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README.md

@@ -1,31 +1,86 @@
 ---
-dataset_info:
-  features:
-  - name: image
-    dtype: image
-  - name: class_label
-    dtype: string
-  - name: class_idx
-    dtype: int64
-  - name: host
-    dtype: string
-  - name: disease
-    dtype: string
-  - name: is_healthy
-    dtype: bool
-  - name: split
-    dtype: string
-  - name: filename
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 64771805.0
-    num_examples: 164
-  download_size: 64498683
-  dataset_size: 64771805.0
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
+license: cc-by-4.0
+task_categories:
+  - image-classification
+language:
+  - en
+tags:
+  - plant-disease
+  - test-fixture
+  - debug-grade
+size_categories:
+  - n<1K
+pretty_name: PlantDoc (tiny)
 ---
+
+# PlantDoc — tiny variant
+
+> **Warning: this is a debug-grade subset, not a faithful subsample for analysis.** Use it for test suites, smoke tests, and notebook iteration. For substantive work, use [`geraldmc/plantdoc-full`](https://huggingface.co/datasets/geraldmc/plantdoc-full).
+
+A 164-image stratified subsample of [`geraldmc/plantdoc-full`](https://huggingface.co/datasets/geraldmc/plantdoc-full), built to support fast iteration. Loading is roughly a 50 MB download instead of ~950 MB, and a pass over the dataset takes seconds rather than minutes.
+
+## Quick start
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("geraldmc/plantdoc-tiny", revision="v0.1.0", split="train")
+print(len(ds))    # 164
+```
+
+Inside the iResearch Institute 2026 Virtual Lab:
+
+```python
+import irilab2026 as iri
+
+metadata_df, hf_dataset = iri.load_plantdoc(variant="tiny")
+```
+
+## What's in this dataset
+
+- **164 images** stratified across 28 classes, 83 train + 81 test
+- **Schema identical to `plantdoc-full`** — same 8 columns (image + 7 metadata), same values for any image that appears in both
+- **Subsample rule:** `min(3, available)` per class per split, with a fixed seed
+
+For every non-orphan class, this means 3 train + 3 test = 6 images. The orphan class (`Tomato two spotted spider mites leaf`) appears with its 2 train images and 0 test images, exactly as in the full variant.
+
+## Schema, normalization, caveats
+
+See the **[full variant's dataset card](https://huggingface.co/datasets/geraldmc/plantdoc-full)** for:
+
+- Column descriptions and types
+- Normalization rules for `host` and `disease`
+- The orphan-class caveat
+- Filename quirks
+- Citation and license details
+
+The schema is identical between the two variants; duplicating it here invites drift.
+
+## Subsample parameters
+
+- **Per-class budget:** `min(3, available)` per (class, split)
+- **Seed:** `42` (passed as `random_state` to pandas `.sample()`)
+- **Source:** `geraldmc/plantdoc-full` at revision `v0.1.0`
+
+The subsample is fully deterministic given these three parameters. Re-running the build script with the same source and seed produces byte-identical metadata. Image bytes also match exactly because the same upstream files are referenced.
+
+## What this dataset is NOT for
+
+- **Training a classifier.** 3 training images per class is far too few to learn anything; this isn't a "small training set" — it's a fixture for code paths.
+- **Measuring per-class accuracy.** Per-class test set sizes here are 1–3 images; any "accuracy" you compute is dominated by sampling noise.
+- **Comparing model architectures.** Any signal would be noise at this scale.
+- **Reporting results in a paper.** Whatever you find on the tiny variant is not a finding about PlantDoc — it's a finding about 164 images that happen to live under this repo ID.
+
+## What this dataset IS for
+
+- **Test suite use.** Fast assertion that loader code, Dataset wrappers, and training pipelines run end-to-end without surprise.
+- **Notebook iteration.** Debugging a preprocessing pipeline or augmentation strategy without paying for the full dataset's load time.
+- **CI runs.** Tests that exercise loader behavior can use this variant on every push without burning minutes on downloads.
+
+## License
+
+CC BY 4.0, matching the full variant and the upstream dataset.
+
+## Citation
+
+Cite the upstream dataset (Singh et al. 2020) and reference this tiny variant as `geraldmc/plantdoc-tiny @ v0.1.0`. Full BibTeX in the full variant's dataset card.