waze-voicepack-links VS GRID-playground

Compare waze-voicepack-links vs GRID-playground and see what are their differences.

waze-voicepack-links

A collaborative list of Waze navigation voice packs (by pipeeeeees)
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waze-voicepack-links GRID-playground
12 1
148 246
- 0.4%
8.4 4.9
about 2 months ago 11 days ago
Python Python
GNU General Public License v3.0 only GNU General Public License v3.0 or later
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.

waze-voicepack-links

Posts with mentions or reviews of waze-voicepack-links. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-03-24.

GRID-playground

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

What are some alternatives?

When comparing waze-voicepack-links and GRID-playground you can also consider the following projects:

robo-vln - Pytorch code for ICRA'21 paper: "Hierarchical Cross-Modal Agent for Robotics Vision-and-Language Navigation"

AirSim-NeurIPS2019-Drone-Racing - Drone Racing @ NeurIPS 2019, built on Microsoft AirSim

Robotics-Object-Pose-Estimation - A complete end-to-end demonstration in which we collect training data in Unity and use that data to train a deep neural network to predict the pose of a cube. This model is then deployed in a simulated robotic pick-and-place task.

Ricardo - Ricardo is an open-source robot featuring computer vision AI and remote controlling features

autodistill - Images to inference with no labeling (use foundation models to train supervised models).