OCR Based Compiler for Java and C plus plus
The ?OCR (Optical Character Recognition) based Compiler for Java and C++ using Android? makes users extract and edit the code which is hand written or in printed form into a mobile phone. This application can help students, teachers as well as programmers to quickly know whether the writt
Project Title
OCR Based Compiler for Java and C plus plus
Project Area of Specialization
Project Summary
The “OCR (Optical Character Recognition) based Compiler for Java and C++ using Android” makes users extract and edit the code which is hand written or in printed form into a mobile phone. This application can help students, teachers as well as programmers to quickly know whether the written code is error free or not. The application allows user to select two basic languages that is JAVA and C++. After selecting language, user is be able to choose image format. The image format can be either in handwritten or in printed form. The image can be captured through a camera. The image written on the page or on whiteboard should be in neat and understandable form, so that Optical Character Recognition is able to extract and edit the code. It is an offline application needs not the presence of an internet. The main aim is to facilitate to the students while learning, teachers who find difficulty in checking papers etc. and for those needy students who cannot afford laptops and PC.
Project Objectives
The aim and objectives of the project are
- to extract Programming code (Printed or Handwritten) into a mobile phone
- to compile Programming code on Android phone
- to show results (Errors and output)
Project Implementation Method
To implement “OCR based compiler for JAVA and C++” in Android the languages explored and used are C++, Java, XML and Python. The first challenge was to create a dataset of characters that is to be used by OCR in decision/comparison stage so, to train the dataset the anaconda with jupyter notebook is configured that is used for accessing the google colab. Python is used on Jupyter notebook to train the dataset and to achieve the processing efficiency Google GPU’s and Floyd-hub is used which is paid GPU’s for training the dataset. This method gives us the dataset in protobuff (.pb) and tflite (.tflite) format, which is used with real time SDK to improve the response time while extracting the code form image.
Benefits of the Project
Newbie programmers have lot of benefits through this application. Its reduces their time in understanding logic, it helps them dry run their code automatically. In short, it provides one click compilation.
Technical Details of Final Deliverable
Android Application (APK file)
Trained Model (.pb , .tflite)
Final Deliverable of the Project
Type of Industry
Technologies
Sustainable Development Goals
Required Resources
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| FloydHUB | Equipment | 1 | 15500 | 15500 |
| Real Time SDK | Equipment | 1 | 4000 | 4000 |
| Miscellaneous | Miscellaneous | 1 | 10000 | 10000 |
| Total in (Rs) | 29500 |
If you need this project, please contact me on contact@adikhanofficial.com
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