Skip to content

roboflow-ai/Monk_Object_Detection

master
Switch branches/tags
Code
This branch is 27 commits ahead, 597 commits behind Tessellate-Imaging:master.
Contribute

Latest commit

 

Git stats

Files

Permalink
Failed to load latest commit information.
Type
Name
Latest commit message
Commit time
 
 
 
 
 
 
 
 
 
 

EfficientDet Pytorch Implementation with Roboflow

Thanks to Monk_Object_Detection for providing the pytorch implementation! Tessellate Imaging - https://www.tessellateimaging.com/

Running on local? Check out ./3_mxrcnn/installation for installation requirements that are different than the Colab tutorial.

What You Will Learn

  • How to load your custom image detection data from Roboflow
  • How to instatiate a pytorch EfficientDet model
  • How to train the EfficientDet model
  • How to use the model for quick inference
  • How to export the model weights for future inference
  • How to reload the model weights

Resources

  • This blog post provides an in depth dive into using the tutorial
  • This notebook provides the code necessary to run the tutorial Open In Colab
  • For reading purposes, the notebook is also saved in Tutorial.ipynb

About Roboflow for Data Management

Roboflow makes managing, preprocessing, augmenting, and versioning datasets for computer vision seamless. Developers reduce 50% of their code when using Roboflow's workflow, automate annotation quality assurance, save training time, and increase model reproducibility.

alt text

Copyright

Copyright 2019 onwards, Tessellate Imaging Private Limited Licensed under the Apache License, Version 2.0 (the "License"); you may not use this project's files except in compliance with the License. A copy of the License is provided in the LICENSE file in this repository.

Releases

No releases published

Packages

No packages published

Languages

  • Jupyter Notebook 98.6%
  • Python 1.3%
  • Shell 0.1%
  • Cython 0.0%
  • C 0.0%
  • C++ 0.0%