Update README.md

README.md

@@ -1,3 +1,76 @@
----
-license: apache-2.0
----
+---
+annotations_creators:
+- crowdsourced
+
+language:
+- en
+language_creators:
+- crowdsourced
+license: []
+multilinguality:
+- monolingual
+paperswithcode_id: imagenet
+pretty_name: Tiny-ImageNet
+size_categories:
+- 100K<n<1M
+source_datasets:
+- extended|imagenet-1k
+task_categories:
+- image-classification
+task_ids:
+- multi-class-image-classification
+---
+
+# Dataset Card for tiny-imagenet-200-clean
+
+## Dataset Description
+
+- **Homepage:** https://www.kaggle.com/c/tiny-imagenet
+- **Repository:** [Needs More Information]
+- **Paper:** http://cs231n.stanford.edu/reports/2017/pdfs/930.pdf
+- **Leaderboard:** https://paperswithcode.com/sota/image-classification-on-tiny-imagenet-1
+
+### Dataset Summary
+
+The original Tiny ImageNet contained 100000 images of 200 classes (500 for each class) downsized to 64×64 colored images. Each class has 500 training images, 50 validation images, and 50 test images.
+This cleaned version removed grey scale images and only kept RGB images.
+
+### Languages
+
+The class labels in the dataset are in English.
+
+## Dataset Structure
+
+### Data Instances
+
+```json
+{
+  'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=64x64 at 0x1A800E8E190,
+  'label': 15
+}
+```
+
+### Data Fields
+
+- image: A PIL.Image.Image object containing the image. Note that when accessing the image column: dataset[0]["image"] the image file is automatically decoded. Decoding of a large number of image files might take a significant amount of time. Thus it is important to first query the sample index before the "image" column, i.e. dataset[0]["image"] should always be preferred over dataset["image"][0].
+- label: an int classification label. -1 for test set as the labels are missing. Check `classes.py` for the map of numbers & labels.
+
+### Data Splits
+
+|              | Train  | Validation | Test |
+| ------------ | ------ | ----- |-----------|
+| # of samples | 98179 | 4909 | 4923 |
+
+## Usage
+
+### Example
+
+#### Load Dataset
+```python
+def example_usage():
+    tiny_imagenet = load_dataset('slegroux/tiny-imagenet-200-clean', split='train')
+    print(tiny_imagenet[0])
+
+if __name__ == '__main__':
+    example_usage()
+```