Add session S04 (wheat-w, test split), replace unlabelled S04 upload

README.md

@@ -15,6 +15,8 @@ tags:
 configs:
 - config_name: default
   data_files:
+  - split: test
+    path: data/test/**
   - split: train
     path: data/train/**
 ---
@@ -27,34 +29,22 @@ 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 2026-10-05 from 3 sessions.
->
-> **Preliminary release, label review pending.** A cross-check against weights and point
-> annotations found count errors in S03 cards 20–23. Cards 21 and 22 are excluded for good;
-> cards 20 and 23 are held back until recounted. Point annotations cover only a few photos
-> so far. Counts may still change.
->
-> **Known open issue:** on S01 cards 19–30, every annotated photo has 5–8 fewer kernel
-> points than `count`, while no missed kernel shows up in them. `count` there may be about
-> 6 too high, which would affect every S01 photo from card 17 on except the recounted CHECK
-> card 24. This is being checked by annotating a CHECK photo.
-
 ## Contents
 
 | | |
 |---|---|
-| Images | 457 |
-| Arrangements (distinct kernel layouts) | 86 |
-| Kernels per image | 225 – 798 |
+| Images | 531 |
+| Arrangements (distinct kernel layouts) | 117 |
+| Kernels per image | 170 – 800 |
 | Images with point annotations | 28 |
-| Splits | train: 457 |
+| Splits | test: 74, train: 457 |
 
 | Session | Species | Lot | Light | Chaff | Cameras | Images | Arrangements | Kernels |
 |---|---|---|---|---|---|---|---|---|
 | S01 | rye-w | rye-w-A | desk | light | Galaxy S23, iPhone 8 | 108 | 27 | 274–787 |
 | S02 | oats-s | oats-s-A | desk | none | Galaxy S23, iPhone 8 | 124 | 31 | 240–798 |
 | S03 | barley-w | barley-w-A | desk | light | Galaxy S23, SM-P610, iPhone 8 | 225 | 28 | 225–733 |
+| S04 | wheat-w | wheat-w-A | desk | light | Pixel 9 | 74 | 31 | 170–800 |
 
 ## Fields
 
@@ -133,22 +123,19 @@ A script decodes the card photos and assigns their total to the photos that foll
 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. One exception: S01 cards 9–11 were
-invalidated by the chain but are included, because their point annotations match `count`
-exactly. In S02 the Galaxy S23 missed the card photos of cards 6 and 22; its photos of
-those two layouts are placed on the card by hand, because they show the same layout as the
-iPhone 8 photos of that card, and the chain validates with them. Card photos and scale
-photos are not included.
+this dataset**, after a review of every group by eye. 
+
+Card photos and scale photos are not included.
 
 ## Splitting
 
-Images are **not independent**: every arrangement appears in 2–22 photos (several phones,
+Images are **not independent**: every arrangement appears in 1–22 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`.
+lot of every training species. The `test` split follows that rule.
 
 ## Loading
 
@@ -180,10 +167,25 @@ a kernel was missed or lies at the edge of the frame. `count` stays the label.
 - 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.
+
+## Contributing
+
+New sessions are welcome. **Do not upload photos to this repository directly.** Every file
+here is generated by the export script from reviewed labels; photos without a
+`metadata.jsonl` row have no count and are useless for training. The tools are in the
+[project repository](https://github.com/SmartFarmingLab/corn1000) (private, access on
+request from the Smart Farming Lab).
+
+1. **Plan:** `tools/plan_session.py <SESSION> --species … --lot … --light … --chaff …`
+   writes `sessions/<SESSION>/plan.json` and the cards to print. Keep `plan.json`: it is
+   the reference the labels are checked against.
+2. **Shoot** the session as described under [Procedure](#procedure).
+3. **Label:** copy the original files (not via a messenger) to `sessions/<SESSION>/` and run
+   `tools/sort_photos.py sessions/<SESSION> --out labels/<SESSION>`.
+4. **Review** every group in `labels/<SESSION>/review.html` and mark the checked rows
+   `review=done` in `labels.csv`.
+5. **Hand in** `plan.json`, `labels/<SESSION>/` and the original photos to the maintainers
+   (the photos are too large for git). They run the export and upload the session here.
 
 ## License