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ArcVision - Image Recognition API

Introduction

This is a Flask-based Image Recognition API that allows users to upload images and receive predictions or information about the recognized objects. This project is designed as a hackathon product, providing a simple and efficient way to perform image recognition tasks using pre-trained machine learning model which is finetuned for smaller devices i.e YOLO Lite.

Features

  • User-friendly Interface : The API provides a simple web interface where users can upload images easily.
  • Object Detection : Utilizes YOLO Lite Self made (You Only Look Once) model for object detection in images.
  • Output Visualization : The recognized objects are highlighted in the output image with bounding boxes and labels.

Login

login_screenshot

Index

login_screenshot

Input

login_screenshot

Output

login_screenshot

Getting Started

We are using Python Anywhere to host the server but you can do it on your Personal Computer

Prerequisites

Make sure you have a Decent PC or Server with following installed:

  • Python
  • Flask
  • OpenCV

Installation

  1. Clone the Repository.
git clone https://github.com/bharathajjarapu/HackerzRec.git
  1. Change Directory.
cd ArcVision
  1. Install the Requirements
pip install flask opencv-contrib-python
  1. Then run the python file in terminal
python app.py
  1. Or If you are using PythonAnywhere run the python file in terminal
python main.py

Usage

  1. Open your web browser and go to http://127.0.0.1:5000/.
  2. Upload an image using the provided form.
  3. Click on the "Detect Object" button.
  4. View the results on the result page, highlighting the recognized objects in the output image.

Project Structure

  • app.py: The main Flask application file containing the routes and image processing logic.
  • templates/: Folder containing HTML templates for the web interface.
  • templates/index.html: Main page for image upload.
  • templates/result.html: Page displaying input and output images with recognized objects.

Happy hacking!