add dataset card and split manifests

README.md

@@ -1,35 +1,23 @@
----
-dataset_info:
-  features:
-  - name: id
-    dtype: string
-  - name: image
-    dtype: image
-  - name: label
-    dtype: int32
-  - name: width
-    dtype: int32
-  - name: height
-    dtype: int32
-  splits:
-  - name: train
-    num_bytes: 126730295
-    num_examples: 16334
-  - name: validation
-    num_bytes: 13866323
-    num_examples: 2045
-  - name: test
-    num_bytes: 13817607
-    num_examples: 2045
-  download_size: 150520232
-  dataset_size: 154414225
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
-  - split: validation
-    path: data/validation-*
-  - split: test
-    path: data/test-*
----
+# Dataset Card
+
+## Overview
+This dataset contains labeled image crops for multi-class visual symbol classification.
+
+## Structure
+- `images/`: image files referenced by the manifests
+- `manifest.csv`: full index
+- `train.csv`, `val.csv`, `test.csv`: split manifests
+
+## Schema
+All CSV files use:
+`id,image_path,label,width,height,split`
+
+`image_path` is relative to the dataset root, formatted as `images/<filename>`.
+
+## Usage
+1. Load one of the split CSV files.
+2. Resolve `image_path` from dataset root.
+3. Use `label` as the class target.
+
+## Notes
+This release includes only sanitized metadata and referenced images needed for training/evaluation splits.