Trying to identify the bird species is a challenging task and often leads to ambiguous labels. Many times professional bird watchers fail to recognize the species of a bird from the image provided. Though many bird species are having the same basic set of parts like a beak, legs, feathers, etc, they can vary much in shape and appearance. The identification of birds species is a challenging task for both humans and computers. Factors like lighting, background or variation in positions (like swimming bird, flying bird) make a larger difference in recognizing the bird species for computers.
So in this python project, we are going to apply the power of machine learning with Python to identify the bird species from images.
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The main idea of the project is to give bird images as input and print the name of it as output.
Algorithms used in the project:
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Caltech-UCSD Birds-200-2011 (CUB-200-2011):
It contains 200 categories and 11788 images of birds.
To complete the project do the following steps:
After training and testing the algorithm on the complete dataset we are able to identify the bird species with a testing accuracy of 51.6%.
Software requirements: Pycharm and Python3.
Programming Languages: Python, Scikit Learn library.
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