In this project, you'll write software that stitches multiple images of a scene together into a panorama automatically. A panorama is a composite image that has a wider field of view than a single image, and can combine images taken at different times for interesting effects.
Your image stitcher will, at a minimum, do the following:
I hereby claim:
To claim this, I am signing this object:
| """ | |
| Some python code for | |
| Markov Chain Monte Carlo and Gibs sampling | |
| by Bruce Walsh | |
| """ | |
| import numpy as np | |
| import numpy.linalg as npla |
| require 'torch' | |
| require 'nn' | |
| require 'optim' | |
| trainset = torch.load("mnist.t7/train_32x32.t7", "ascii") | |
| trainset.data = trainset.data:resize(60000, 32*32) | |
| trainset.data = trainset.data:double() | |
| test = torch.load("mnist.t7/test_32x32.t7", "ascii") | |
| test.data = test.data:resize(10000, 32*32) |
| #!/usr/bin/env python | |
| import numpy | |
| import sys | |
| import timeit | |
| try: | |
| import numpy.core._dotblas | |
| print 'FAST BLAS' | |
| except ImportError: | |
| print 'slow blas' |
| #! /usr/bin/env python | |
| import numpy | |
| import time | |
| import scipy.linalg as linalg | |
| try: | |
| import numpy.core._dotblas | |
| print 'Using ATLAS:' | |
| except ImportError: | |
| print 'No ATLAS:' |
| #!/usr/bin/env python | |
| """ | |
| __author__: Martin Felder | |
| Demo for sequential bayesin learning | |
| for linear regression models. See | |
| Chapter 3.3 of 'Pattern recognition | |
| and machine learning' by Chris Bishop, 2001 | |
| """ | |
| import sys | |
| import scipy as sp | |
| from scipy.special import gamma | |
| import pylab | |
| a = float(sys.argv[1]) | |
| b = float(sys.argv[2]) | |
