| --- |
| 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/** |
| - split: test |
| path: data/test/** |
| --- |
| |
| # 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. |
|
|
| ## Contents |
|
|
| | | | |
| |---|---| |
| | Images | 836 | |
| | Arrangements (distinct kernel layouts) | 128 | |
| | Kernels per image | 170 – 1000 | |
| | Images with point annotations | 158 | |
|
|
| | Session | Species | Pollution | Cameras | Images | Arrangements | Kernels | |
| |---|---|---|---|---|---|---| |
| | S02 | oats-s | none | Galaxy S23, iPhone 8 | 124 | 31 | 240–798 | |
| | S03 | barley-w | light | Galaxy S23, Galaxy Tab S6 Lite, iPhone 8 | 231 | 28 | 225–733 | |
| | S04 | wheat-w | light | Galaxy Tab S6 Lite, Pixel 9 | 131 | 33 | 170–800 | |
| | S05 | durum-w | light | Galaxy S23, iPhone 8 | 265 | 31 | 230–782 | |
| | count_1000 | barley-w, durum-w, rye-w, wheat-w, oats-s | light, none | Galaxy S23, iPhone 8 | 85 | 5 | 1000–1000 | |
| |
| ## 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. | |
| | `pollution` | `none`, `light` or `heavy`: amount of chaff, awns, broken kernels, pebbles, dust or office materials mixed in. **Never counted.** | |
| | `camera` | Camera model from EXIF. | |
| | `taken_at` | Capture time from EXIF (camera clock, no time zone). | |
| | `raw_file` | Path of the original raw file in this repo (`raw/…`) if the photo was shot as DNG; else empty. | |
| | `kernel_points` | `[x, y]` of every counted kernel, see *Point annotations*; null if the photo is not annotated. | |
| | `broken_points` | `[x, y]` of broken kernels (not counted); null if not annotated. | |
| | `invalid_points` | `[x, y]` of other objects marked as not countable; null if not annotated. | |
|
|
| ## How it was collected |
|
|
| ### Counting rules |
|
|
| Based on ISO 520:2010. |
|
|
| **Counts as a kernel:** an intact kernel, including shrivelled and small ones. Barley and |
| oats count with their husk. Twins count as two kernels. |
|
|
| **Never counts:** broken kernels; chaff, straw and awns; foreign seeds, dust and stones. |
| Borderline cases were sorted out rather than judged, to keep the count exact. |
|
|
| **Pollution in the data:** chaff, awns, broken kernels, pebbles, dust or office materials will |
| occur in the use case, so some sessions deliberately contain them as noise (`pollution` = |
| `light` or `heavy`). They are never part of `count`. |
|
|
| ### Materials |
|
|
| - White A4 sheet on a dark or high-contrast background |
| - Cups for the kernels, each holding a verified 50 kernels |
| - Printed session cards and special cards (REDO, INVALIDATE) from the planning script |
|
|
| ### Sessions |
|
|
| - **S02:** spring oats (`oats-s`), not polluted; Galaxy S23 and iPhone 8; |
| 2026-10-02. |
| - **S03:** winter barley (`barley-w`), lightly polluted; Galaxy S23 (shot as DNG), |
| iPhone 8 and Galaxy Tab S6 Lite; shot over three days, 2026-09-16 to 09-21. |
| - **S04:** winter soft wheat (`wheat-w`), lightly polluted; Pixel 9 and Galaxy Tab |
| S6 Lite; 2026-10-15. The tablet missed or misdated the photos of cards 0, 3, 8, |
| 14 and 15; its photos of those layouts were placed on the card by hand and checked |
| against the Pixel photos. |
| - **S05:** winter durum wheat (`durum-w`), lightly polluted; Galaxy S23 (shot as |
| DNG) and iPhone 8; 2026-10-15. |
| - **count_1000:** the `test` split. All five species with exactly 1000 kernels in every |
| photo, 13–21 photos per species; barley lightly polluted, the others not polluted; |
| Galaxy S23 (shot as DNG) and iPhone 8; 2026-10-26. No session cards were photographed: |
| the species were assigned by capture time and checked by eye, and each species is one |
| `arrangement_id`. |
| |
| ## Splitting |
| |
| Images are **not independent**: every arrangement appears in 2–22 photos (several phones, |
| several angles), and consecutive arrangements of a session share most of their kernels. |
| Split by `session`; never by image, and never by `arrangement_id` |
| alone. |
| |
| The `test` split is session `count_1000` (see *Sessions*); `train` holds all other sessions. |
| |
| ## 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. |
|
|
| ## Point annotations |
|
|
| A subset of photos carries one point per object, placed by hand in CVAT. Coordinates are |
| pixels of the **upright** image, i.e. after the EXIF orientation is applied (what `datasets` |
| returns), with the origin at the top left. The points are a second, independent annotation: |
| `len(kernel_points)` can differ from `count` by a few kernels, mostly on dense sheets where |
| a kernel was missed or lies at the edge of the frame. `count` stays the label. |
|
|
| ## Known limitations |
|
|
| - Only the species in the table above so far. |
| - Some sessions contain pollution (`pollution` ≠ `none`). It is visible in the photos and |
| deliberately not part of the count. |
|
|
| ## 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. --> |
|
|
