nstiwari / e2e-tflite-tutorials Goto Github PK

• 🔭 Software Engineer | LTIMindtree
• 🌱 Google Developer Expert - Machine Learning
• 🖊️ Contributor to Google Dev Library
• 💬 I also write blogs on Machine Learning and Deep Learning applications on Medium.
• 📫 If you think I can help you, let's connect and talk on LinkedIn.

Following are some of my favorite repositories that I have contributed to and/or contribute to.

FarmScan: Farmer's Assistance is an implementation of using the Google Pro Vision model API on Android to recognize the freshness of fruits/vegetables, its approximate market value, shelf life, and a lot more insights to help farms plan cultivation/selling of crops better.

This project is an implementation of fine-tuning an SDXL model using DreamBooth and LoRA on custom data of interior rooms to generate designs for your home.

PharmaScan is an Android application that leverages Gemini Pro Vision model to identify medicines and provide their details such as usage, dosage, diagnosis, etc on-the-go.

As an initiative to solve for environment, this project is an implementation of detecting various categories of waste in real-time by deploying a TF Lite model directly on the browser.

Create a video game controller that plays the game for you by detecting and classifying human poses. This project is an end-to-end tutoial to train a pose classifier model and deploy it using TF Lite.

A cool project where Computer Vision meets video games. This project lets you do object detection in Grand Theft Auto: Vice City, in real-time.

A fun image classification Android app built using TF Lite that classifies cartoons.

An end-to-end project on training a custom object detection model and deploying it on the browser using TensorFlow.js.

A Computer Vision application built using TensorFlow for businesses that require data pipelines for extraction of visual data (graphs and charts) from images and dashboards.

Train a custom text classifier and deploy it on an Android app using TF Lite.

Train a YOLOv3 Custom Object Detection model and inference the detections using Python and OpenCV.

Convert YOLOv3 based models into TF Lite version using Python and inference the results using OpenCV.