Fast Fourier Transform (FFT) in Python

Fast Fourier Transform (FFT) is Discrete Fourier Transform (DFT) algorithm. To perform FFT in Python you need to install several packages/modules/libraries. You can skip this portion if you already have it available. I am a windows user so I will show how to setup your machine for windows environment. This is an effort to provide the easiest and extensive tutorial for image processing beginners in python.

Things you need to download and install are as follows:

1. Install Python 2.7.10 (as for Python 3.4 you will face challenges for other packages) from https://www.python.org/downloads/

2. Install SciPy 0.16.0 superpack for Python 2.7 from http://sourceforge.net/projects/scipy/files/scipy/0.16.0/

3. Install NumPy 1.9.2 superpack for Python 2.7 from http://sourceforge.net/projects/numpy/files/NumPy/1.9.2/

4. Install Six 1.9.0 from https://pypi.python.org/pypi/six

5. Install Matplotlib 1.4.3 for Python 2.7 from http://sourceforge.net/projects/matplotlib/files/matplotlib/matplotlib-1.4.3/windows/

6. Install Dateutil 2.4.2 from https://pypi.python.org/pypi/python-dateutil [Install Six (see step-4) before installing Dateutil]

7. Install PIL 1.1.7 for Python 2.7 from http://www.pythonware.com/products/pil/

8. Install PyParsing 2.0.3 for Python 2.7 from http://sourceforge.net/projects/pyparsing/files/pyparsing/pyparsing-2.0.3/

9. Install OpenCV (Open Source Computer Vision) 3.0.0 from http://sourceforge.net/projects/opencvlibrary/files/opencv-win/3.0.0/

Ploting sinusoidal waves in Python

Aim: Plot sine wave with 5 cycles.

Code:

import numpy as np
import matplotlib.pyplot as plt

t = np.linspace(0, 10*np.pi, 1024, endpoint=True)
s = np.sin(t)
plt.plot(t,s)
plt.show()

Output:

NVIDIA Deep Learning Webinar

DEEP LEARNING LAB SERIES SCHEDULE:

[Click the respective link to open the folder]

• 7/22 Class #1 - Introduction to Deep Learning

• 7/29 Office Hours for Class #1

• 8/5 Class #2 - Getting Started with DIGITS interactive training system for image classification

• 8/12 Office Hours for Class #2

• 8/19 Class #3 - Getting Started with the Caffe Framework

• 8/26 Office Hours for Class #3

• 9/2 Class #4 - Getting Started with the Theano Framework

• 9/9 Office Hours for Class #4

• 9/16 Class #5 - Getting Started with the Torch Framework

• 9/23 Office Hours for Class #5

It is an introductory course (free online webinar) on Deep learning which is a part of Machine learning which is a part of Artificial intelligence. More information available at developer.nvidia.com/deep-learning-courses

Useful links:

• Caffe: http://caffe.berkeleyvision.org/
• Theano: http://deeplearning.net/software/theano/
• Torch: http://torch.ch/
• DIGITS: https://developer.nvidia.com/digits
• cuDNN: https://developer.nvidia.com/cudnn

Top 7 Full HD Octacore Android Smartphones Under 25000 Rupees

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Top 19 Octacore Android Smartphones Under 10000 Rupees

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