Upload README.md

README.md

@@ -1,3 +1,90 @@
 ---
-license: apache-2.0
+task_categories:
+  - video-classification
+language:
+  - vi
+configs:
+  - config_name: default
+    data_files:
+      - split: train
+        path: "data/shard_*-train.parquet"
+      - split: public_test
+        path: "data/shard_*-public_test.parquet"
+      - split: private_test
+        path: "data/shard_*-private_test.parquet"
 ---
+# ViSignLanguage-MediaPipe
+
+MediaPipe Holistic 3D keypoint dataset extracted from the Vietnamese Sign Language (**ViSignLanguage**) video dataset.
+
+## Dataset Splits & Shard Mapping
+
+Custom split names (`train`, `public_test`, `private_test`) are configured in the YAML header above so `datasets.load_dataset("Haloroute/ViSignLanguage-MediaPipe")` automatically resolves all splits:
+
+| Split | Total Videos | Extracted (Uploaded) | Failed / Empty |
+| :--- | ---: | ---: | ---: |
+| `train` | 3875 | 3875 | 0 |
+| `public_test` | 1630 | 1630 | 0 |
+| `private_test` | 2859 | 2859 | 0 |
+
+## Schema & Columns
+
+Each row corresponds to a single video clip stored in Arrow/Parquet format:
+
+| Column | Type / Shape | Description |
+| :--- | :--- | :--- |
+| `pose_pts` | `float32[T, 33, 3]` | Normalized 3D body pose landmarks (`x, y, z`). |
+| `pose_conf` | `float32[T, 33]` | Per-landmark visibility score from MediaPipe Pose (`[0.0, 1.0]`, `0.0` when missing). |
+| `face_pts` | `float32[T, 478, 3]` | Normalized 3D face mesh landmarks (`x, y, z`, 478 points including iris). |
+| `face_conf` | `float32[T, 478]` | Presence score (`1.0` when face is detected in frame, `0.0` when missing). |
+| `left_hand_pts` | `float32[T, 21, 3]` | Normalized 3D left-hand landmarks (`x, y, z`). |
+| `left_hand_conf` | `float32[T, 21]` | Presence score (`1.0` when left hand is detected in frame, `0.0` when missing). |
+| `right_hand_pts` | `float32[T, 21, 3]` | Normalized 3D right-hand landmarks (`x, y, z`). |
+| `right_hand_conf` | `float32[T, 21]` | Presence score (`1.0` when right hand is detected in frame, `0.0` when missing). |
+| `transcript` | `string` | NFC-normalized Vietnamese sign gloss for `train`; empty string `""` for test splits. |
+| `fps` | `float32` | Video frame rate (probed via OpenCV, fallback to metadata CSV). |
+| `duration` | `int32` | Number of decoded frames `T`. |
+| `key` | `string` | Unique relative identifier: `train/<label>/<filename>` or `<split>/<filename>`. |
+| `metadata` | `string` | JSON-encoded object (`ensure_ascii=False`) with `label`, `label_id`, `split`, `filename`, and CSV metadata (`size_mb`, `fps`, `total_frames`, `width`, `height`, `duration_s` for `train`). |
+
+## Keypoint Layout
+
+- **Pose**: 33 landmarks (`x, y` normalized to `[0, 1]` image coordinates, `z` relative depth at hips origin). Confidence is the landmark `visibility` probability.
+- **Face**: 478 landmarks (`x, y, z` normalized). Confidence is binary (`1.0` if detected, `0.0` if missing).
+- **Hands (Left / Right)**: 21 landmarks each (`x, y, z` normalized). Confidence is binary (`1.0` if detected, `0.0` if missing).
+- Leading person dimension `(1, T, ...)` from `HolisticPose` is squeezed to `(T, ...)`.
+
+## Label Mapping
+
+The complete 100-class mapping (`label -> int id`, NFC-normalized) is stored in [`label_mapping.json`](label_mapping.json).
+
+| ID | Label (NFC Vietnamese) |
+| ---: | :--- |
+| 0 | `An ủi` |
+| 1 | `Áp dụng` |
+| 2 | `Ăn` |
+| 3 | `Ăn mừng` |
+| 4 | `Ban ngày` |
+| 5 | `Ban đêm` |
+| 6 | `Bàn tay` |
+| 7 | `Băn khoăn` |
+| 8 | `Bạn thân` |
+| 9 | `Bế mạc` |
+| 10 | `Bệnh nhân` |
+| 11 | `Bệnh viện` |
+| 12 | `Biết` |
+| 13 | `Biếu tặng` |
+| 14 | `Bộ y tế` |
+| ... | *(100 total classes — see `label_mapping.json`)* |
+
+## Usage
+
+```python
+import json
+from datasets import load_dataset
+
+ds = load_dataset("Haloroute/ViSignLanguage-MediaPipe")
+sample = ds["train"][0]
+print(sample["key"], sample["transcript"], sample["duration"])
+meta = json.loads(sample["metadata"])
+```