Python代写代考

MyPanorama_student3 In [1]: import numpy as np import matplotlib import matplotlib.image as image import matplotlib.pyplot as plt from skimage.transform import AffineTransform, ProjectiveTransform, warp %matplotlib notebook # NOTE: all “magic” options for backend plotting are: inline, notebook, and “external” (default) # see http://ipython.readthedocs.io/en/stable/interactive/plotting.html for details LineBuilder class for entering correspoinding points in each image¶ Note: left mouse […]

MyMorphing_student3 In [2]: import numpy as np import matplotlib import matplotlib.image as image import matplotlib.pyplot as plt from skimage.transform import PiecewiseAffineTransform, warp, resize %matplotlib notebook # NOTE: all “magic” options for backend plotting are: inline, notebook, and “external” (default) # see http://ipython.readthedocs.io/en/stable/interactive/plotting.html for details LineBuilder class for entering correspoinding points in each image¶ Note: left mouse

In [1]: import numpy as np import matplotlib import matplotlib.image as image import matplotlib.pyplot as plt from skimage.transform import PiecewiseAffineTransform, warp, resize %matplotlib notebook # NOTE: all “magic” options for backend plotting are: inline, notebook, and “external” (default) # see http://ipython.readthedocs.io/en/stable/interactive/plotting.html for details LineBuilder class for entering correspoinding points in each image¶ Note: left mouse clicks

Example for using function load_data and printing dataset¶ In [335]: from hw3_utils import load_data #downsample the training and validation dataset if needed, ds_rate should be larger than 1. ds_rate=None datasets = load_data(ds_rate=ds_rate,theano_shared=False) train_set_x, train_set_y = datasets[0] valid_set_x, valid_set_y = datasets[1] test_set_x, test_set_y = datasets[2] print(‘Current training data size is %i’%train_set_x.shape[0]) print(‘Current validation data size is %i’%valid_set_x.shape[0])