A small computer vision project in the making. The goal is to create a simple website that implements CNN Keras model to recognize handwritten characters (letters and digits) from an input file (a photo, image, or a scanned file). Beside CNN Keras, we are also using CRAFT (Character-Region Awareness For Text detection) in Pytorch. The point is to run our model on seperate character.

• We used the popular MNIST dataset with over 60k images of handwritten digits to practice using CNN in Keras.
• Developed a more complexed CNN model on EMNIST (Extended-MNIST) dataset that returns 91.30% accuracy for EMNIST Bymerge and 88.20% for EMNIST Byclass.
• Current models are performing low accuracy on non-EMNIST testing dataset.
• Using CRAFT to extract character images from IAM dataset as a data augmentation method.
• Training a new model on the new dataset.
• Implementing prebuilt tools to detect lines in texts.
• Implementing prebuilt tools to convert italic texts to straight texts.

• Minh Quan Huynh: https://github.com/hmq1812
• Duc Minh Hoang: https://github.com/minhduchoang301/OCR-community-website

Please click on the folders to see new updates. The project is still in the process.