HybridNets VS YOLOP

Compare HybridNets vs YOLOP and see what are their differences.

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HybridNets YOLOP
2 5
560 1,823
- 1.5%
4.7 3.2
5 months ago 7 months ago
Python Python
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.

HybridNets

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

YOLOP

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

What are some alternatives?

When comparing HybridNets and YOLOP you can also consider the following projects:

medicaldetectiontoolkit - The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.

PaddleSeg - Easy-to-use image segmentation library with awesome pre-trained model zoo, supporting wide-range of practical tasks in Semantic Segmentation, Interactive Segmentation, Panoptic Segmentation, Image Matting, 3D Segmentation, etc.

albumentations - Fast image augmentation library and an easy-to-use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about the library: https://www.mdpi.com/2078-2489/11/2/125

Ultra-Fast-Lane-Detection - Ultra Fast Structure-aware Deep Lane Detection (ECCV 2020)

mmrazor - OpenMMLab Model Compression Toolbox and Benchmark.

jiant - jiant is an nlp toolkit

ml-cvnets - CVNets: A library for training computer vision networks

SGDepth - [ECCV 2020] Self-Supervised Monocular Depth Estimation: Solving the Dynamic Object Problem by Semantic Guidance