redis-python pseudoimss-python image pipelines achieved

python/ctypes_test.py → python/pseudo_imss.py

-import ctypes
-from ctypes import *
-import pathlib
-import skimage
-import pickle
-import numpy as np
 import os
-from skimage import io, filters
-from io import StringIO
+import ctypes, pathlib
+import skimage, pickle
+import numpy as np
+import time
+
+from io            import StringIO
+from ctypes        import *
+from skimage       import io, filters
 from skimage.color import rgb2gray, rgba2rgb
 
 ##############################################
@@ -17,20 +17,18 @@ libname = header_dir / "liblittle_lib.so"
 c_lib   = ctypes.CDLL(libname)
 
 ##############################################
-############### STORE AN IMAGE ###############
+################ STORE IMAGE #################
+
+t_init = time.clock()
 
 #Retrieve the concerning image.
-#image_file    = open('./clouds.jpg', 'rb')
-#image_buffer  = image_file.read()
-#buffer_length = len(image_buffer)
-#Load directory.
 filename = os.path.join('.', 'clouds.jpg')
-#Read the image.
-clouds = io.imread(filename)
-
-clouds = pickle.dumps(clouds)
-print(type(clouds))
-
+clouds   = io.imread(filename)
+t0 = time.clock()
+clouds   = pickle.dumps(clouds)
+t1 = time.clock() - t0
+print(t1)
+#Size of the concerning image.
 clouds_len = len(clouds)
 #Specify return parameters.
 c_lib.set_data.restype = ctypes.c_int32
@@ -51,13 +49,19 @@ answer = c_lib.get_data(return_buffer)
 ##############################################
 ############## TRANSFORM IMAGE ###############
 
-clouds_from_c = pickle.loads(return_buffer)
 #Read the image.
-#clouds = io.imread(qwertyu)
+t0 = time.clock()
+clouds_from_c = pickle.loads(return_buffer)
+t1 = time.clock() - t0
+print(t1)
 #Turn it to grayscale.
 clouds_from_c = rgb2gray(clouds_from_c)
-#Apply a simple threshold.
+#Determine a simple threshold.
 threshold = filters.threshold_otsu(clouds_from_c)
+#Apply the former.
 image_thesholded = clouds_from_c > threshold
 #Save the files.
 io.imsave("clouds_test.png", image_thesholded)
+
+t_end = time.clock() - t_init
+print(t_end)

python/redis_cli.py

 import os
 import pickle
 import skimage
+import time
 import numpy as np
 from skimage import io, filters
 from skimage.color import rgb2gray
@@ -26,6 +27,8 @@ rc = RedisCluster(startup_nodes = startup_nodes, decode_responses = False)
 ###################################### READ AN IMAGE ######################################
 ###########################################################################################
 
+t_init = time.clock()
+
 #Load directory.
 filename = os.path.join('.', 'clouds.jpg')
 #Read the image.
@@ -41,3 +44,6 @@ threshold = filters.threshold_otsu(clouds_from_redis)
 image_thesholded = clouds_from_redis > threshold
 #Save the files.
 io.imsave("clouds_test.png", image_thesholded)
+
+t_end = time.clock() - t_init
+print(t_end)