Welcome to this repository for object detection using the Indoor Object Detection Dataset by Adhikari and Bishwo. This repository contains a Colab notebook that demonstrates how to train an object detector using the dataset.
The Indoor Object Detection Dataset by Adhikari and Bishwo contains images of indoor scenes with labeled objects. The dataset includes a total of 7 classes of objects and 2213 images.
Google Colab TensorFlow 2.x Python 3
Clone this repository:
git clone https://github.com/d-duran/IndoorObjectDetection.git
Open the Colab notebook: indoor_object_detection.ipynb
Run the notebook
The Colab notebook contains all the code necessary to train and evaluate an object detector using the Indoor Object Detection Dataset. The notebook also includes instructions on how to use the trained model to detect objects in new images.
The object detector is able to achieve good performance on the test set of the Indoor Object Detection Dataset. The model can be used for various indoor object detection applications.
I would like to thank Adhikari and Bishwo for providing this dataset.
Adhikari, Bishwo. (2022). Indoor Object Detection Dataset. https://zenodo.org/record/2654485#.Y9FTiRXMJD9
The code in this repository is available under the MIT License.