Leave S01 out, drop the test split and the lot column
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- README.md +18 -28
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README.md
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@@ -15,8 +15,6 @@ tags:
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configs:
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- config_name: default
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data_files:
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- split: test
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path: data/test/**
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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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| Images |
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| Arrangements (distinct kernel layouts) |
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| Kernels per image | 170 – 800 |
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| Images with point annotations |
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| Splits | test: 131, train: 728 |
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| Session | Species |
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|---|---|---|---|---|---|---|
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| S05 | durum-w | durum-w-A | light | Galaxy S23, iPhone 8 | 265 | 31 | 230–782 |
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## Fields
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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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| `pollution` | `none`, `light` or `heavy`: amount of chaff, awns, broken kernels, pebbles, dust or office materials 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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### Procedure
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Each session covers one species
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follows a pre-generated plan of about 30 session cards. Each card carries a QR code and
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states the new total and what to add or remove (`add 17`, `remove 12`, `add 1 cup + 9`).
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### Sessions
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- **
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2026-09-15/16.
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- **S02:** spring oats (`oats-s-A`), not polluted; Galaxy S23 and iPhone 8;
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2026-10-02.
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- **S03:** winter barley (`barley-w
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iPhone 8 and Galaxy Tab S6 Lite; shot over three days, 2026-09-16 to 09-21.
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- **S04:** winter soft wheat (`wheat-w
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S6 Lite; 2026-10-15.
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14 and 15; its photos of those layouts were placed on the card by hand and checked
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against the Pixel photos.
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- **S05:** winter durum wheat (`durum-w
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DNG) and iPhone 8; 2026-10-15.
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### Labelling
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Images are **not independent**: every arrangement appears in 2–22 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 `
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alone.
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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. The `test` split follows that rule.
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-
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## Loading
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```python
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## Known limitations
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- Only the species
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- Some sessions contain pollution (`pollution` ≠ `none`). It is visible in the photos and
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deliberately not part of the count.
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[project repository](https://github.com/SmartFarmingLab/corn1000) (private, access on
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request from the Smart Farming Lab).
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1. **Plan:** `tools/plan_session.py <SESSION> --species … --
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writes `sessions/<SESSION>/plan.json` and the cards to print. Keep `plan.json`: it is
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the reference the labels are checked against.
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2. **Shoot** the session as described under [Procedure](#procedure).
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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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| Images | 751 |
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| Arrangements (distinct kernel layouts) | 123 |
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| Kernels per image | 170 – 800 |
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| Images with point annotations | 158 |
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| Session | Species | Pollution | Cameras | Images | Arrangements | Kernels |
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|---|---|---|---|---|---|---|
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| S02 | oats-s | none | Galaxy S23, iPhone 8 | 124 | 31 | 240–798 |
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+
| S03 | barley-w | light | Galaxy S23, Galaxy Tab S6 Lite, iPhone 8 | 231 | 28 | 225–733 |
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+
| S04 | wheat-w | light | Galaxy Tab S6 Lite, Pixel 9 | 131 | 33 | 170–800 |
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| S05 | durum-w | light | Galaxy S23, iPhone 8 | 265 | 31 | 230–782 |
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## Fields
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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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| `pollution` | `none`, `light` or `heavy`: amount of chaff, awns, broken kernels, pebbles, dust or office materials 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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### Procedure
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Each session covers one species and one pollution level, and
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follows a pre-generated plan of about 30 session cards. Each card carries a QR code and
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states the new total and what to add or remove (`add 17`, `remove 12`, `add 1 cup + 9`).
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### Sessions
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- **S02:** spring oats (`oats-s`), not polluted; Galaxy S23 and iPhone 8;
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2026-10-02.
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- **S03:** winter barley (`barley-w`), lightly polluted; Galaxy S23 (shot as DNG),
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iPhone 8 and Galaxy Tab S6 Lite; shot over three days, 2026-09-16 to 09-21.
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- **S04:** winter soft wheat (`wheat-w`), lightly polluted; Pixel 9 and Galaxy Tab
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S6 Lite; 2026-10-15. The tablet missed or misdated the photos of cards 0, 3, 8,
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14 and 15; its photos of those layouts were placed on the card by hand and checked
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against the Pixel photos.
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- **S05:** winter durum wheat (`durum-w`), lightly polluted; Galaxy S23 (shot as
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DNG) and iPhone 8; 2026-10-15.
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### Labelling
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Images are **not independent**: every arrangement appears in 2–22 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 `session`; never by image, and never by `arrangement_id`
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alone.
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## Loading
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```python
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## Known limitations
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+
- Only the species in the table above so far.
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- Some sessions contain pollution (`pollution` ≠ `none`). It is visible in the photos and
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deliberately not part of the count.
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|
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[project repository](https://github.com/SmartFarmingLab/corn1000) (private, access on
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request from the Smart Farming Lab).
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+
1. **Plan:** `tools/plan_session.py <SESSION> --species … --pollution …`
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writes `sessions/<SESSION>/plan.json` and the cards to print. Keep `plan.json`: it is
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the reference the labels are checked against.
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2. **Shoot** the session as described under [Procedure](#procedure).
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