Update README.md

README.md

@@ -1,19 +1,19 @@
 ---
 license: cc-by-nc-nd-4.0
 task_categories:
-  - object-detection
-  - image-classification
+- object-detection
+- image-classification
 size_categories:
-  - n<1K
+- 1K<n<10K
 tags:
-  - indian-vehicles
-  - vehicle-detection
-  - object-detection
-  - image-classification
-  - computer-vision
-  - automotive
-  - self-driving
-  - traffic-analysis
+- indian-vehicles
+- vehicle-detection
+- object-detection
+- image-classification
+- computer-vision
+- automotive
+- self-driving
+- traffic-analysis
 pretty_name: Indian Vehicle Dataset (Sample)
 ---
 
@@ -47,7 +47,7 @@ Scenes cover a wide variety of road scenarios, including dense city traffic, hig
 |  | Sample (this repo) | Full Dataset |
 | --- | --- | --- |
 | Images | ~200 (subset) | 50,000+ |
-| Annotation formats | Pascal VOC / YOLO / COCO | COCO, YOLO, Pascal VOC, TF-Record |
+| Annotation formats | Pascal VOC (XML) — other formats available on request | COCO, YOLO, Pascal VOC, TF-Record |
 | Locations covered | Representative subset | 1,000+ cities across India |
 | Resolution | HD (1920×1080 and above) | HD (1920×1080 and above) |
 | Scene diversity | Representative subset | Full range (urban, rural, day, night, close, far) |
@@ -64,18 +64,14 @@ indian-vehicle-dataset/
 ├── images/                  # JPG images
 │   ├── image_0001.jpg
 │   └── ...
-└── annotations/             # Annotations in multiple formats
-    ├── voc/                 # Pascal VOC XML annotations (one per image)
-    │   ├── image_0001.xml
-    │   └── ...
-    ├── yolo/                # YOLO TXT annotations (one per image)
-    │   ├── image_0001.txt
-    │   └── ...
-    └── coco/                # COCO JSON annotations
-        └── annotations.json
+└── annotations/             # Pascal VOC XML annotations (one per image)
+    ├── image_0001.xml
+    └── ...
 ```
 
-Each annotation file contains bounding-box labels for the vehicle classes listed above, with filenames matching their corresponding image.
+Each XML file contains bounding-box annotations in the Pascal VOC format, with filenames matching their corresponding image.
+
+> **Need a different annotation format?** This sample ships in Pascal VOC (XML) only. YOLO, COCO, and TF-Record versions are available on request — see the conversion snippet below, or contact [sales@datacluster.ai](mailto:sales@datacluster.ai).
 
 ## Data Collection
 
@@ -105,17 +101,17 @@ git clone https://huggingface.co/datasets/Dataclusterlabspvtltd/Indian-Vehicle-D
 
 ### Convert VOC to YOLO or COCO
 
-If you only have Pascal VOC annotations, convert easily with `pylabel`:
+The sample ships in Pascal VOC format. Convert easily with `pylabel`:
 
 ```python
 from pylabel import importer
 
 # VOC → YOLO
-dataset = importer.ImportVOC(path="annotations/voc")
-dataset.export.ExportToYoloV5(output_path="annotations/yolo")
+dataset = importer.ImportVOC(path="annotations")
+dataset.export.ExportToYoloV5(output_path="annotations_yolo")
 
 # VOC → COCO
-dataset.export.ExportToCoco(output_path="annotations/coco/annotations.json")
+dataset.export.ExportToCoco(output_path="annotations_coco/annotations.json")
 ```
 
 ## License