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README.md

@@ -1,23 +1,89 @@
 ---
-dataset_info:
-  features:
-  - name: question_id
-    dtype: string
-  - name: jpg
-    dtype: image
-  - name: question
-    dtype: string
-  - name: groundtruth
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 1865606658
-    num_examples: 1840
-  download_size: 1864989941
-  dataset_size: 1865606658
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
+task_categories:
+- visual-question-answering
+- object-detection
+language:
+- en
+tags:
+- remote-sensing
+- geospatial
+- satellite-imagery
+size_categories:
+- 1K<n<10K
 ---
+
+# GeoChat_bench_split Dataset
+
+## Dataset Description
+
+This dataset is a curated subset of the GeoChat_Bench benchmark from the EarthDial-Dataset, specifically containing samples with multiple ground truth bounding boxes.
+
+### Dataset Summary
+
+- **Total Samples:** 1,840
+- **Source:** akshaydudhane/EarthDial-Dataset (GeoChat_Bench subset)
+- **Task:** Visual grounding / object localization in satellite imagery
+- **Modality:** Image (RGB) + Text
+
+### Dataset Structure
+
+The dataset contains 4 columns:
+
+1. **question_id** (string): Unique identifier for each sample
+2. **jpg** (Image): RGB satellite/aerial image
+3. **question** (string): Question asking for object locations (format: "Give me the location of <ref>object description")
+4. **groundtruth** (string): Multiple bounding box coordinates in the format `[[x1,y1,x2,y2,confidence]][[x1,y1,x2,y2,confidence]]...`
+
+### Data Fields
+
+- `question_id`: Unique sample identifier
+- `jpg`: PIL Image object in RGB format
+- `question`: Natural language question with reference tags
+- `groundtruth`: Serialized list of bounding boxes
+
+### Example
+
+```python
+{
+    'question_id': 'sota_2403',
+    'jpg': <PIL.Image>,
+    'question': 'Give me the location of <ref>10 large small-vehicles',
+    'groundtruth': '[[20, 43, 27, 53, 90]][[5, 38, 11, 47, 90]]...'
+}
+```
+
+## Dataset Creation
+
+### Curation Process
+
+1. Loaded GeoChat_Bench from EarthDial-Dataset
+2. Filtered samples containing multiple bounding boxes in ground truth (>1 list)
+3. Sorted by number of bounding boxes in descending order
+4. Selected top 1,840 samples (all available samples with multiple boxes)
+5. Cleaned question text to remove formatting prefixes and tags
+
+### Source Data
+
+Original dataset: [EarthDial-Dataset](https://huggingface.co/datasets/akshaydudhane/EarthDial-Dataset)
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+# Load the dataset
+dataset = load_dataset("yobro4619/GeoChat_bench_split")
+
+# Access samples
+sample = dataset['train'][0]
+print(sample['question'])
+print(sample['groundtruth'])
+```
+
+## License
+
+Please refer to the original [EarthDial-Dataset](https://huggingface.co/datasets/akshaydudhane/EarthDial-Dataset) for licensing information.
+
+## Citation
+
+If you use this dataset, please cite the original EarthDial-Dataset paper.