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Visual-Recognition-System

Lab1 for CS 188 UCLA

Developed a Python program using OpenCV, Numpy, and Scikit-learn libraries to build a set of visual recognition systems that can identify scenes in different images

  • Uses SIFT, SURF, or ORB descriptors to capture local information in a training image and then K-means or hierarchical agglomerative clustering to build a Bag of Words represent vocabulary
  • Uses K Nearest Neighbors or SVM Classifiers to identify the contents of an image
  • homework1.py will use the functions defined in utils.py to perform all combinations of the tests and save outputs to files.

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Lab1 for CS 188 UCLA

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