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Add sessions S01 and S03

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README.md ADDED
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+ ---
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+ pretty_name: corn1000 — counted cereal kernels on A4
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+ license: cc-by-nc-4.0
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+ language:
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+ - en
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+ size_categories:
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+ - n<1K
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+ tags:
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+ - agriculture
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+ - counting
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+ - object-counting
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+ - cereal
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+ - grain
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+ - thousand-kernel-weight
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+ configs:
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+ - config_name: default
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+ data_files:
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+ - split: train
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+ path: data/train/**
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+ ---
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+
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+ # corn1000 — counted cereal kernels on A4
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+
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+ Photos of cereal kernels spread on a white A4 sheet, each labelled with the **exact number
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+ of kernels** on the sheet. The dataset is built to train models that count kernels from a
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+ single phone photo, as the first step of estimating the thousand-kernel weight
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+ (TKW = mass ÷ count × 1000). A 1 % count error is a 1 % TKW error, so the collection
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+ protocol is built around label correctness.
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+
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+ > **Status: work in progress.** Collection is ongoing; species, lots and the test split
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+ > will be added. Built 2026-09-25 from 2 sessions.
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+
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+ ## Contents
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+
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+ | | |
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+ |---|---|
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+ | Images | 402 |
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+ | Arrangements (distinct kernel layouts) | 56 |
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+ | Kernels per image | 225 – 787 |
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+ | Splits | train: 402 |
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+
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+ | Session | Species | Lot | Light | Chaff | Cameras | Images | Arrangements | Kernels |
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+ |---|---|---|---|---|---|---|---|---|
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+ | S01 | rye-w | rye-w-A | desk | light | Galaxy S23, iPhone 8 | 96 | 24 | 274–787 |
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+ | S03 | barley-w | barley-w-A | desk | light | Galaxy S23, SM-P610, iPhone 8 | 306 | 32 | 225–733 |
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+
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+ ## Fields
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+
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+ | Column | Meaning |
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+ |---|---|
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+ | `image` | The photo. JPEG; see *Orientation* below. |
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+ | `count` | Number of kernels on the sheet — the label. |
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+ | `arrangement_id` | One physical layout of kernels (`<session>-<step>[-<take>]`). Every arrangement is photographed several times, see *Splitting*. |
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+ | `session`, `step`, `take` | Session ID, card number within the session, and re-shoot number after a REDO. |
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+ | `species` | `rye-w` winter rye, `durum-w` winter durum wheat, `barley-w` winter barley, `oats-s` spring oats, `wheat-w` winter soft wheat. |
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+ | `lot` | Seed lot the kernels come from. |
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+ | `light` | Lighting setup of the session (free text). |
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+ | `chaff` | `none`, `light` or `heavy`: amount of chaff, awns and broken kernels mixed in. **Never counted.** |
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+ | `camera` | Camera model from EXIF. |
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+ | `taken_at` | Capture time from EXIF (camera clock, no time zone). |
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+ | `weight_g` | Mass of the counted kernels in grams, only where they were weighed; else empty. |
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+ | `tkw_g` | `weight_g ÷ count × 1000`, where `weight_g` exists. |
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+ | `raw_file` | Path of the original raw file in this repo (`raw/…`) if the photo was shot as DNG; else empty. |
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+
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+ ## How it was collected
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+
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+ Each session covers one species, one seed lot, one lighting setup and one chaff level, and
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+ follows a pre-generated plan of about 30 steps. Each step is a printed card with a QR code
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+ that states the new total and what to add or remove (`add 17`, `remove 12`,
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+ `add 1 cup + 9`; cups hold a verified 50 kernels, each counted twice). For every card:
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+
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+ 1. The pile is changed as the card says. Every few cards a **CHECK** card has the whole
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+ pile recounted; a mismatch is recorded with an INVALIDATE card and corrected.
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+ 2. The card is photographed, then the kernels are spread by hand into a single layer
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+ (touching allowed, no piles) and photographed about twice per phone: roughly top-down,
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+ and tilted 20–30° or from another height. Several phones shoot every arrangement.
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+ 3. The pile is gathered again for the next card.
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+
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+ A script decodes the card photos and assigns their total to the photos that follow them.
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+ It checks that every total follows from the previous one and the card's delta. A group
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+ whose chain breaks (a skipped or unread card) stays *suspect* until the next CHECK, and
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+ groups before an INVALIDATE are *invalidated*. **Only groups whose chain validated are in
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+ this dataset**, after a review of every group by eye. Card photos and scale photos are not
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+ included.
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+
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+ Counting follows ISO 520:2010: an intact kernel counts, including shrivelled and small
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+ ones; barley and oats count with their husk; broken kernels, chaff, awns, weed seeds and
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+ stones never count.
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+
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+ ## Splitting
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+
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+ Images are **not independent**: every arrangement appears in 2–25 photos (several phones,
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+ several angles), and consecutive arrangements of a session share most of their kernels.
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+ Split by `lot`, or at least by `session`; never by image, and never by `arrangement_id`
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+ alone.
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+
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+ The intended evaluation holds out winter soft wheat (`wheat-w`) entirely, plus at least one
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+ 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`.
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+
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+ ## Loading
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+
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+ ```python
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+ from datasets import load_dataset
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+
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+ ds = load_dataset("SmartFarmingLab/corn1000")
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+ ```
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+
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+ **Orientation:** most JPEGs are stored sideways with an EXIF orientation tag, exactly as the
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+ phones wrote them. `datasets`, browsers and `cv2.imread` apply the tag; plain
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+ `PIL.Image.open` does not — call `PIL.ImageOps.exif_transpose` after it.
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+
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+ **Raw photos:** some phones shot DNG. For those, the image in `data/` was developed with
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+ LibRaw (rawpy, camera white balance, full resolution, JPEG quality 95). The originals are in
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+ `raw/`, linked by `raw_file`. Colours of developed DNGs differ from the phones' own JPEG
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+ processing.
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+
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+ ## Known limitations
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+
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+ - Only the species and lots in the table above so far.
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+ - Some sessions contain chaff and broken kernels (`chaff` ≠ `none`). They are visible in the
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+ photos and deliberately not part of the count.
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+ - The background around the sheet, paper, lighting and phones vary between sessions, but not
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+ systematically; some photos show printed square markers or paper clips on the sheet.
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+ - `weight_g` is only filled in for weighed CHECK groups and is typed in by hand from a photo
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+ of the scale display.
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+
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+ ## License
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+
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+ [CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/): free to use and adapt for
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+ non-commercial purposes with attribution. For commercial use, contact the Smart Farming Lab
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+ (Universität Leipzig).
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+
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+ ## Citation
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+
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+ No publication yet. <!-- TODO: add BibTeX once the paper or a DOI exists. -->
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  • Pointer size: 132 Bytes
  • Size of remote file: 3.88 MB
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Git LFS Details

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  • Pointer size: 132 Bytes
  • Size of remote file: 2.18 MB
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Git LFS Details

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  • Pointer size: 132 Bytes
  • Size of remote file: 2.4 MB
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Git LFS Details

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  • Pointer size: 132 Bytes
  • Size of remote file: 3.84 MB
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Git LFS Details

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  • Pointer size: 132 Bytes
  • Size of remote file: 4.27 MB
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Git LFS Details

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  • Pointer size: 132 Bytes
  • Size of remote file: 2.23 MB
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Git LFS Details

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  • Pointer size: 132 Bytes
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Git LFS Details

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  • Pointer size: 132 Bytes
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Git LFS Details

  • SHA256: 0a0fb7a9deaeb2d3f1d5b2f8027e26f6fc698caa1b73c7f7be7e21044ecc3abf
  • Pointer size: 132 Bytes
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Git LFS Details

  • SHA256: e299ae2adba2ad2ae2bdeb29cbb40309ef2d26ca5701428e369bc3c67ba725aa
  • Pointer size: 132 Bytes
  • Size of remote file: 2.1 MB
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Git LFS Details

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  • Pointer size: 132 Bytes
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Git LFS Details

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  • Pointer size: 132 Bytes
  • Size of remote file: 3.76 MB