Add short description for API access and fix some formatting

README.md

@@ -2,7 +2,7 @@
 license: cc0-1.0
 language:
 - en
-pretty_name: mmla_wilds
+pretty_name: "MMLA The Wilds"
 task_categories: [image-classification]
 tags:
 - biology
@@ -12,10 +12,11 @@ tags:
 - drone
 - zebra
 size_categories: 10K<n<100K
+description: "Annotated video frames of giraffes, Grevy's zebras, Persian onagers, and African Painted Dogs collected at The Wilds in Ohio. This dataset is intended for use in training and evaluating computer vision models for animal detection and classification from drone imagery. It includes frames from various sessions, with annotations indicating the presence of animals in the images in YOLO format, and is designed to facilitate research in wildlife monitoring and conservation using autonomous drones."
 ---
 
 
-# Dataset Card for mmla-wilds
+# Dataset Card for MMLA The Wilds
 
 <!-- Provide a quick summary of what the dataset is or can be used for. --> 
 
@@ -26,8 +27,8 @@ This is a dataset containing annotated video frames of giraffes, Grevy's zebras,
 ### Dataset Description
 
 - **Curated by:** Jenna Kline
-- **Homepage:** [mmla](https://imageomics.github.io/mmla/)
-- **Repository:** [https://github.com/imageomics/mmla](https://github.com/imageomics/mmla)
+- **Homepage:** [MMLA website](https://imageomics.github.io/mmla/)
+- **Repository:** [imageomics/mmla](https://github.com/imageomics/mmla)
 - **Paper:** [MMLA: Multi-Environment, Multi-Species, Low-Altitude Drone Dataset](https://arxiv.org/abs/2504.07744)
 
 <!-- Provide a longer summary of what this dataset is. -->
@@ -52,7 +53,7 @@ The dataset is intended for use in training and evaluating computer vision model
 
 
 ## Dataset Structure
-```​
+```
 /dataset/
     README.md
     session_1/
@@ -127,7 +128,7 @@ Give your train-test splits for benchmarking; could be as simple as "split is in
 The dataset was created to facilitate research in wildlife monitoring and conservation using advanced imaging technologies. The goal is to develop and evaluate computer vision models that can accurately detect and classify animals from drone imagery, and their generalizability across different species and environments.
 
 
-<!-- ### Source Data -->
+### Source Data
 
 <!-- This section describes the source data (e.g., news text and headlines, social media posts, translated sentences, ...). As well as an original source it was created from (e.g., sampling from Zenodo records, compiling images from different aggregators, etc.) -->
 
@@ -202,7 +203,7 @@ This dataset (the compilation) has been marked as dedicated to the public domain
 
 
 **Data**
-```​
+```
 @misc{mmla_wilds,
   author = {  Jenna Kline,
               Alison Zhong,
@@ -217,7 +218,7 @@ This dataset (the compilation) has been marked as dedicated to the public domain
 ```
 
 **Paper**
-```​
+```
 @misc{kline2025mmla,
       title={MMLA: Multi-Environment, Multi-Species, Low-Altitude Drone Dataset}, 
       author={Jenna Kline and Samuel Stevens and Guy Maalouf and Camille Rondeau Saint-Jean and Dat Nguyen Ngoc and Majid Mirmehdi and David Guerin and Tilo Burghardt and Elzbieta Pastucha and Blair Costelloe and Matthew Watson and Thomas Richardson and Ulrik Pagh Schultz Lundquist},
@@ -232,7 +233,7 @@ This dataset (the compilation) has been marked as dedicated to the public domain
 If you use this dataset, please cite the [WildWing video dataset](https://huggingface.co/datasets/imageomics/wildwingdeployment) used to generate data for sessions 2-4.
 
 **Related Papers**
-```​
+```
 @article{kline2025wildwing,
   title={WildWing: An open-source, autonomous and affordable UAS for animal behaviour video monitoring},
   author={Kline, Jenna and Zhong, Alison and Irizarry, Kevyn and Stewart, Charles V and Stewart, Christopher and Rubenstein, Daniel I and Berger-Wolf, Tanya},