document FoTA mixed-gel finding (some captures use markered right finger)

README.md

@@ -88,29 +88,43 @@ Public GelSight Mini data is scattered. Authors release each dataset with its ow
 
 |       Subset      | Source dataset                          | Frames    | Gel        | Has labels                              |
 |-------------------|------------------------------------------|----------:|------------|------------------------------------------|
-| `fota_labeled`    | FoTA — *panda_warped* still captures    | **29,494**| markerless | end-effector x,y,z + quaternion          |
-| `fota_unlabeled`  | FoTA — same captures, video frames      | **516,523**| markerless | object name only                        |
+| `fota_labeled`    | FoTA — *panda_warped* still captures    | **29,494** (66% markerless, 34% markered) | mixed¹ | end-effector x,y,z + quaternion |
+| `fota_unlabeled`  | FoTA — same captures, video frames      | **516,523** (mixed¹)| mixed¹ | object name only            |
 | `threedcal`       | py3DCal sphere indentation grid          | **36,270**| markerless | probe x, y, penetration depth (mm)       |
 | `feats`           | FEATS indentation with force grids       | **22,013**| **markered** (two gel variants — see below) | indenter shape/size + contact forces |
-| **Total markerless** | (FoTA + 3DCal)                        | **582,287** |          |                                          |
-| **Total markered**   | (FEATS)                              | **22,013**  |          |                                          |
+
+¹ FoTA used **different gels on the two gripper fingers** for many of its captures. Approximately 36 of 124 captures use a markered gel on the right finger and a markerless gel on the left; the remaining 88 captures use markerless gels on both. The per-row `markered` column was set by averaging ~50 frames per capture and counting visible dark dots in the mean image (threshold ≥10 dots). Use it to filter:
+
+```python
+ds = load_dataset("yxma/gelsight-mini-pretrain", "fota_labeled", split="train")
+markerless = ds.filter(lambda r: not r["markered"])
+markered   = ds.filter(lambda r: r["markered"])
+```
 
 ## Sample images
 
-### `fota_labeled`  ·  29,494 frames  ·  markerless  ·  +6DoF pose
-One labeled still captured at every recorded end-effector pose along a Franka Panda trajectory pressing one of 13 household objects into the gel. The arc-shaped imprints are tactile signatures of objects (here, plier handles, clamps, knives, etc.).
+### `fota_labeled`  ·  29,494 frames  ·  mixed gel  ·  +6DoF pose
+One labeled still captured at every recorded end-effector pose along a Franka Panda trajectory pressing one of 13 household objects into the gel. The arc-shaped imprints are tactile signatures of objects (here, plier handles, clamps, knives, etc.). FoTA used **both markered and markerless gels** — use the `markered` column to filter.
+
+Random sample (mixed):
+
+![fota_labeled mixed](assets/samples_100_fota_labeled.png)
+
+Per gel variant:
 
-![fota_labeled](assets/samples_fota_labeled.png)
+| markerless (66% of the data) | markered (34% of the data) |
+|:---:|:---:|
+| ![fota markerless](assets/samples_100_fota_labeled_markerless.png) | ![fota markered](assets/samples_100_fota_labeled_markered.png) |
 
 ### `threedcal`  ·  36,270 frames  ·  markerless  ·  +xyz pose
 A motorised sphere indenter is pressed into the gel at **1,209 different (x, y) positions** at a fixed 3 mm depth. The bright spot moves as the probe walks across the sensor surface — useful for learning a calibrated position→appearance mapping.
 
-![threedcal](assets/samples_threedcal.png)
+![threedcal](assets/samples_100_threedcal.png)
 
 ### `feats`  ·  22,013 frames  ·  **markered**  ·  +force
 Six indenter shapes (sphere, cuboid, cylinder, pyramid, cross, plus one "unknown" set of held-out probes), each pressed into a markered (dotted) GelSight Mini gel. Provides f_x, f_y, f_z forces and a 32×24 depth grid per image. Forces span from ~0 N (light touch) to **−73 N** (heavy normal compression).
 
-![feats](assets/samples_feats.png)
+![feats](assets/samples_100_feats.png)
 
 > **⚠️ FEATS has two physical gel variants.** A new column `gel_variant` distinguishes them:
 > - `"black_dot"` (21,618 frames) — the standard dotted Mini gel used for `train`, `val`, `test`, `test_unknown_indenters`, `test_diff_sensor_old_gel`.