beats it by 0.166 on phone-camera wells (0.415 vs 0.249)

COMPLEMENTS toxoplasma_plaque_v1 rather than replacing it: prefer v1 (round 3) for microscope-only work, where it scores 0.836 against this model’s 0.808 on PFA-fixed wells and is far more precise; prefer this one for mixed or unknown sources
the only plaque model trained on phone-camera wells – F1 0.415 against round 3’s 0.249, though recall there is 0.296, so it still misses most plaques on phone images and is not yet a counting tool
it did NOT clear the promotion bar of 0.02 literature F1 fixed before the run (it came in at -0.001), so round 3 remains production
balanced precision/recall (0.81/0.83) where round 3 is lopsided (0.93/0.73): round 3’s low recall systematically UNDERCOUNTS, which matters more than F1 for a counting assay
hallucinates 2 objects across 6 blank-lawn wells where round 3 hallucinates 19
first plaque model on cpsam_v2; rounds 1-4 used cpsam v1, so base and data changed together and the gap to round 3 is not attributable to the extra curation alone
training data: https://huggingface.co/datasets/einarolafsson/toxoplasma-plaque-dataset

Published as einarolafsson/toxoplasma-plaque-segmentation-cpsam-r5, as cpsam_plaque_r5.

SHA-256 0927023a745ac6a19bae0ec72c89b7b864a4ff8d047a41f3f1e9767e1a4d0600.

Toxoplasma Plaque Well Detector v1¶

Architecture. YOLO11n

Trained on. whole-plate and multi-well Toxoplasma plaque-assay images; yolo11n base, 150 epochs, batch 16, imgsz 640

Measured. mAP50 0.993 on its own held-out split; on the test set shared with v2 it scores mAP50 0.8838, against v2’s 0.9457

the 0.993 is measured on v3’s OWN split, which is easier than the set v2 is measured on; on that shared set this model scores mAP50 0.8838 against v2’s 0.9457, so v2 is the better detector
kept because the published plaque corpus was measured with these weights, so results in the paper trace back to this row
locates WELLS, not plaques; it is the front half of a two-stage pipeline with toxoplasma_plaque_v1, and the well it finds also gives the diameter that makes areas comparable across microscopes

Published as einarolafsson/toxoplasma-plaque-well-detector-yolo11, as yolo_welldetect_v3.pt.

SHA-256 b826058754fb5d4df36c3a7283aac049015cbb044b5ef096c55d19f37172a50c.

Toxoplasma Plaque Well Detector v2¶

Architecture. YOLO26n (ultralytics 8.4.155)

Trained on. whole-plate and multi-well Toxoplasma plaque-assay images plus 939 newly reviewed PMC figures, accepted boxes and confirmed negatives alike; yolo26n base, best validation mAP50-95 at epoch 28

Measured. mAP50 0.9457 and mAP50-95 0.8341 against v1’s (yolo_welldetect_v3.pt) 0.8838 and 0.7630 on the SAME test set; stock YOLO has no plaque-well class, so v1 is the baseline

on the shared test set it beats v1 (the v3 weights) on every measure, and cuts false boxes on no-well figures from 152 to 49
84 of the 129 test images contain no well at all, which is what the false-box count is measured on
locates WELLS, not plaques; the front half of a two-stage pipeline with the plaque segmentation model
the repository publishes this weight as weights/best.pt; spaCR saves it under the name above so two detectors cannot both land as best.pt

Published as einarolafsson/toxoplasma-plaque-well-detector-yolo26, as yolo_welldetect_v4.pt.

SHA-256 f2a1e1110f09b2a1d5ef5545adaba7c57f1158669d0bfc50d8fabe9f86da30c7.

Toxoplasma from Cell Mask (cross-channel)¶

Architecture. Cellpose-SAM (cpsam_v2)

Trained on. cross-channel: given the host cell image, predicts where the Toxoplasma parasitophorous vacuoles are, with no parasite stain. 100 epochs, base cpsam_v2, AdamW lr 1e-5, targets are PV-regenerated masks

Measured. F1 0.606 against 0.021 for stock cpsam_v2 on 463 well-grouped held-out fields, at IoU 0.5

F1 0.606, AJI 0.494, Dice 0.610 at IoU 0.5 against stock cpsam_v2’s 0.021/0.008/0.020 – stock cannot do this task at all
per host: HeLa 0.711, HFF 0.557, THP1 0.465; THP1 is the weak case
the held-out split selects the checkpoint, so it is validation data rather than an independent test set
accuracy falls above IoU 0.8 – suited to counting, occupancy and area rather than precise morphometry

Published as einarolafsson/toxoplasma-from-cellmask-cpsam, as toxoplasma_from_cellmask_pv.

SHA-256 481dfccc1a68cc594aafcb71088efc25b5f5c6a6240e52902c0089759b3149ab.

Toxoplasma PV v2 (round 5)¶

Architecture. Cellpose-SAM (cpsam_v2)

Trained on. Toxoplasma tachyzoite parasitophorous vacuoles stained with goat anti-Toxoplasma-biotin, and tachyzoites expressing DsRed in the PV lumen (RH and ME49). Round 5: 556 images, 100 epochs, base cpsam_v2

Measured. F1 0.817 +/- 0.036 by 5-fold cross-validation over 619 pairs; ~0.86 against 0.713 for stock on the 11 in-house held-out wells

supersedes toxoplasma_pv_v1 (round 2, 229 images): more than twice the training data and cross-validated rather than single-split
5-fold CV over 619 pairs: F1 0.817 (SD 0.036), AJI 0.714, Dice 0.802
per-dataset variance is real – F1 ranges ~0.74 to ~0.93 by screen
accuracy falls above IoU 0.8 – suited to counting and area rather than precise morphometry

Published as einarolafsson/toxoplasma-pv-segmentation-cpsam-r5, as cpsam_v2_toxo_r5.

SHA-256 17c689e3b117745561e20a885c2a2a998ed360fa97cac8c0446316ae5905c10f.

Toxoplasma PV v3 (round 6)¶

Architecture. Cellpose-SAM (cpsam_v2)

Measured. F1 0.860 against stock cpsam_v2’s 0.765 on the 11 anchor wells at IoU 0.5; AJI 0.803 against 0.505

NEWEST IS NOT BEST HERE: round 6 does not beat round 2 on the anchor wells – 0.8602 against 0.8648 – and the PV project still promotes round 5
it is the first PV round whose checkpoint was chosen on a held-out validation set (108 fields) instead of on the test wells
5-fold cross-validation, grouped by source: F1 0.8168 +/- 0.028, AJI 0.7516, Dice 0.8424
the 11 anchor wells have been held out since round 1, so they are the only fields no PV round has ever trained on

Published as einarolafsson/toxoplasma-pv-segmentation-cpsam-r6, as cpsam_v2_toxo_r6.

SHA-256 146ef269979b1d1ab45c11039b0ab164f68001adaa8f73f1f8f18be6fcfd060e.

Live cell v1 (phase, brightfield, DIC)¶

Architecture. Cellpose-SAM (cpsam_v2)

Trained on. unstained cells in phase contrast, brightfield and DIC: LIVECell, DeepSea, YeaZ, yeast microstructures, five Cell Tracking Challenge sets, BBBC009, BBBC030, QPI and Revvity. Base cpsam_v2, cellpose 4.2.1.1, lr 1e-5, batch 4; stopped at epoch 37 of 100

Measured. on the datasets stock cpsam_v2 never trained on, F1 0.960 against 0.885 at IoU 0.5; over all 2,199 test fields, 0.694 against 0.738, because stock trained on LIVECell and YeaZ and wins on LIVECell

TWO STOCK COMPARISONS, NOT ONE: stock cpsam_v2 trained on LIVECell and YeaZ, so its score there is partly memorisation. On the datasets it never saw (DeepSea, the CTC sets, BBBC009, BBBC030, QPI, Revvity, yeast microstructures) this model scores F1 0.960 against 0.885
it does NOT replace stock on LIVECell-style Incucyte phase: 0.671 against 0.724 there, and it missed its own pre-registered promotion bar
by modality at IoU 0.5: brightfield 0.964 (stock 0.912), DIC +0.026 over stock, phase 0.689 (stock 0.735)
F1 0.865 on a train sample, 0.696 on validation and 0.694 on test; no per-epoch loss was recorded

Published as einarolafsson/live-cell-segmentation-cpsam, as live_cell_v1.

SHA-256 7ade69377093fe81830ddc7c52ba8618bef1fefe7d1243c01b9c1beed7fcb090.

Cross-channel nuclei-from-cellmask¶

Architecture. Cellpose-SAM (cpsam_v2)

Trained on. cross-channel: given the cell image, predicts where the nuclei are, with no nuclear stain – which frees the DAPI/Hoechst channel for another marker. 100 epochs, base cpsam_v2

Measured. F1 0.888 against 0.201 for stock cpsam_v2 on 453 well-grouped held-out fields, at IoU 0.5

F1 0.888, AJI 0.792, Dice 0.877 at IoU 0.5 against stock cpsam_v2’s 0.201/0.286/0.449
per host: HFF 0.932, HeLa 0.860, THP1 0.861
the held-out split selects the checkpoint, so it is validation data rather than an independent test set
predicts nuclei from cell morphology – expect degraded accuracy on unusual or highly confluent morphologies

Published as einarolafsson/cross-channel-nuclei-from-cellmask-cpsam, as nuclei_from_cellmask_best.

SHA-256 2675553a46e97a7bc4bd2bfe3e954954194fe71ca4e94261e752a02bf0b6eb47.

Cross-channel cell-from-hoechst¶

Architecture. Cellpose-SAM (cpsam_v2)

Trained on. Hoechst-stained nuclei paired with curated host-cell masks; fine-tuned from stock cpsam_v2, 100 epochs, best epoch 70

Measured. F1 0.870 against stock cpsam_v2’s 0.301 on 451 held-out fields at IoU 0.5 – a delta of 0.569

the counterpart of nuclei_from_cellmask_v1: that one predicts nuclei from the cell mask, this one predicts the cell from the nucleus
precision 0.944 against recall 0.806 – it misses cells rather than inventing them, which is the safer direction for counting
quote the DELTA over stock (0.569), not the ratio: stock’s mAP of 0.0575 is a near-zero denominator that makes any ratio look huge

Published as einarolafsson/cross-channel-cell-from-hoechst-cpsam, as cell_from_hoechst_best.

SHA-256 d1992433b4f2f291f73738830bb953198165fdc10719e54dae9b8c2bd430e0eb.

Toxoplasma from Hoechst (cross-channel)¶

Architecture. Cellpose-SAM (cpsam_v2)

Trained on. cross-channel: given the Hoechst/nuclear image, predicts where the Toxoplasma parasitophorous vacuoles are, with no parasite stain. 100 epochs, base cpsam_v2, AdamW lr 1e-05, targets are PV-regenerated masks

Measured. F1 0.569 against 0.002 for stock cpsam_v2 on 463 well-grouped held-out fields, at IoU 0.5

F1 0.569, AJI 0.421, Dice 0.546 at IoU 0.5 against stock cpsam_v2’s 0.002/0.006/0.016
the Hoechst route is harder than the cell-mask route – compare toxoplasma_from_cellmask_v1
the held-out split selects the checkpoint, so it is validation data rather than an independent test set
accuracy falls above IoU 0.8 – suited to counting, occupancy and area rather than precise morphometry

Published as einarolafsson/toxoplasma-from-hoechst-cpsam, as toxoplasma_from_hoechst_pv.

SHA-256 8dc05ebced3550d1a418c13d24d319e0482c742988df29a525520026cb2f0d96.