import numpy as np
from SparseEdges import SparseEdges
mp = SparseEdges('https://raw.githubusercontent.com/bicv/SparseEdges/master/default_param.py')
mp.N = 128
image = mp.imread('https://raw.githubusercontent.com/bicv/SLIP/master/database/serre07_targets/B_N107001.jpg')
mp.pe.figsize_edges = 9
image = mp.normalize(image, center=True)
#! trying now using no whitening of the image
mp.pe.do_whitening = False
import os
matname = os.path.join(mp.pe.matpath, 'experiment_test_nowhitening.npy')
matname_RMSE = os.path.join(mp.pe.matpath, 'experiment_test_nowhitening_RMSE.npy')
try:
edges = np.load(matname)
except:
edges, C_res = mp.run_mp(image, verbose=True)
np.save(matname, edges)
fig, a = mp.show_edges(edges, image=image, mask=True)
import numpy as np
from SparseEdges import SparseEdges
mp = SparseEdges('https://raw.githubusercontent.com/bicv/SparseEdges/master/default_param.py')
mp.N = 128 # number of edges
mp.pe.figsize_edges = 9
#! defining a reference test image (see test_Image)
image = np.zeros((mp.pe.N_X, mp.pe.N_Y))
image[mp.pe.N_X/2:mp.pe.N_X/2+mp.pe.N_X/4, mp.pe.N_X/2:mp.pe.N_X/2+mp.pe.N_X/4] = 1
image[mp.pe.N_X/2:mp.pe.N_X/2+mp.pe.N_X/4, mp.pe.N_X/4:mp.pe.N_X/2] = -1
import os
matname = os.path.join(mp.pe.matpath, 'experiment_test_MP.npy')
try:
edges = np.load(matname)
except:
edges, C_res = mp.run_mp(image, verbose=False)
np.save(matname, edges)
fig, a = mp.show_edges(edges, image=mp.whitening(image))
