make-sense VS awesome-object-detection

Compare make-sense vs awesome-object-detection and see what are their differences.

awesome-object-detection

Awesome Object Detection based on handong1587 github: https://handong1587.github.io/deep_learning/2015/10/09/object-detection.html (by amusi)
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make-sense awesome-object-detection
7 1
2,969 7,245
- -
2.4 10.0
about 2 months ago over 1 year ago
TypeScript
GNU General Public License v3.0 only -
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.

make-sense

Posts with mentions or reviews of make-sense. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-12-07.

awesome-object-detection

Posts with mentions or reviews of awesome-object-detection. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-03-30.

What are some alternatives?

When comparing make-sense and awesome-object-detection you can also consider the following projects:

label-studio - Label Studio is a multi-type data labeling and annotation tool with standardized output format

darkflow - Translate darknet to tensorflow. Load trained weights, retrain/fine-tune using tensorflow, export constant graph def to mobile devices

cvat - Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale. [Moved to: https://github.com/cvat-ai/cvat]

ImageAI - A python library built to empower developers to build applications and systems with self-contained Computer Vision capabilities

AID - One-Stop System for Machine Learning.

YOLOv3_TensorFlow - Complete YOLO v3 TensorFlow implementation. Support training on your own dataset.

VoTT - Visual Object Tagging Tool: An electron app for building end to end Object Detection Models from Images and Videos.

gluon-cv - Gluon CV Toolkit

Universal Data Tool - Collaborate & label any type of data, images, text, or documents, in an easy web interface or desktop app.

SynthDet - SynthDet - An end-to-end object detection pipeline using synthetic data

pytorch-pose-hg-3d - PyTorch implementation for 3D human pose estimation

notebooks - Examples and tutorials on using SOTA computer vision models and techniques. Learn everything from old-school ResNet, through YOLO and object-detection transformers like DETR, to the latest models like Grounding DINO and SAM.