docs: expand dataset card from original GDrive readme

README.md

@@ -1,76 +1,165 @@
 ---
-license: cc-by-4.0
+license: cc-by-sa-4.0
 task_categories:
 - image-classification
 tags:
 - magic-the-gathering
 - card-identification
 - temporal-eval
+- edition-identification
+pretty_name: Sol Ring Temporal Eval
+size_categories:
+- n<1K
 ---
 
-# Sol Ring Eval Dataset
+# Sol Ring Dataset
 
-A temporal evaluation benchmark for Magic: The Gathering card identification,
-specifically designed to measure how **multi-frame rolling-buffer** approaches
-compare to single-frame identification.
+(c) 2026, HanClinto Games, LLC
 
-## What's in it
+A collection of 307 reference frames for benchmarking Magic: The Gathering card
+identification — specifically **edition (set) discrimination** under real-world
+camera conditions.
 
-- **308 frames** from 22 distinct Sol Ring printings (editions), drawn from
-  21 short phone-camera videos.
-- Each edition is its own video; frames within a video are temporally ordered
-  by `frame_number` (spaced ~60 source frames ≈ 1–2 seconds apart at 30 fps).
-- `corners.csv` provides per-frame homography-verified card corner coordinates
-  (normalized 0–1), a sharpness proxy (`num_good_matches`), and the ground-truth
-  `card_id` (Scryfall UUID) and `set_code`.
+## Purpose
 
-## File layout
+To provide a meaningful, reproducible metric for measuring and comparing the
+accuracy of card recognition algorithms, with particular focus on
+**set / edition identification** rather than just card-name recognition.
 
-```
-corners.csv          308-row metadata file (see schema below)
-data/frames/*.jpg    source JPEG frames (pre-dewarped, camera perspective intact)
-```
+## Theory
 
-## corners.csv schema
+In Magic: The Gathering, Commander is the most popular way to play the game.
 
-| Column | Type | Description |
-|---|---|---|
-| `img_path` | str | Path relative to repo root (`data/frames/{filename}`) |
-| `card_id` | str | Scryfall UUID — ground-truth card identity |
-| `set_code` | str | Set abbreviation parsed from filename (e.g. `khc`) |
-| `frame_number` | int | Frame index within the source video — establishes temporal order |
-| `corner0_x` … `corner3_y` | float | Homography-detected card corners, normalized 0–1 |
-| `num_good_matches` | int | SIFT inlier count — proxy for detection confidence |
-| `matching_area_pct` | float | Fraction of reference card area matched |
+In Commander, the single most-popular card (ranked #1 on EDHREC) is Sol Ring.
 
-## Intended use
+The Mike Bierik artwork for Sol Ring is the most-reprinted artwork in the
+entire game, appearing across dozens of Commander precon sets with nearly
+identical artwork and card layout.
 
-Simulate a live-camera feed per edition:
+This makes Sol Ring uniquely valuable as a benchmark: it is simultaneously
+the most-played card in the most-played format, *and* the card whose printings
+are most easily confused with one another. A system that can reliably
+distinguish a C17 Sol Ring from a C18 Sol Ring from a CMR Sol Ring — all
+sharing the same artwork — has demonstrated meaningful edition discrimination,
+not just card-name lookup.
 
-```python
-from collections import deque
-from datasets import load_dataset
+This dataset therefore represents a practical, high-stakes standard for edition
+identification accuracy across a wide swath of modern sets.
+
+## Dataset construction
+
+21 distinct printings of Sol Ring were acquired through TCGPlayer — each from
+a different edition, each bearing the iconic Mike Bierik artwork.
+
+Short videos were recorded of each card using a mobile phone against a plain
+white background, capturing dozens of frames per card across varied lightings,
+angles, and minor motion blur.
+
+Each video filename is labeled with the Scryfall UUID of the correct card.
+
+Keyframes were extracted with FFmpeg, and blur detection was used to filter out
+unwanted frames. The remaining sharp ("good") frames are what appear in this
+dataset under `data/frames/`.
+
+Corner coordinates for each frame were then detected via a SIFT homography
+pipeline matching against the known Scryfall reference image for that card.
+These are stored in `corners.csv` and can be used to dewarp each frame to a
+clean, perspective-corrected card crop before running an identification model.
 
-ds = load_dataset("HanClinto/solring-eval", split="train")
+## Temporal structure
 
-# Group by card_id, sort by frame_number to get temporal sequence
-for card_id, frames in group_by_card(ds):
+Frames within each edition are **temporally ordered** by `frame_number`
+(the source video frame index, spaced roughly every 60 source frames
+≈ 1–2 seconds at 30 fps). This ordering is critical for simulating a
+live-camera rolling-buffer evaluation:
+
+```python
+from collections import deque, defaultdict
+import csv, cv2
+from pathlib import Path
+
+rows = list(csv.DictReader(open("corners.csv")))
+by_card = defaultdict(list)
+for r in rows:
+    by_card[r["card_id"]].append(r)
+for frames in by_card.values():
+    frames.sort(key=lambda r: int(r["frame_number"]))
+
+# Simulate a rolling buffer of up to 5 embeddings
+for card_id, frames in by_card.items():
     buffer = deque(maxlen=5)
-    for frame in sorted(frames, key=lambda r: r["frame_number"]):
-        emb = embed(dewarp(frame))
-        kept = [e for e in buffer if cosine_sim(emb, e) >= 0.7]
+    for row in frames:
+        img  = cv2.imread(row["img_path"])
+        emb  = embed(dewarp(img, row))          # your model here
+        kept = [e for e in buffer
+                if cosine_sim(emb, e) >= 0.7]  # filter bad grabs
         search_emb = normalize(mean([emb] + kept)) if kept else emb
         top1 = gallery_search(search_emb)
         buffer.append(emb)
         record(top1 == card_id)
 ```
 
-## Edition list (22 printings)
+## File layout
 
-All 22 are distinct Scryfall card IDs for Sol Ring across different sets.
-See `corners.csv` `card_id` + `set_code` columns for the full list.
+```
+corners.csv          307-row metadata file (schema below)
+data/frames/*.jpg    source JPEG frames (original camera perspective, not cropped)
+```
+
+## corners.csv schema
+
+| Column | Type | Description |
+|---|---|---|
+| `img_path` | str | Path relative to repo root: `data/frames/{filename}` |
+| `card_id` | str | Scryfall UUID — ground-truth card identity |
+| `set_code` | str | Set abbreviation parsed from filename (e.g. `khc`) |
+| `frame_number` | int | Source video frame index — establishes temporal order within an edition |
+| `corner0_x` … `corner3_y` | float | Homography-detected card corners, normalized 0–1 |
+| `num_good_matches` | int | SIFT inlier count — proxy for detection confidence |
+| `matching_area_pct` | float | Fraction of the Scryfall reference card area matched |
+
+## Edition list
+
+All 21 printings share the Mike Bierik Sol Ring artwork.
+
+| card_id | set | frames | frame range |
+|---|---|---|---|
+| `2c52c96d-e20f-4025-b759-674b36cf0db3` | AFC | 14 | 0–784 |
+| `1b59533a-3e38-495d-873e-2f89fbd08494` | C13 | 14 | 0–780 |
+| `b79cb394-eb91-4b3b-91d4-c6a0f723feb1` | C14 | 15 | 0–840 |
+| `3459b229-7c46-4f70-87d4-bb31c2c17dd9` | C15 | 13 | 0–720 |
+| `0f003fde-be17-4159-a361-711ed0bee911` | C16 |  9 | 182–662 |
+| `c6399a22-cebf-4c1d-a23e-4c68f784ac1b` | C17 | 16 | 1–900 |
+| `83a0f2eb-2f6d-4aaa-b7a9-ea06d5de7eca` | C18 | 18 | 0–1020 |
+| `e672d408-997c-4a19-810a-3da8411eecf2` | C19 | 15 | 0–842 |
+| `286bea73-8ad8-4423-8a7c-8497420fdb54` | C20 | 11 | 0–663 |
+| `4cbc6901-6a4a-4d0a-83ea-7eefa3b35021` | C21 | 21 | 0–1200 |
+| `199cde21-5bc3-49cd-acd4-bae3af6e5881` | CLB | 17 | 0–964 |
+| `f9a32f17-49c4-4654-a087-1ba474f37377` | CM2 | 15 | 1–904 |
+| `f48f7190-9ee3-477f-8b25-91e8c2916624` | CMA | 14 | 0–782 |
+| `71357a3d-9a9f-4ec6-8e01-1966b220206c` | CMD | 13 | 0–722 |
+| `58b26011-e103-45c4-a253-900f4e6b2eeb` | CMR | 11 | 0–720 |
+| `beebe533-29b9-4041-ab66-0a8233c50d56` | DMC | 17 | 0–1085 |
+| `0afa0e33-4804-4b00-b625-c2d6b61090fc` | KHC | 13 | 0–787 |
+| `1b3a4537-1d51-47ac-a12e-6b8d68f530e6` | MB1 | 13 | 0–780 |
+| `3917f744-b876-47ae-94ad-f72b215ff1e7` | NEC | 14 | 0–786 |
+| `38d347b7-dc17-417a-ab07-29fe99b9a101` | PHED | 19 | 0–1143 |
+| `8a5edac3-855a-4820-b913-44de5b29b7d0` | ZNC | 15 | 0–840 |
 
 ## License
 
-Images are derivative of Wizards of the Coast card artwork; usage is for
-non-commercial research only. Metadata (corners.csv) is CC BY 4.0.
+This dataset is released under the
+[Creative Commons Attribution-ShareAlike 4.0 International License (CC BY-SA 4.0)](https://creativecommons.org/licenses/by-sa/4.0/).
+
+You are free to share and adapt this material for any purpose, including
+commercially, as long as you provide appropriate credit and distribute any
+derivative datasets under the same license. You are **explicitly free to use
+this dataset for commercial purposes** under those terms.
+
+The goal is a universal, openly-accessible standard for measuring card
+identification accuracy — usable for comparing closed-source and open-source
+solutions alike. If the above terms don't work for your situation, reach out
+and we can discuss alternative licensing.
+
+Contributions are welcome. Additions or corrections to the dataset are
+appreciated but not required.