multiprocessing

b18arundhati · May 12, 2017 · 8db34c0 · 8db34c0
1 parent 6b2eaeb
commit 8db34c0
Showing 1 changed file with 20 additions and 17 deletions.
diff --git a/fuzzy_c_spatial_spectral.py b/fuzzy_c_spatial_spectral.py
@@ -23,7 +23,7 @@
 neg_dist = 0
 cluster_number = 6
 cluster_color = {0:[255,255,0],1:[128,255,0],2:[0,128,255],3:[255,0,255],4:[255,0,0],5:[0,0,0]}
-image_path = "IMS1_HYSI_GEO_114_05FEB2009_S1_TOA_REFLECTANCE_07_SPBIN.tif"
+image_path = "test_new.jpeg"
 maxconn=8
 pool=threading.BoundedSemaphore(value=maxconn)
 dist_mat = []
@@ -37,18 +37,18 @@ def calculate_fuzzy_index(itertion_number,h,fxkyk):
 
 def get_data_from_image():
 	global image_path
-	# M = np.asarray(Image.open(image_path))
-	dataset = gdal.Open(image_path,gdal.GA_ReadOnly)
-	col = dataset.RasterXSize
-	row = dataset.RasterYSize
-	# print dataset.RasterCount
-	a = [[[]for y in xrange(col)] for z in xrange(row)]
-	for i in xrange(1,dataset.RasterCount + 1):
-		band = dataset.GetRasterBand(i).ReadAsArray()
-		for m in xrange(0,row):
-			for n in xrange(0,col):
-				a[m][n].append(band[m][n])
-	M = np.array(a,dtype='uint16')
+	M = np.asarray(Image.open(image_path))
+	# dataset = gdal.Open(image_path,gdal.GA_ReadOnly)
+	# col = dataset.RasterXSize
+	# row = dataset.RasterYSize
+	# # print dataset.RasterCount
+	# a = [[[]for y in xrange(col)] for z in xrange(row)]
+	# for i in xrange(1,dataset.RasterCount + 1):
+	# 	band = dataset.GetRasterBand(i).ReadAsArray()
+	# 	for m in xrange(0,row):
+	# 		for n in xrange(0,col):
+	# 			a[m][n].append(band[m][n])
+	# M = np.array(a,dtype='uint16')
 	image_name = image_path.split(".")[0]
 	f = open("data_"+str(image_name)+".pickle","wb")
 	# f = open("data_test.pickle","wb")
@@ -253,17 +253,20 @@ def get_cluster_ref(U,data,v,v_denom):
 	return v
 
 def calculate_distance(params):
-	global dist_mat
+	global cluster_number
+	# global dist_mat
 	# print dist_mat
 	n,m,U,itertion_number,data,cluster_centres = params[0],params[1],params[2],params[3],params[4],params[5]
 	# print n,m
-	cluster_number = len(cluster_centres)
+	# cluster_number = len(cluster_centres)
 	cluster_spatial_arr,alpha = spatial_dist_denom(n,m,U,itertion_number)
+	dist = [0 for i in xrange(0,cluster_number)]
 	for r in xrange(0,cluster_number):
-		dist = eu_distance(data[m][n],cluster_centres[r]) + spatial_distance(r,cluster_spatial_arr,alpha)
+		dist[r] = eu_distance(data[m][n],cluster_centres[r]) + spatial_distance(r,cluster_spatial_arr,alpha)
 		# if dist != dist_mat[m][n][r]:
 		# 	print 'yes',m,n,r
-		dist_mat[m][n][r] = dist
+		# dist_mat[m][n][r] = dist
+	return dist
 
 class GrabUrl(threading.Thread):
     def __init__(self, arg0):