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_opc
+pretty_name: "MMLA Ol Pejeta Conservancy"
 task_categories:
 - image-classification
 tags:
@@ -13,10 +13,11 @@ tags:
 - drone
 - zebra
 size_categories: 10K<n<100K
+description: " Annotated video frames of Plains zebras collected at the Ol Pejeta Conservancy (OPC) in Kenya using the semi-autonomous WildWing system. includes frames from various sessions, with annotations indicating the presence of zebras in the images in YOLO format. The dataset is intended for use in training and evaluating computer vision models for animal detection and classification from drone imagery to facilitate research in wildlife monitoring and conservation using advanced imaging technologies."
 ---
 
 
-# Dataset Card for mmla-opc
+# Dataset Card for MMLA Ol Pejeta Conservancy
 
 <!-- Provide a quick summary of what the dataset is or can be used for. --> 
 
@@ -30,7 +31,7 @@ with annotations indicating the presence of zebras in the images in YOLO format.
 
 - **Curated by:** Jenna Kline
 - **Homepage:** [mmla project](https://github.com/Imageomics/mmla)
-- **Repository:** [https://github.com/Imageomics/mmla](https://github.com/Imageomics/mmla)
+- **Repository:** [Imageomics/mmla](https://github.com/Imageomics/mmla)
 - **Paper:** [MMLA: Multi-Environment, Multi-Species, Low-Altitude Aerial Footage Dataset](https://arxiv.org/abs/2504.07744)
 
 
@@ -61,7 +62,7 @@ The dataset includes frames extracted from drone videos captured during five dis
 Multiple sessions may occur on the same day but in different locations or targeting different animal groups. During each session, multiple drone videos were recorded to capture animals in their natural habitat under varying environmental conditions.
 
 ## Dataset Structure
-```​
+```
 /dataset/
     classes.txt
     session_1/
@@ -138,7 +139,7 @@ Note on data partitions: HuggingFace limits folders to 10,000 files per folder,
   - `3`: dog
 
 Note: only zebras appear in this dataset; other class labels are included to be consistent across MMLA data collected at other locations, 
-see the data from [Mpala Research Center](https://huggingface.co/datasets/imageomics/mmla_mpala) and [The Wilds](https://huggingface.co/datasets/imageomics/mmla_wilds) datasets.
+see the [MMLA data from Mpala Research Center](https://huggingface.co/datasets/imageomics/mmla_mpala) and [The Wilds MMLA dataset](https://huggingface.co/datasets/imageomics/mmla_wilds).
 
 
 **frame_id.txt**:
@@ -163,7 +164,7 @@ 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.) -->
 
@@ -231,7 +232,7 @@ This dataset (the compilation) has been marked as dedicated to the public domain
 **BibTeX:**
 
 **Data**
-```​
+```
 @misc{mmla_opc,
   author = {Kline, Jenna and 
             Nguyen Ngoc, Dat and
@@ -262,7 +263,7 @@ 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},