Create README.md

README.md

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+# Multi-Domain Perception Dataset
+
+Unlabeled raw image dataset organized across domain environments, perspectives, and source origins. Designed for downstream annotation (e.g., Label Studio) and computer vision pipelines.
+
+## Repository Structure
+
+Data files are organized cleanly by domain, provenance type, and collection date to prevent naming collisions and facilitate subset loading:
+
+```text
+data/
+├── <domain>/
+│   └── <source_type>/
+│       └── <date_collected>/
+│           └── <raw_data_files>
+└── metadata.jsonl
+```
+
+### Dataset Schema (`metadata.jsonl`)
+
+Each line in `metadata.jsonl` tracks individual file paths alongside collection provenance:
+
+```json
+{
+  "file_name": "data/underwater/real_world/2026-08-19/camera_front/frame_0001.webp",
+  "metadata": {
+    "author": "Collector Name",
+    "domain": "Underwater",
+    "perspective": "Planar",
+    "date_collected": "2026-08-19",
+    "notes": "Field trial under ambient light",
+    "md5": "e99a18c428cb38d5f260853678922e03",
+    "provenance": {
+      "type": "real_world",
+      "platform": "sensor_rig"
+    }
+  }
+}
+```
+
+## Supported Fields
+
+* **Domain:** `Surface`, `Ground`, `Underwater`, `Aerial`, `Other`
+* **Perspective:** `Horizon (Looking to fore/aft/sides)`, `Nadir (Looking down)`, `Zenith (Looking up)`, `Not Applicable`
+* **Source Type:** `real_world`, `synthetic`, `simulated`
+
+## Usage with Hugging Face `datasets`
+
+```python
+from datasets import load_dataset
+
+# Load full dataset with metadata features
+ds = load_dataset("username/repo-name")
+
+# Filter for real-world underwater data
+underwater_real = ds.filter(
+    lambda x: x["metadata"]["domain"] == "Underwater" 
+    and x["metadata"]["provenance"]["type"] == "real_world"
+)
+```