/MMDetection-FasterRCNN

Ready to dive into the world of object detection? My MMDetection-FasterRCNN repository is your go-to resource for training a lightning-fast Faster R-CNN model on the KITTI tiny dataset. With my Jupyter Notebook, you'll embark on a seamless journey from setup to evaluation, leveraging the capabilities of MMDetection.

Primary LanguageJupyter Notebook

MMDetection-FasterRCNN

This repository contains an Jupyter Notebook (MMDetection_FasterRCNN.ipynb) for training a Faster R-CNN model on a KITTI tiny dataset using MMDetection.

Overview

This Jupyter Notebook provides a step-by-step guide to training a Faster R-CNN object detection model on the KITTI tiny dataset. The model is implemented using MMDetection, a state-of-the-art open-source object detection toolbox based on PyTorch.

Notebook Structure

  • MMDetection_FasterRCNN.ipynb: This Jupyter Notebook contains the code for setting up the training pipeline, configuring the Faster R-CNN model, loading and preprocessing the dataset, training the model, and evaluating its performance.

Requirements

  • Python 3.x
  • Jupyter Notebook or JupyterLab (from Anaconda)

Make sure to install all the necessary dependencies before running the notebook.

Dataset

The KITTI tiny dataset used in this notebook can be obtained from OpenMMLab: KITTI Dataset