First version of GUI handwritten digits recognizer written in Python with Pygame, OpenCV and TensorFlow/Keras.
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Updated
Aug 27, 2022 - Python
First version of GUI handwritten digits recognizer written in Python with Pygame, OpenCV and TensorFlow/Keras.
A script that trains a model to recognize handwritten digits using the MNIST data set. Then it loads external files and uses the neural network to predict what digits they are.
This is a project in which I store all my attempts to create an application that can recognize effortlessly written in Bulgarian text and numbers.
A program for generating and analyzing four-digit combinations. Provides sequence counts and verification using itertools and collections libraries.
Teaching a neural network how to write letters and digits with reinforcement learning.
Predict with Caffe models and save the result in a suitable format
Trained deep neural networks to predict and classify input image (MNISTDD) datasets with python.
The Synthetic Digits dataset for domain adaptation (PyTorch).
This program will train several time an ai model in order to make it predict handwritten digits
Round a numeric value to the nearest number toward zero with N significant figures.
Optical Character Recognition for Numerical Digits
Brute force solver for digits, returns all possible combinations of numbers as well as the total number of combinations
Round a numeric value to the nearest number toward negative infinity with N significant figures.
This is a python program which uses deep learning and image processing to create virtual pen where the user can hover with the configured colour tip over the webcam to write digits. The deep learning model trained using mnist is used to recognize the digits. It uses keras for deep learning and opencv for image processing.
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