diff --git a/.gitattributes b/.gitattributes index bed0738c7eeb449bca98b5d2f33c89a1ee56349a..43eb314c263d6fca2e12420da617e393d504095b 100644 --- a/.gitattributes +++ b/.gitattributes @@ -1,60 +1,3 @@ -*.7z filter=lfs diff=lfs merge=lfs -text -*.arrow filter=lfs diff=lfs merge=lfs -text -*.avro filter=lfs diff=lfs merge=lfs -text -*.bin filter=lfs diff=lfs merge=lfs -text -*.bz2 filter=lfs diff=lfs merge=lfs -text -*.ckpt filter=lfs diff=lfs merge=lfs -text -*.ftz filter=lfs diff=lfs merge=lfs -text -*.gz filter=lfs diff=lfs merge=lfs -text -*.h5 filter=lfs diff=lfs merge=lfs -text -*.joblib filter=lfs diff=lfs merge=lfs -text -*.lfs.* filter=lfs diff=lfs merge=lfs -text -*.lz4 filter=lfs diff=lfs merge=lfs -text -*.mds filter=lfs diff=lfs merge=lfs -text -*.mlmodel filter=lfs diff=lfs merge=lfs -text -*.model filter=lfs diff=lfs merge=lfs -text -*.msgpack filter=lfs diff=lfs merge=lfs -text -*.npy filter=lfs diff=lfs merge=lfs -text -*.npz filter=lfs diff=lfs merge=lfs -text -*.onnx filter=lfs diff=lfs merge=lfs -text -*.ot filter=lfs diff=lfs merge=lfs -text -*.parquet filter=lfs diff=lfs merge=lfs -text -*.pb filter=lfs diff=lfs merge=lfs -text -*.pickle filter=lfs diff=lfs merge=lfs -text -*.pkl filter=lfs diff=lfs merge=lfs -text -*.pt filter=lfs diff=lfs merge=lfs -text -*.pth filter=lfs diff=lfs merge=lfs -text -*.rar filter=lfs diff=lfs merge=lfs -text -*.safetensors filter=lfs diff=lfs merge=lfs -text -saved_model/**/* filter=lfs diff=lfs merge=lfs -text -*.tar.* filter=lfs diff=lfs merge=lfs -text -*.tar filter=lfs diff=lfs merge=lfs -text -*.tflite filter=lfs diff=lfs merge=lfs -text -*.tgz filter=lfs diff=lfs merge=lfs -text -*.wasm filter=lfs diff=lfs merge=lfs -text -*.xz filter=lfs diff=lfs merge=lfs -text -*.zip filter=lfs diff=lfs merge=lfs -text -*.zst filter=lfs diff=lfs merge=lfs -text -*tfevents* filter=lfs diff=lfs merge=lfs -text -# Audio files - uncompressed -*.pcm filter=lfs diff=lfs merge=lfs -text -*.sam filter=lfs diff=lfs merge=lfs -text -*.raw filter=lfs diff=lfs merge=lfs -text -# Audio files - compressed -*.aac filter=lfs diff=lfs merge=lfs -text -*.flac filter=lfs diff=lfs merge=lfs -text -*.mp3 filter=lfs diff=lfs merge=lfs -text -*.ogg filter=lfs diff=lfs merge=lfs -text -*.wav filter=lfs diff=lfs merge=lfs -text -# Image files - uncompressed -*.bmp filter=lfs diff=lfs merge=lfs -text -*.gif filter=lfs diff=lfs merge=lfs -text -*.png filter=lfs diff=lfs merge=lfs -text -*.tiff filter=lfs diff=lfs merge=lfs -text -# Image files - compressed -*.jpg filter=lfs diff=lfs merge=lfs -text -*.jpeg filter=lfs diff=lfs merge=lfs -text -*.webp filter=lfs diff=lfs merge=lfs -text -# Video files - compressed -*.mp4 filter=lfs diff=lfs merge=lfs -text -*.webm filter=lfs diff=lfs merge=lfs -text +*.png filter=lfs diff=lfs merge=lfs -text +*.jpg filter=lfs diff=lfs merge=lfs -text +*.jpeg filter=lfs diff=lfs merge=lfs -text diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000000000000000000000000000000000000..6df87e15c1c2e0f3224e56a81f921ef48064d539 --- /dev/null +++ b/.gitignore @@ -0,0 +1,24 @@ +# Scripts (not part of the dataset release) +scripts/ + +# Python artifacts +__pycache__/ +*.py[cod] +*.pyo + +# OS metadata +.DS_Store +Thumbs.db +desktop.ini + +# Editor directories +.vscode/ +.idea/ + +# Python environments +venv/ +.env +env/ + +# Jupyter +.ipynb_checkpoints/ diff --git a/README.md b/README.md new file mode 100644 index 0000000000000000000000000000000000000000..92ff2ce5c13ff522474f88a0d63faf8476d443e1 --- /dev/null +++ b/README.md @@ -0,0 +1,243 @@ +--- +task_categories: + - object-detection +tags: + - microscopy + - biology + - few-shot + - cell-detection + - biomedical + - malaria + - blood-cells + - live-cell-imaging + - fibroblast +size_categories: + - n<1K +--- + +# Micro-OD + +**Micro-OD** is a few-shot microscopy object detection benchmark. It aggregates four publicly available biological imaging datasets across distinct microscopy domains and cell types, and packages them into a standardised format designed for evaluating vision models — in particular, large vision-language models (VLMs) — under few-shot, in-context prompting conditions. + +## Motivation + +Microscopy object detection is a challenging setting for general-purpose vision models: images are domain-specific, class vocabularies are narrow but fine-grained, and labelled data is scarce. Micro-OD is designed to probe how well a model can detect cells and parasites in a new domain when given only a handful of annotated example images at inference time — without any fine-tuning. + +## Dataset Splits + +The dataset contains two splits that together constitute the few-shot evaluation protocol: + +| Split | Role | Images per sub-dataset | Total images | +|---|---|---|---| +| `example` | Few-shot support set | 10 | 40 | +| `test` | Evaluation query set | 53 | 212 | + +**Evaluation protocol:** For each sub-dataset, a model may be provided with up to **10 example images** (from the `example` split) as in-context demonstrations. It is then evaluated on each of the **53 test images** in the `test` split. No fine-tuning on the example images is assumed — they serve solely as few-shot context. + +## Sub-datasets + +Micro-OD draws from four independent biological imaging datasets, each occupying its own sub-directory within each split. + +### BBBC — Malaria Parasite Detection + +- **Domain:** Bright-field blood smear images; malaria parasite detection +- **Source:** [Broad Bioimage Benchmark Collection](https://bbbc.broadinstitute.org/) +- **Original size:** 1,328 images +- **Image format:** PNG +- **Classes (6):** + | Class | Description | + |---|---| + | Red Blood Cells | Uninfected erythrocytes; overwhelmingly dominant class | + | Trophozoite Cells | Early intracellular malaria parasite stage | + | Ring Cells | Ring-form malaria parasite stage | + | Gametocyte Cells | Sexual-stage malaria parasites | + | Schizont Cells | Late-stage malaria parasites (multinucleate) | + | White Blood Cells | Leucocytes; rare in smear images | + +### BCCD — Blood Cell Count Dataset + +- **Domain:** Peripheral blood smear images; complete blood cell counting +- **Source:** [BCCD Dataset](https://github.com/Shenggan/BCCD_Dataset) +- **Original size:** 364 images +- **Image format:** JPG +- **Classes (3):** + | Class | Description | + |---|---| + | Red Blood Cells | Erythrocytes; most abundant class | + | White Blood Cells | Leucocytes; large, clearly visible nuclei | + | Platelets | Thrombocytes; small and sparse | + +### LIVECell — Live Cell Phase-Contrast Imaging (RatC6) + +- **Domain:** Phase-contrast microscopy of RatC6 (rat glioblastoma) cells in culture +- **Images:** [LIVECell Dataset](https://sartorius-research.github.io/LIVECell/) — Edlund et al., 2021 (RatC6 subset) +- **Annotations:** Morphology-based bounding-box labels (Polygonal / Round / Spindle) annotated in-lab +- **Original size:** 420 images (RatC6 subset) +- **Image format:** PNG +- **Classes (3):** + | Class | Description | + |---|---| + | Spindle Cells | Elongated, bipolar morphology; predominant class | + | Polygonal Cells | Flat, multi-angular morphology | + | Round Cells | Spherical or near-spherical morphology | + +### NIH-3T3 — Mouse Fibroblast Cell Line + +- **Domain:** Phase-contrast microscopy of NIH-3T3 mouse fibroblasts +- **Images & Annotations:** In-lab collection and annotation +- **Original size:** 63 images +- **Image format:** PNG +- **Classes (3):** + | Class | Description | + |---|---| + | Polygonal Cells | Flat, multi-angular morphology; dominant class | + | Spindle Cells | Elongated, bipolar fibroblast morphology | + | Round Cells | Spherical or detached cells | + +## Folder Structure + +``` +Micro-OD/ +├── example/ # Few-shot support set +│ ├── BBBC/ +│ │ ├── annotation.jsonl # Bounding-box annotations +│ │ ├── images/ # 10 PNG images +│ │ └── images_overlay/ # 10 images with bounding boxes drawn +│ ├── BCCD/ +│ │ ├── annotation.jsonl +│ │ ├── images/ # 10 JPG images +│ │ └── images_overlay/ +│ ├── LIVECell/ +│ │ ├── annotation.jsonl +│ │ ├── images/ # 10 PNG images +│ │ └── images_overlay/ +│ ├── NIH-3T3/ +│ │ ├── annotation.jsonl +│ │ ├── images/ # 10 PNG images +│ │ └── images_overlay/ +│ └── stat.txt # Split-level statistics +│ +└── test/ # Evaluation query set + ├── BBBC/ + │ ├── annotation.jsonl + │ ├── images/ # 53 PNG images + │ └── images_overlay/ + ├── BCCD/ + │ ├── annotation.jsonl + │ ├── images/ # 53 JPG images + │ └── images_overlay/ + ├── LIVECell/ + │ ├── annotation.jsonl + │ ├── images/ # 53 PNG images + │ └── images_overlay/ + ├── NIH-3T3/ + │ ├── annotation.jsonl + │ ├── images/ # 53 PNG images + │ └── images_overlay/ + └── stat.txt # Split-level statistics +``` + +Each `images_overlay/` folder contains copies of the images with ground-truth bounding boxes rendered on top, useful for visual verification. + +## Annotation Format + +Annotations are stored as [JSON Lines](https://jsonlines.org/) (`.jsonl`) files — one JSON object per line, one line per image. + +```json +{ + "image_path": "images/", + "bbox": { + "": [ + [[x_min, y_min], [x_max, y_max]], + [[x_min, y_min], [x_max, y_max]] + ], + "": [ + [[x_min, y_min], [x_max, y_max]] + ] + } +} +``` + +**Coordinate convention:** +- All coordinates are in **pixel space**. +- Each bounding box is represented as two points: `[x_min, y_min]` (top-left corner) and `[x_max, y_max]` (bottom-right corner). +- A class key is present only if at least one instance of that class appears in the image. + +**Concrete example** (from `example/BCCD/annotation.jsonl`): + +```json +{ + "image_path": "images/BCCD_example_1.jpg", + "bbox": { + "Red Blood Cells": [ + [[201, 223], [314, 322]], + [[1, 252], [89, 357]], + [[203, 336], [292, 441]] + ], + "White Blood Cells": [ + [[211, 4], [338, 132]] + ], + "Platelets": [ + [[330, 442], [373, 480]] + ] + } +} +``` + +## Dataset Statistics + +Detailed per-class statistics are available in `example/stat.txt` and `test/stat.txt`. Summaries are provided below. + +### Test Split — 212 images + +| Sub-dataset | Images | Classes | Total boxes | Boxes/image (mean) | Boxes/image (range) | +|---|---|---|---|---|---| +| BBBC | 53 | 6 | 4,000 | 75.5 | 19–135 | +| BCCD | 53 | 3 | 952 | 18.0 | 9–30 | +| LIVECell | 53 | 3 | 223 | 4.2 | 1–15 | +| NIH-3T3 | 53 | 3 | 376 | 7.1 | 1–14 | +| **Total** | **212** | **10** | **5,551** | — | — | + +### Example Split — 40 images + +The **Support-Spread Score** (SS) is a composite metric reflecting both class coverage (fraction of classes represented in the sample) and class balance (how evenly instances are distributed across represented classes). Higher is better; a score of 1.0 indicates perfect coverage and balance. + +| Sub-dataset | Images | Total boxes | Boxes/image (mean) | Support-Spread Score | +|---|---|---|---|---| +| BBBC | 10 | 734 | 73.4 | 0.136 | +| BCCD | 10 | 78 | 7.8 | 0.680 | +| LIVECell | 10 | 40 | 4.0 | 0.763 | +| NIH-3T3 | 10 | 62 | 6.2 | 0.612 | +| **Total** | **40** | **914** | — | — | + +The low SS for BBBC (0.136) reflects the extreme dominance of Red Blood Cells in the malaria dataset, which makes it difficult to achieve a balanced 10-image sample across all 6 classes. + +### Class Inventory + +| Class | Sub-dataset(s) | Test boxes | +|---|---|---| +| Gametocyte Cells | BBBC | 24 | +| Platelets | BCCD | 159 | +| Polygonal Cells | LIVECell, NIH-3T3 | 417 | +| Red Blood Cells | BBBC, BCCD | 4,427 | +| Ring Cells | BBBC | 34 | +| Round Cells | LIVECell, NIH-3T3 | 24 | +| Schizont Cells | BBBC | 10 | +| Spindle Cells | LIVECell, NIH-3T3 | 158 | +| Trophozoite Cells | BBBC | 193 | +| White Blood Cells | BBBC, BCCD | 105 | + +Note that Polygonal Cells, Round Cells, and Spindle Cells appear in both LIVECell and NIH-3T3 but describe morphologically similar — not biologically identical — phenotypes in different cell lines. + +## Attribution + +Micro-OD combines images and annotations from multiple sources. Please credit the original sources as appropriate: + +- **BBBC (malaria):** Ljosa, V., Sokolnicki, K. L., & Carpenter, A. E. (2012). Annotated high-throughput microscopy image sets for validation. *Nature Methods*, 9(7), 637. [https://bbbc.broadinstitute.org/](https://bbbc.broadinstitute.org/) + +- **BCCD:** Shenggan. *BCCD Dataset*. GitHub. [https://github.com/Shenggan/BCCD_Dataset](https://github.com/Shenggan/BCCD_Dataset) + +- **LIVECell (images):** Edlund, C., et al. (2021). LIVECell — A large-scale dataset for label-free live cell segmentation. *Nature Methods*, 18(9), 1038–1045. [https://doi.org/10.1038/s41592-021-01249-6](https://doi.org/10.1038/s41592-021-01249-6). The morphology-based bounding-box annotations used in Micro-OD were produced in-lab and are not part of the original LIVECell release. + +- **NIH-3T3:** Images and bounding-box annotations are an in-lab collection and are not sourced from a public dataset. + diff --git a/example/BBBC/annotation.jsonl b/example/BBBC/annotation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..9eab2fc749ca7d3176e7f3958b36d2c7ad1896ed --- /dev/null +++ b/example/BBBC/annotation.jsonl @@ -0,0 +1,10 @@ +{"image_path": "images/BBBC_example_1.png", "bbox": {"Red Blood Cells": [[[452, 915], [540, 1014]], [[434, 159], [538, 275]], [[482, 334], [581, 444]], [[418, 414], [519, 528]], [[950, 770], [1054, 877]], [[1452, 156], [1557, 269]], [[1302, 818], [1409, 930]], [[363, 1012], [477, 1122]], [[726, 424], [825, 527]], [[1100, 35], [1211, 152]], [[954, 613], [1069, 730]], [[888, 438], [1009, 558]], [[1267, 1005], [1375, 1111]], [[684, 551], [776, 651]], [[1232, 737], [1329, 853]], [[139, 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sha256:19f29402459f0ca6d9153226177d197913706a3f256235711a354ddf9f07ea5f +size 1771176 diff --git a/example/stat.txt b/example/stat.txt new file mode 100644 index 0000000000000000000000000000000000000000..62ca2be24d2623fc672a36bb2eb71c0a27964ae3 --- /dev/null +++ b/example/stat.txt @@ -0,0 +1,81 @@ +=== BCCD === +Images sampled : 10 of 364 +Classes : Platelets, Red Blood Cells, White Blood Cells +Bounding-boxes (original dataset): + Platelets: 361 (min_nz 1, max_nz 6; min_all 0, max_all 6) + Red Blood Cells: 4155 (min_nz 3, max_nz 27; min_all 0, max_all 27) + White Blood Cells: 372 (min_nz 1, max_nz 2; min_all 0, max_all 2) +Bounding-boxes (sampled subset): + Platelets: 10 (min_nz 1, max_nz 1; min_all 1, max_all 1) + Red Blood Cells: 58 (min_nz 4, max_nz 8; min_all 4, max_all 8) + White Blood Cells: 10 (min_nz 1, max_nz 1; min_all 1, max_all 1) +Boxes per image (orig) : min=1, max=30, mean=13.43, median=14.00 +Boxes per image (sampled): min=6, max=10, mean=7.80, median=8.00 +Support-Spread Score : 0.680 (coverage 1.000, balance 0.680) + +=== BBBC === +Images sampled : 10 of 1328 +Classes : Gametocyte Cells, Red Blood Cells, Ring Cells, Schizont Cells, Trophozoite Cells, White Blood Cells +Bounding-boxes (original dataset): + Gametocyte Cells: 156 (min_nz 1, max_nz 2; min_all 0, max_all 2) + Red Blood Cells: 83034 (min_nz 8, max_nz 219; min_all 8, max_all 219) + Ring Cells: 522 (min_nz 1, max_nz 8; min_all 0, max_all 8) + Schizont Cells: 190 (min_nz 1, max_nz 4; min_all 0, max_all 4) + Trophozoite Cells: 1584 (min_nz 1, max_nz 11; min_all 0, max_all 11) + White Blood Cells: 103 (min_nz 1, max_nz 2; min_all 0, max_all 2) +Bounding-boxes (sampled subset): + Gametocyte Cells: 6 (min_nz 1, max_nz 1; min_all 0, max_all 1) + Red Blood Cells: 684 (min_nz 44, max_nz 115; min_all 44, max_all 115) + Ring Cells: 6 (min_nz 1, max_nz 2; min_all 0, max_all 2) + Schizont Cells: 6 (min_nz 1, max_nz 1; min_all 0, max_all 1) + Trophozoite Cells: 26 (min_nz 1, max_nz 5; min_all 1, max_all 5) + White Blood Cells: 6 (min_nz 1, max_nz 1; min_all 0, max_all 1) +Boxes per image (orig) : min=9, max=223, mean=64.45, median=58.00 +Boxes per image (sampled): min=48, max=118, mean=73.40, median=72.00 +Support-Spread Score : 0.136 (coverage 0.717, balance 0.190) + +=== NIH-3T3 === +Images sampled : 10 of 63 +Classes : Polygonal Cells, Round Cells, Spindle Cells +Bounding-boxes (original dataset): + Polygonal Cells: 346 (min_nz 1, max_nz 13; min_all 0, max_all 13) + Round Cells: 17 (min_nz 1, max_nz 5; min_all 0, max_all 5) + Spindle Cells: 75 (min_nz 1, max_nz 5; min_all 0, max_all 5) +Bounding-boxes (sampled subset): + Polygonal Cells: 43 (min_nz 1, max_nz 9; min_all 1, max_all 9) + Round Cells: 6 (min_nz 1, max_nz 2; min_all 0, max_all 2) + Spindle Cells: 13 (min_nz 1, max_nz 3; min_all 1, max_all 3) +Boxes per image (orig) : min=1, max=14, mean=6.95, median=7.00 +Boxes per image (sampled): min=2, max=12, mean=6.20, median=5.50 +Support-Spread Score : 0.612 (coverage 0.833, balance 0.735) + +=== LIVECell === +Images sampled : 10 of 420 +Classes : Polygonal Cells, Round Cells, Spindle Cells +Bounding-boxes (original dataset): + Polygonal Cells: 178 (min_nz 1, max_nz 8; min_all 0, max_all 8) + Round Cells: 19 (min_nz 1, max_nz 3; min_all 0, max_all 3) + Spindle Cells: 719 (min_nz 1, max_nz 7; min_all 0, max_all 7) +Bounding-boxes (sampled subset): + Polygonal Cells: 15 (min_nz 1, max_nz 3; min_all 0, max_all 3) + Round Cells: 6 (min_nz 1, max_nz 1; min_all 0, max_all 1) + Spindle Cells: 19 (min_nz 1, max_nz 5; min_all 1, max_all 5) +Boxes per image (orig) : min=1, max=15, mean=2.18, median=2.00 +Boxes per image (sampled): min=2, max=8, mean=4.00, median=3.00 +Support-Spread Score : 0.763 (coverage 0.833, balance 0.916) + +=== GLOBAL SUMMARY === +Datasets : 4 +Images : 40 of 2175 +Unique classes : Gametocyte Cells, Platelets, Polygonal Cells, Red Blood Cells, Ring Cells, Round Cells, Schizont Cells, Spindle Cells, Trophozoite Cells, White Blood Cells +Total boxes : + Gametocyte Cells: 6 + Platelets: 10 + Polygonal Cells: 58 + Red Blood Cells: 742 + Ring Cells: 6 + Round Cells: 12 + Schizont Cells: 6 + Spindle Cells: 32 + Trophozoite Cells: 26 + White Blood Cells: 16 diff --git a/test/BBBC/annotation.jsonl b/test/BBBC/annotation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..c070d2a5f42ae9dc334df3fa4d6c1d75d6e42d00 --- /dev/null +++ b/test/BBBC/annotation.jsonl @@ -0,0 +1,53 @@ +{"image_path": "images/BBBC_test_1.png", "bbox": {"Red Blood Cells": [[[410, 822], [525, 935]], [[138, 482], [238, 584]], [[390, 978], [499, 1070]], [[1393, 65], [1496, 165]], [[601, 527], [726, 646]], [[567, 733], [672, 832]], [[1223, 844], [1325, 942]], [[480, 287], [575, 383]], [[495, 555], [589, 655]], [[712, 161], [813, 254]], [[56, 1051], [178, 1167]], [[831, 189], [956, 304]], [[673, 795], [782, 903]], [[347, 634], [481, 753]], [[477, 662], [579, 768]], [[684, 369], [813, 501]], [[73, 892], [176, 998]], [[144, 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White Blood Cells: 56 (min_nz 1, max_nz 2; min_all 0, max_all 2) +Boxes per image (orig) : min=1, max=30, mean=13.43, median=14.00 +Boxes per image (sampled): min=9, max=30, mean=17.96, median=18.00 + +=== BBBC === +Images sampled : 53 of 1328 +Classes : Gametocyte Cells, Red Blood Cells, Ring Cells, Schizont Cells, Trophozoite Cells, White Blood Cells +Bounding-boxes (original dataset): + Gametocyte Cells: 156 (min_nz 1, max_nz 2; min_all 0, max_all 2) + Red Blood Cells: 83034 (min_nz 8, max_nz 219; min_all 8, max_all 219) + Ring Cells: 522 (min_nz 1, max_nz 8; min_all 0, max_all 8) + Schizont Cells: 190 (min_nz 1, max_nz 4; min_all 0, max_all 4) + Trophozoite Cells: 1584 (min_nz 1, max_nz 11; min_all 0, max_all 11) + White Blood Cells: 103 (min_nz 1, max_nz 2; min_all 0, max_all 2) +Bounding-boxes (sampled subset): + Gametocyte Cells: 24 (min_nz 1, max_nz 2; min_all 0, max_all 2) + Red Blood Cells: 3690 (min_nz 17, max_nz 129; min_all 17, max_all 129) + Ring Cells: 34 (min_nz 1, max_nz 8; min_all 0, max_all 8) + Schizont Cells: 10 (min_nz 1, max_nz 4; min_all 0, max_all 4) + Trophozoite Cells: 193 (min_nz 1, max_nz 10; min_all 0, max_all 10) + White Blood Cells: 49 (min_nz 1, max_nz 2; min_all 0, max_all 2) +Boxes per image (orig) : min=9, max=223, mean=64.45, median=58.00 +Boxes per image (sampled): min=19, max=135, mean=75.47, median=74.00 + +=== NIH-3T3 === +Images sampled : 53 of 63 +Classes : Polygonal Cells, Round Cells, Spindle Cells +Bounding-boxes (original dataset): + Polygonal Cells: 346 (min_nz 1, max_nz 13; min_all 0, max_all 13) + Round Cells: 17 (min_nz 1, max_nz 5; min_all 0, max_all 5) + Spindle Cells: 75 (min_nz 1, max_nz 5; min_all 0, max_all 5) +Bounding-boxes (sampled subset): + Polygonal Cells: 303 (min_nz 1, max_nz 13; min_all 0, max_all 13) + Round Cells: 11 (min_nz 1, max_nz 5; min_all 0, max_all 5) + Spindle Cells: 62 (min_nz 1, max_nz 5; min_all 0, max_all 5) +Boxes per image (orig) : min=1, max=14, mean=6.95, median=7.00 +Boxes per image (sampled): min=1, max=14, mean=7.09, median=7.00 + +=== LIVECell === +Images sampled : 53 of 420 +Classes : Polygonal Cells, Round Cells, Spindle Cells +Bounding-boxes (original dataset): + Polygonal Cells: 178 (min_nz 1, max_nz 8; min_all 0, max_all 8) + Round Cells: 19 (min_nz 1, max_nz 3; min_all 0, max_all 3) + Spindle Cells: 719 (min_nz 1, max_nz 7; min_all 0, max_all 7) +Bounding-boxes (sampled subset): + Polygonal Cells: 114 (min_nz 1, max_nz 8; min_all 0, max_all 8) + Round Cells: 13 (min_nz 1, max_nz 3; min_all 0, max_all 3) + Spindle Cells: 96 (min_nz 1, max_nz 7; min_all 0, max_all 7) +Boxes per image (orig) : min=1, max=15, mean=2.18, median=2.00 +Boxes per image (sampled): min=1, max=15, mean=4.21, median=4.00 + +=== GLOBAL SUMMARY === +Datasets : 4 +Images : 212 of 2175 +Unique classes : Gametocyte Cells, Platelets, Polygonal Cells, Red Blood Cells, Ring Cells, Round Cells, Schizont Cells, Spindle Cells, Trophozoite Cells, White Blood Cells +Total boxes : + Gametocyte Cells: 24 + Platelets: 159 + Polygonal Cells: 417 + Red Blood Cells: 4427 + Ring Cells: 34 + Round Cells: 24 + Schizont Cells: 10 + Spindle Cells: 158 + Trophozoite Cells: 193 + White Blood Cells: 105