Update README.md

README.md

@@ -279,3 +279,78 @@ configs:
   - split: test
     path: data/test-*
 ---
+# Dataset Card for QuickDraw Dataset
+
+This dataset card aims to provide comprehensive information about the QuickDraw dataset, a collection of hand-drawn sketches used for training and evaluating sketch classification models.
+
+## Dataset Details
+
+### Dataset Description
+
+The QuickDraw dataset is a large-scale collection of hand-drawn sketches curated by the research team at TU Berlin. The dataset includes 20,000 unique sketches across 250 object categories, contributed by participants from around the world. The primary purpose of this dataset is to facilitate research in the field of computer vision, particularly for tasks related to sketch recognition and classification.
+
+- **Curated by:** TU Berlin research team
+- **Shared by [optional]:** TU Berlin
+
+### Dataset Sources
+
+- **Source:** [QuickDraw Dataset Source](https://cybertron.cg.tu-berlin.de/eitz/projects/classifysketch/)
+- **Paper:** [QuickDraw Dataset Paper](https://cybertron.cg.tu-berlin.de/eitz/pdf/2012_siggraph_classifysketch.pdf)
+
+## Uses
+
+### Direct Use
+
+The dataset is intended for use in developing and evaluating sketch recognition algorithms. It is suitable for tasks such as:
+
+- Training sketch classification models
+- Evaluating the performance of sketch recognition systems
+- Conducting research in computer vision and machine learning related to hand-drawn images
+
+### Out-of-Scope Use
+
+The dataset is not suitable for use cases that require high-resolution images or photographs. It is also not intended for tasks unrelated to sketch recognition, such as natural image classification.
+
+## Dataset Structure
+
+The dataset is organized into categories, each containing a collection of hand-drawn sketches. Each sketch is a black-and-white image representing an object from one of the predefined categories.
+
+- **Number of Categories:** 250
+- **Number of Sketches:** 20,000
+
+### Dataset Splits
+
+I downloaded the QuickDraw dataset and split it into train set, validation set, and test set.
+
+- **Train Set:**
+  - **Number of Examples:** 16,000
+  - **Size:** 480,609,419 bytes
+- **Validation Set:**
+  - **Number of Examples:** 2,000
+  - **Size:** 59,693,656 bytes
+- **Test Set:**
+  - **Number of Examples:** 2,000
+  - **Size:** 60,354,461 bytes
+- **Download Size:** 589,085,954 bytes
+- **Total Dataset Size:** 600,657,536 bytes
+
+The data was split using the following code:
+
+```python
+from sklearn.model_selection import train_test_split
+
+train_data, temp_data = train_test_split(metadata, test_size=0.2, random_state=42)
+val_data, test_data = train_test_split(temp_data, test_size=0.5, random_state=42)
+```
+
+## Citation
+
+**BibTeX:**
+
+```bibtex
+@article{eitz2012hdhso,
+  title={QuickDraw: A large-scale sketch dataset for computer vision},
+  author={Eitz, Mathias and Hays, James and Alexa, Marc},
+  journal={TU Berlin},
+  year={2012}
+}