diff --git a/README.md b/README.md
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+---
+pretty_name: corn1000 — counted cereal kernels on A4
+license: cc-by-nc-4.0
+language:
+- en
+size_categories:
+- n<1K
+tags:
+- agriculture
+- counting
+- object-counting
+- cereal
+- grain
+- thousand-kernel-weight
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train/**
+---
+
+# corn1000 — counted cereal kernels on A4
+
+Photos of cereal kernels spread on a white A4 sheet, each labelled with the **exact number
+of kernels** on the sheet. The dataset is built to train models that count kernels from a
+single phone photo, as the first step of estimating the thousand-kernel weight
+(TKW = mass ÷ count × 1000). A 1 % count error is a 1 % TKW error, so the collection
+protocol is built around label correctness.
+
+> **Status: work in progress.** Collection is ongoing; species, lots and the test split
+> will be added. Built 2026-09-25 from 2 sessions.
+
+## Contents
+
+| | |
+|---|---|
+| Images | 402 |
+| Arrangements (distinct kernel layouts) | 56 |
+| Kernels per image | 225 – 787 |
+| Splits | train: 402 |
+
+| Session | Species | Lot | Light | Chaff | Cameras | Images | Arrangements | Kernels |
+|---|---|---|---|---|---|---|---|---|
+| S01 | rye-w | rye-w-A | desk | light | Galaxy S23, iPhone 8 | 96 | 24 | 274–787 |
+| S03 | barley-w | barley-w-A | desk | light | Galaxy S23, SM-P610, iPhone 8 | 306 | 32 | 225–733 |
+
+## Fields
+
+| Column | Meaning |
+|---|---|
+| `image` | The photo. JPEG; see *Orientation* below. |
+| `count` | Number of kernels on the sheet — the label. |
+| `arrangement_id` | One physical layout of kernels (`<session>-<step>[-<take>]`). Every arrangement is photographed several times, see *Splitting*. |
+| `session`, `step`, `take` | Session ID, card number within the session, and re-shoot number after a REDO. |
+| `species` | `rye-w` winter rye, `durum-w` winter durum wheat, `barley-w` winter barley, `oats-s` spring oats, `wheat-w` winter soft wheat. |
+| `lot` | Seed lot the kernels come from. |
+| `light` | Lighting setup of the session (free text). |
+| `chaff` | `none`, `light` or `heavy`: amount of chaff, awns and broken kernels mixed in. **Never counted.** |
+| `camera` | Camera model from EXIF. |
+| `taken_at` | Capture time from EXIF (camera clock, no time zone). |
+| `weight_g` | Mass of the counted kernels in grams, only where they were weighed; else empty. |
+| `tkw_g` | `weight_g ÷ count × 1000`, where `weight_g` exists. |
+| `raw_file` | Path of the original raw file in this repo (`raw/…`) if the photo was shot as DNG; else empty. |
+
+## How it was collected
+
+Each session covers one species, one seed lot, one lighting setup and one chaff level, and
+follows a pre-generated plan of about 30 steps. Each step is a printed card with a QR code
+that states the new total and what to add or remove (`add 17`, `remove 12`,
+`add 1 cup + 9`; cups hold a verified 50 kernels, each counted twice). For every card:
+
+1. The pile is changed as the card says. Every few cards a **CHECK** card has the whole
+   pile recounted; a mismatch is recorded with an INVALIDATE card and corrected.
+2. The card is photographed, then the kernels are spread by hand into a single layer
+   (touching allowed, no piles) and photographed about twice per phone: roughly top-down,
+   and tilted 20–30° or from another height. Several phones shoot every arrangement.
+3. The pile is gathered again for the next card.
+
+A script decodes the card photos and assigns their total to the photos that follow them.
+It checks that every total follows from the previous one and the card's delta. A group
+whose chain breaks (a skipped or unread card) stays *suspect* until the next CHECK, and
+groups before an INVALIDATE are *invalidated*. **Only groups whose chain validated are in
+this dataset**, after a review of every group by eye. Card photos and scale photos are not
+included.
+
+Counting follows ISO 520:2010: an intact kernel counts, including shrivelled and small
+ones; barley and oats count with their husk; broken kernels, chaff, awns, weed seeds and
+stones never count.
+
+## Splitting
+
+Images are **not independent**: every arrangement appears in 2–25 photos (several phones,
+several angles), and consecutive arrangements of a session share most of their kernels.
+Split by `lot`, or at least by `session`; never by image, and never by `arrangement_id`
+alone.
+
+The intended evaluation holds out winter soft wheat (`wheat-w`) entirely, plus at least one
+lot of every training species. There is no `test` split yet: no held-out lot or species has been collected so far, so everything is in `train`.
+
+## Loading
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("SmartFarmingLab/corn1000")
+```
+
+**Orientation:** most JPEGs are stored sideways with an EXIF orientation tag, exactly as the
+phones wrote them. `datasets`, browsers and `cv2.imread` apply the tag; plain
+`PIL.Image.open` does not — call `PIL.ImageOps.exif_transpose` after it.
+
+**Raw photos:** some phones shot DNG. For those, the image in `data/` was developed with
+LibRaw (rawpy, camera white balance, full resolution, JPEG quality 95). The originals are in
+`raw/`, linked by `raw_file`. Colours of developed DNGs differ from the phones' own JPEG
+processing.
+
+## Known limitations
+
+- Only the species and lots in the table above so far.
+- Some sessions contain chaff and broken kernels (`chaff` ≠ `none`). They are visible in the
+  photos and deliberately not part of the count.
+- The background around the sheet, paper, lighting and phones vary between sessions, but not
+  systematically; some photos show printed square markers or paper clips on the sheet.
+- `weight_g` is only filled in for weighed CHECK groups and is typed in by hand from a photo
+  of the scale display.
+
+## License
+
+[CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/): free to use and adapt for
+non-commercial purposes with attribution. For commercial use, contact the Smart Farming Lab
+(Universität Leipzig).
+
+## Citation
+
+No publication yet. <!-- TODO: add BibTeX once the paper or a DOI exists. -->
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