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Commit d6a9aa10 authored by Angeline Aguinaldo's avatar Angeline Aguinaldo
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gmm with Replicates

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SRC/Python/.idea/workspace.xml
+ 23
− 35
View file @ d6a9aa10
...@@ -24,8 +24,8 @@ ...@@ -24,8 +24,8 @@
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...@@ -33,33 +33,21 @@ ...@@ -33,33 +33,21 @@
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...@@ -393,9 +381,9 @@ ...@@ -393,9 +381,9 @@
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...@@ -548,15 +536,23 @@ ...@@ -548,15 +536,23 @@
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...@@ -565,16 +561,8 @@ ...@@ -565,16 +561,8 @@
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......
SRC/Python/PIXEL_REPLICATION_LIB.py
+ 18
− 9
View file @ d6a9aa10
...@@ -40,7 +40,7 @@ def PixelReplicate(bwim): ...@@ -40,7 +40,7 @@ def PixelReplicate(bwim):
import cv2 import cv2
print("Computing Distance Transform...") print("Computing Distance Transform...")
bwd = cv2.distanceTransform(bwim, distanceType=cv2.DIST_L2, maskSize=cv2.DIST_MASK_5) bwd = cv2.distanceTransform(bwim, distanceType=cv2.DIST_L2, maskSize=cv2.DIST_MASK_PRECISE)
bwd = np.asmatrix(bwd, dtype=float) bwd = np.asmatrix(bwd, dtype=float)
roundBwd = np.round(bwd) roundBwd = np.round(bwd)
nPtsRep = np.sum(roundBwd, dtype=int) nPtsRep = np.sum(roundBwd, dtype=int)
...@@ -71,17 +71,26 @@ def PixelReplicate(bwim): ...@@ -71,17 +71,26 @@ def PixelReplicate(bwim):
def fitGMM(ptsRep, k): def fitGMM(ptsRep, k):
from sklearn.mixture import GMM from sklearn.mixture import GMM
import numpy as np
import cv2 import cv2
print("Fitting GMM...") print("Fitting GMM...")
gmm0 = cv2.ml.EM_create() gmm0 = cv2.ml.EM_create()
gmm0.setCovarianceMatrixType(2) gmm0.setCovarianceMatrixType(2)
gmm0.setClustersNumber(k) gmm0.setClustersNumber(k)
termCrit = (20, 400, 1e-4) termCrit = (20, 400, 1e-15)
gmm0.setTermCriteria(termCrit) gmm0.setTermCriteria(termCrit)
gmm0.trainEM(ptsRep) bestGMM = []
bestLL = float("-inf")
for i in np.arange(0, 10, 1):
print('Replicate: ', str(i+1))
newGMM = gmm0.trainEM(ptsRep)
LL = sum(newGMM[1])
if LL > bestLL:
bestGMM = gmm0
bestLL = LL
# gmm0 = GMM(n_components=k, covariance_type='full', n_iter=400, n_init=20, verbose=0, tol=1e-4, init_params='m') # gmm0 = GMM(n_components=k, covariance_type='full', n_iter=400, n_init=20, verbose=0, tol=1e-4, init_params='m')
# gmmfit = gmm0.fit(ptsRep) # gmmfit = gmm0.fit(ptsRep)
return gmm0 return bestGMM
def drawClusters(gmm0, bwim, ptsEdge): def drawClusters(gmm0, bwim, ptsEdge):
import numpy as np import numpy as np
...@@ -107,12 +116,12 @@ def drawClusters(gmm0, bwim, ptsEdge): ...@@ -107,12 +116,12 @@ def drawClusters(gmm0, bwim, ptsEdge):
plt.hold(True) plt.hold(True)
print("Plotting...") print("Plotting...")
colors = ['m', 'r', 'c', 'g', 'y', 'b'] colors = ['m', 'r', 'c', 'g', 'y', 'b']
for h in np.unique(clusters): for h in np.arange(0, np.max(clusters)+1, 1):
clustIdx = np.where(clusters == h) clustIdx = np.where(clusters == h)
bwLabel[np.array([pts[clustIdx, 0]]), np.array([pts[clustIdx, 1]])] = h + 1 bwLabel[np.array([pts[clustIdx[0], 0]]), np.array([pts[clustIdx[0], 1]])] = h + 1
plt.scatter(x=pts[clustIdx, 1], y=pts[clustIdx, 0], s=50, c=colors[h], lw=0) plt.scatter(x=pts[clustIdx[0], 1], y=pts[clustIdx[0], 0], s=40, c=colors[h], lw=0)
if ~all(ptsEdge == 0): if sum(ptsEdge) != 0:
plt.scatter(ptsEdge[0:, 1], ptsEdge[0:, 1], s=50, c='w', lw=0) plt.scatter(ptsEdge[0:, 1], ptsEdge[0:, 1], s=50, c='w', lw=0)
plt.axis('off') plt.axis('off')
......
SRC/Python/PixelRep_Demo.py
+ 3
− 3
View file @ d6a9aa10
...@@ -33,12 +33,12 @@ import GENERATE_ELLIPSE_LIB as GenEllipse ...@@ -33,12 +33,12 @@ import GENERATE_ELLIPSE_LIB as GenEllipse
# Generate random ellipse image # Generate random ellipse image
print("Generating Ellipse...") print("Generating Ellipse...")
K = 5 # number of ellipse to fit K = 4 # number of ellipse to fit
bwim, trueBounds = GenEllipse.GetRandomEllipseImage(K) # bwim, trueBounds = GenEllipse.GetRandomEllipseImage(K)
# # You may import an image for demo by uncommenting the following code: # # You may import an image for demo by uncommenting the following code:
import cv2 import cv2
im = cv2.imread('U:\Angeline\PixelRep\Ellipse.tif', cv2.CV_8UC1) im = cv2.imread('U:\Angeline\PixelRep\Ellipse_k4.tif', cv2.CV_8UC1)
# im = cv2.imread('INSERT FILENAME', cv2.CV_8UC1) # im = cv2.imread('INSERT FILENAME', cv2.CV_8UC1)
th, bwim = cv2.threshold(im, 0, 1, cv2.THRESH_BINARY) th, bwim = cv2.threshold(im, 0, 1, cv2.THRESH_BINARY)
trueBounds = [0, 0] trueBounds = [0, 0]
......
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