https://github.com/mdaiyub/koala-detection

Object detection is a major area of computer vision applications. For the task I utilized a set of images that contain instances of Koala. The goal is to preprocess the images and build a dataset, train an object detection model using the prepared dataset, and develop an API for getting inferences from the model.
https://github.com/mdaiyub/koala-detection

Last synced: about 4 hours ago
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Object detection is a major area of computer vision applications. For the task I utilized a set of images that contain instances of Koala. The goal is to preprocess the images and build a dataset, train an object detection model using the prepared dataset, and develop an API for getting inferences from the model.

• Host: GitHub
• URL: https://github.com/mdaiyub/koala-detection
• Owner: mdaiyub
• Created: 2023-11-18T13:17:56.000Z (12 months ago)
• Default Branch: main
• Last Pushed: 2023-11-19T08:08:18.000Z (12 months ago)
• Last Synced: 2023-11-19T15:00:55.863Z (12 months ago)
• Language: Jupyter Notebook
• Homepage:
• Size: 957 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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# Koala-Detection

Custom YOLO Version DATA LINK: [Koala-Detection](https://drive.google.com/drive/folders/1_aKb-jiZBP3Xi9fnzs8rtcBHEQsaG5Id?usp=sharing)

To get the data set into the YOLO version, I first manually annotated each data bound box by Roboflow online annotator tools, 

then exported the annotated and non-annotated data simultaneously to the YOLO version.