GitHub - yogirajgutte/Image-Classifier-and-Text-Extractor: This application can classify images and extract texts that are present on the screen of user. It is very easy to use.

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This application can classify images and extract texts that are present on the screen of user. It is very easy to use.

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Name		Name	Last commit message	Last commit date
Latest commit History 15 Commits
Model Training and Testing		Model Training and Testing
Web-Based GUI		Web-Based GUI
What's On My Screen		What's On My Screen
screenshots		screenshots
Image Classification Using Convolutional Neural Networks Report.pdf		Image Classification Using Convolutional Neural Networks Report.pdf
LICENSE		LICENSE
Model_tf.z01		Model_tf.z01
Model_tf.z02		Model_tf.z02
Model_tf.z03		Model_tf.z03
Model_tf.z04		Model_tf.z04
Model_tf.z05		Model_tf.z05
Model_tf.zip		Model_tf.zip
README.txt		README.txt

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Demo Video: https://www.linkedin.com/feed/update/urn:li:activity:6756269221916762112/

This tool was made by me and my colleague as a project for college.
The repository contains 'Image Classification using Convolutional Neural Networks.pdf' as a report to this project
Follow the guidelines given below in order to use it.




1) 'Model Training and Testing' folder contains the Jupyter Notebooks with code for training and testing of the models.

2) 'Web-Based GUI' folder contains a web-based app which can be used for data visualization and model testing.

3) 'What's On My Screen' folder contains the standalone app based on the CNN model and Tesseract Engine. It can be used in realtime. More details are present in the folder.

4) Extract 'Model_tf.zip' to the same directory.

5) 'Model_tf' folder contains the trained model. It is important as both the apps use data from this folder. There's no need to open this folder.