PhotoStat is intended to be a web-based AI to solve introductory hypothesis tests (z-tests and t-tests of Normal distributions) by inserting an image of a word problem or typing out the question.
This project is a work in progress. I will first implement the project without using machine learning. I will extract necessary data from the word problem using other methods for the initial implementation of the project. Then, I will re-implement the project using machine learning.
- Website with a simple interface to take/insert an image of a word problem or type out the question
- Option to take a picture of the word problem
- Option to upload a picture of the word problem
- Option to type out the word problem
- Allow users to view a step-by-step process of the hypothesis test
- Option to copy the solution to the clipboard or save it to a file
View more information about the AI regarding its reliability (%) and the project
- Add a way to process the image into text
- Refine image to text processing accuracy
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Train a model to extract core data (e.g. mean, standard deviation, etc.) from the problem -
Train a model to perform the hypothesis test -
Train a model to differentiate between z-tests and t-tests - Allow users to view a step-by-step process of the hypothesis test
- Allow users to copy the solution to the clipboard
- Allow users to save the solution to a file
- Allow users to share the solution with others
- Create a website for the project
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Connect the AI to the website -
Allow users to view more information about the AI regarding its reliability (%) and the project - Create a histogram of the website's daily/weekly/monthly usage and save it to a spreadsheet
- Pytesseract
- You will need to install:
pip install pytesseract
- Download Tesseract at UB Mannheim
- You will need to install:
- Word2Number
pip install word2number