Blood-Cell-Detection-using-TFOD-API

This project demonstrates the use of TensorFlow Object Detection API (along with GCP ML Engine) to automatically detect Red Blood Cells (RBCs), White Blood Cells (WBCs), and Platelets in each image taken via microscopic image readings

MIT License

Stars
22
View Code on GitHub View on X
Ecosystems: Jupyter Notebook

Statistics for this project are still being loaded, please check back later.

Related Projects
TensorFlow-Lite-Object-Detection-on-Android-and-Raspberry-Pi

A tutorial showing how to train, convert, and run TensorFlow Lite object detection models on Andr...

21 Sep 2019 1,497
Vehicle-Number-Plate-Detection

This project demonstrates the use of TensorFlow Object Detection API to automatically number plat...

24 Aug 2019 35
ml-deployment-k8s-tfserving

This project shows how to serve an TF based image classification model as a web service with TFSe...

17 May 2022 119
Global-Wheat-Detection

Showcases the use of deep learning to detect wheat heads from crops. The project is based on: htt...

06 May 2020 18
salsa-valentina

08 Jun 2019 1
ML-Bootcamp-Launchpad

Contains notebooks prepared for ML Bootcamp organized by Google Developers Launchpad.

05 Dec 2019 51
E2E-Object-Detection-in-TFLite

This repository shows how to train a custom detection model with the TFOD API, optimize it with T...

10 Sep 2020 28