def elasticDistort(picture, sigma, alpha):
dx, dy = generateDisplacementFields(sigma, alpha)
distortion = np.zeros(Constants.pic_shape)
Visualizer.plotNumber('dx', dx)
Visualizer.plotNumber('dy', dy)
# For each pixel use the displacement field to grab new pixel values
# Hopefully it will be elastically distorted! :D
# Bilinear interpolation
for i in range(Constants.pic_height):
for j in range(Constants.pic_width):
x = i + dx[i, j]
y = j + dy[i, j]
# If the new location we're trying to grab is outside the picture
# boundaries, then leave the pixel value as zero
if x < 0 or x > (Constants.pic_width - 1):
continue
if y < 0 or y > (Constants.pic_height - 1):
continue
distortion[i, j] = bilinearInterpolation(picture, x, y)
return distortion
def main():
from Visualizer import Visualizer
#data = np.genfromtxt('Data/train.csv', delimiter=',') # Why does numpy break? Nobody knows...
print 'Reading data'
data = pd.read_csv('Data/train.csv')
print 'Reshaping data'
row = 0
label = data.iloc[row, 0]
picture = np.reshape(data.iloc[row, 1:], Constants.pic_shape)
print 'Plotting number'
Visualizer.plotNumber(str(label), picture)
print 'Transforming'
sigma = 4
alpha = 8
elasticDistort(picture, sigma, alpha)
return
# distortion = elasticDistort(picture, sigma, alpha)
print distortion
print 'Plotting zoom'
Visualizer.plotNumber(str(label), distortion)
