Update README.md

README.md

@@ -23,7 +23,7 @@ size_categories: 10K<n<100K
 ## Dataset Details
 This is a dataset containing annotated video frames of giraffes, Grevy's zebras, and Plains zebras collected at the Mpala Research Center in Kenya. The dataset is intended for use in training and evaluating computer vision models for animal detection and classification from drone imagery.
 
-The annotations indicate the presence of animals in the images in COCO format. The dataset is designed to facilitate research in wildlife monitoring and conservation using autonomous drones.
+The annotations indicate the presence of animals in the images in YOLO format. The dataset is designed to facilitate research in wildlife monitoring and conservation using autonomous drones.
 
 
 ### Dataset Description
@@ -39,14 +39,14 @@ This dataset contains video frames collected as part of the [Kenyan Animal Behav
 project at the [Mpala Research Center](https://mpala.org/) in Kenya in January 2023. 
 
 Sessions 1 and 2 are derived from the [full-length videos](https://huggingface.co/datasets/imageomics/KABR-mini-scene-raw-videos) 
-used in the [original KABR mini-scene release](https://huggingface.co/datasets/imageomics/KABR), now available in COCO format. 
+used in the [original KABR mini-scene release](https://huggingface.co/datasets/imageomics/KABR), now available in YOLO format. 
 Sessions 3, 4 and 5 are part of the [kabr-tools release](https://huggingface.co/datasets/imageomics/kabr-worked-examples), 
 derived from these [full-length videos](https://huggingface.co/datasets/imageomics/KABR-raw-videos). 
 The dataset is intended for use in training and evaluating computer vision models for animal detection and classification from drone imagery. 
-The dataset includes frames from various sessions, with annotations indicating the presence of zebras in the images in COCO format. 
+The dataset includes frames from various sessions, with annotations indicating the presence of zebras in the images in YOLO format. 
 The dataset is designed to facilitate research in wildlife monitoring and conservation using advanced imaging technologies.
 
-The dataset consists of 104,062 frames. Each frame is accompanied by annotations in COCO format, indicating the presence of zebras and giraffes and their bounding boxes within the images. The annotations were completed manually by the dataset curator using [CVAT](https://www.cvat.ai/) and [kabr-tools](https://github.com/Imageomics/kabr-tools).
+The dataset consists of 104,062 frames. Each frame is accompanied by annotations in YOLO format, indicating the presence of zebras and giraffes and their bounding boxes within the images. The annotations were completed manually by the dataset curator using [CVAT](https://www.cvat.ai/) and [kabr-tools](https://github.com/Imageomics/kabr-tools).
 
 
 | Session | Date Collected | Total Frames | Species | Video File IDs in Session |
@@ -260,7 +260,7 @@ The dataset includes frames extracted from drone videos captured during five dis
 ```
 
 ### Data Instances
-All images are named <video_id_frame>.jpg, each within a folder named for the date of the session. The annotations are in COCO format and are stored in a corresponding .txt file with the same name as the image. 
+All images are named <video_id_frame>.jpg, each within a folder named for the date of the session. The annotations are in YOLO format and are stored in a corresponding .txt file with the same name as the image. 
 
 Note on data partitions: DJI saves video files into 3GB chunks, so each session is divided into multiple video files. HuggingFace limits folders to 10,000 files per folder, so each video file is further divided into partitions of 10,000 files. The partition folders are named `partition_1`, `partition_2`, etc. The original video files are not included in the dataset.
 
@@ -310,7 +310,7 @@ This is what _you_ did to it following collection from the original source; it w
 
 The data was collected manually using a [DJI Air 2S drone](https://www.dji.com/support/product/air-2s). The drone was flown at the [Mpala Research Center](https://mpala.org/) in Laikipia, Kenya, capturing video footage of giraffes, Grevy's zebras, and Plains zebras in their natural habitat.
 
-The videos were annotated manually using the Computer Vision Annotation Tool [CVAT](https://www.cvat.ai/) and [kabr-tools](https://github.com/Imageomics/kabr-tools). These detection annotations and original video files were then processed to extract individual frames, which were saved as JPEG images. The annotations were converted to COCO format, with bounding boxes indicating the presence of zebras in each frame.
+The videos were annotated manually using the Computer Vision Annotation Tool [CVAT](https://www.cvat.ai/) and [kabr-tools](https://github.com/Imageomics/kabr-tools). These detection annotations and original video files were then processed to extract individual frames, which were saved as JPEG images. The annotations were converted to YOLO format, with bounding boxes indicating the presence of zebras in each frame.
 
 <!-- #### Who are the source data producers?
 [More Information Needed] -->
@@ -328,7 +328,7 @@ Ex: We standardized the taxonomic labels provided by the various data sources to
 
 
 #### Annotation process
-[CVAT](https://www.cvat.ai/) and [kabr-tools](https://github.com/Imageomics/kabr-tools) were used to annotate the video frames. The annotation process involved manually labeling the presence of animals in each frame, drawing bounding boxes around them, and converting the annotations to COCO format.
+[CVAT](https://www.cvat.ai/) and [kabr-tools](https://github.com/Imageomics/kabr-tools) were used to annotate the video frames. The annotation process involved manually labeling the presence of animals in each frame, drawing bounding boxes around them, and converting the annotations to YOLO format.
 <!-- This section describes the annotation process such as annotation tools used, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. -->
 
 #### Who are the annotators?