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cs230

Alphanumeric-Augmented-CNN contains a model for recognizing rotated handwritten alphanumeric characters.

Background-Scripts contains scripts used to generate background images for standardized objects.

Darkflow-Geometric contains instructions for using the Darkflow YOLOv2 model on the dataset that can be generated with scripts inside.

Darkflow-Human contains instructions for using the Darkflow YOLOv2 model on human detection and scripts for annotating data.

EMNIST-Siamese-Model contains a model of a Siamese Convolutional Neural Network designed as a backup to the vanilla CNN to generate encodings for different character classes.

Segmentation contains a k-means clustering implementation for segmenting shape and character from an inputted image, as well as determining color of the object.

SURF contains a preliminary SURF approach for localizing standardized objects.

Simple-NNs-and-older-versions are the models we tried before arriving at the ones above.

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Stanford CS230 Deep Learning Project

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  • Python 96.0%
  • Java 4.0%