Separating text from image

[harshmishra19]

Deep Learning Simplified Repository (Proposing new issue)

:red_circle: Separating text from image : :red_circle:Aim of the project is to provide users with a code that can help them take out text from images and automatically get an report generated on that image : :red_circle: Dataset : :red_circle: Using some libraries like pytesseract : Try to use 3-4 algorithms to implement the models and compare all the algorithms to find out the best fitted algorithm for the model by checking the accuracy scores. Also do not forget to do a exploratory data analysis before creating any model.

---

📍 Follow the Guidelines to Contribute in the Project :

• You need to create a separate folder named as the Project Title.
• Inside that folder, there will be four main components.
  • Images - To store the required images.
  • Dataset - To store the dataset or, information/source about the dataset.
  • Model - To store the machine learning model you've created using the dataset.
  • requirements.txt - This file will contain the required packages/libraries to run the project in other machines.
• Inside the Model folder, the README.md file must be filled up properly, with proper visualizations and conclusions.

---

:red_circle::yellow_circle: Points to Note :

• The issues will be assigned on a first come first serve basis, 1 Issue == 1 PR.
• "Issue Title" and "PR Title should be the same. Include issue number along with it.
• Follow Contributing Guidelines & Code of Conduct before start Contributing.

---

:white_check_mark: To be Mentioned while taking the issue :

• Full name : Harsh Mishra
• GitHub Profile Link : https://github.com/harshmishra19
• Email ID : [email protected]
• Participant ID (if applicable):
• Approach for this Project :
• What is your participant role? (Mention the Open Source program) Gssoc'24

---

Happy Contributing 🚀

All the best. Enjoy your open source journey ahead. 😎

[github-actions[bot]]

Thank you for creating this issue! We'll look into it as soon as possible. Your contributions are highly appreciated! 😊

[abhisheks008]

Please share the dataset and your approach for solving this issue. @harshmishra19

[harshmishra19]

yea here's the breakdown

• Image Analysis: The program will leverage any available Vision API to analyze the uploaded image.
• Text Extraction: The program will utilize the Optical Character Recognition (OCR) capabilities of the chosen API to extract all text content within the image.
• Visual Element Segmentation: Basic image segmentation techniques will be implemented to potentially isolate individual visual elements present within the main image.

Image Used

and here is the result image during processing

And here is the report Generated

[abhisheks008]

What are the deep learning techniques you are planning to implement here?

[harshmishra19]

Currently I am using Pytesseract which is a Python wrapper for Google's Tesseract-OCR Engine, which is an optical character recognition (OCR) tool used to extract text from images. But I can opt for Convolutional Neural Networks (CNNs) EAST (Efficient and Accurate Scene Text Detector): This model can detect text in natural scenes.

[abhisheks008]

Currently I am using Pytesseract which is a Python wrapper for Google's Tesseract-OCR Engine, which is an optical character recognition (OCR) tool used to extract text from images. But I can opt for Convolutional Neural Networks (CNNs) EAST (Efficient and Accurate Scene Text Detector): This model can detect text in natural scenes.

Implement all the above mentioned models for this dataset and find out the best fitted one based on the accuracy scores of the implemented models/methods.

Assigned @harshmishra19