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Machine Learning

Team

Name Student ID Path
Ryan Reynickha Fatullah M296BSY1298 Machine Learning
Syifa Nur'Afni Hidayat M494BSX0800 Machine Learning

About The Project

In order to create our model, we utilized Machine Learning with the architecture of CNN (Convolutional Neural Network). The dataset we used for training the model is called Fruit and Vegetables SSM.

Endpoint API

we have a endpoint that can be used to classify fruits & vegetables images with architecture of CNN (Convolutional Neural Network).

Method Routes Type Description
Predict
POST /predict multipart/form-data Predict uploaded fruits & vegetables images

Built With

  • Uvicorn (fastapi)
  • Tensorflow
  • Pillow
  • Python-multipart
  • Numpy

Try This Project

Dive into this project and discover its functionalities.

Prerequisites

Before you start, ensure that you have the following software installed on your system:

  • Python 3.10.x
  • Pip 22.x.x
  • Git LFS

Installation

  1. Clone the repo

     git clone https://github.com/Ingridentify/Machine-Learning.git
 git lfs pull

  2. Move to ./Machine-Learning directory

     cd ./Machine-Learning

  3. Install requirements using PIP

     pip install -r requirements.txt

  4. Run ml service application

     python app.py

Requirements

  • fastapi
  • tensorflow
  • Pillow
  • numpy
  • uvicorn[standard]
  • python-multipart

Important Link