Update README.md

README.md

@@ -1,3 +1,51 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+task_categories:
+- image-classification
+language:
+- en
+tags:
+- Watermark-or-Not
+- Experimental
+size_categories:
+- 10K<n<100K
+---
+
+# Watermark-or-Not-20K Dataset
+
+## Overview
+
+The **Watermark-or-Not-20K** dataset consists of 20,000 images annotated with binary labels indicating the presence or absence of a watermark. It is designed to support training and evaluation of models focused on watermark detection, which is useful for content filtering, copyright protection, and image moderation tasks.
+
+## Dataset Structure
+
+- **Split:** `train`
+- **Number of samples:** 20,000
+- **Label Type:** Categorical (2 classes)
+- **Image Resolution:** Ranges from 158 pixels to 4.93k pixels in width
+- **Storage Format:** Auto-converted to Parquet for efficient access
+
+## Label Classes
+
+The dataset contains the following classes:
+
+- `0` - No Watermark
+- `1` - Watermark
+
+## Usage
+
+The dataset can be accessed using the Hugging Face `datasets` library:
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("prithivMLmods/Watermark-or-Not-20K")
+````
+
+## Applications
+
+This dataset is suitable for:
+
+* Training computer vision models to detect watermarks
+* Fine-tuning transformer-based vision models on binary classification tasks
+* Building AI-based content moderation pipelines