Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning VS HugsVision

Compare Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning vs HugsVision and see what are their differences.

Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning

My Computer Vision project from my Computer Vision Course (Fall 2020) at Goethe University Frankfurt, Germany. Performance comparison between state-of-the-art Object Detection algorithms YOLO and Faster R-CNN based on the Berkeley DeepDrive (BDD100K) Dataset. (by alen-smajic)
Our great sponsors
  • WorkOS - The modern identity platform for B2B SaaS
  • InfluxDB - Power Real-Time Data Analytics at Scale
  • SaaSHub - Software Alternatives and Reviews
Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning HugsVision
8 1
57 188
- -
3.6 0.0
about 3 years ago 9 months ago
Jupyter Notebook Jupyter Notebook
MIT License MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

HugsVision

Posts with mentions or reviews of HugsVision. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing Real-time-Object-Detection-for-Autonomous-Driving-using-Deep-Learning and HugsVision you can also consider the following projects:

get-started-with-JAX - The purpose of this repo is to make it easy to get started with JAX, Flax, and Haiku. It contains my "Machine Learning with JAX" series of tutorials (YouTube videos and Jupyter Notebooks) as well as the content I found useful while learning about the JAX ecosystem.

poolformer - PoolFormer: MetaFormer Is Actually What You Need for Vision (CVPR 2022 Oral)

yolo-tf2 - yolo(all versions) implementation in keras and tensorflow 2.x

fashionpedia-api - Python API for Fashionpedia Dataset

simple-faster-rcnn-pytorch - A simplified implemention of Faster R-CNN that replicate performance from origin paper

ganspace - Discovering Interpretable GAN Controls [NeurIPS 2020]

lama - 🦙 LaMa Image Inpainting, Resolution-robust Large Mask Inpainting with Fourier Convolutions, WACV 2022

CoordConv

NYU-DLSP20 - NYU Deep Learning Spring 2020

Transformer-Explainability - [CVPR 2021] Official PyTorch implementation for Transformer Interpretability Beyond Attention Visualization, a novel method to visualize classifications by Transformer based networks.

Mask-RCNN-Implementation - Mask RCNN Implementation on Custom Data(Labelme)

Vision-Project-Image-Segmentation