Merge pull request #9 from mastys100/master

Python 3.x.x compatibility

Author: MicrocontrollersAndMore

DetectChars.py

@@ -1,4 +1,5 @@
 # DetectChars.py
+import os
 
 import cv2
 import numpy as np
@@ -49,15 +50,15 @@ def loadKNNDataAndTrainKNN():
     try:
         npaClassifications = np.loadtxt("classifications.txt", np.float32)                  # read in training classifications
     except:                                                                                 # if file could not be opened
-        print "error, unable to open classifications.txt, exiting program\n"                # show error message
+        print("error, unable to open classifications.txt, exiting program\n")  # show error message
         os.system("pause")
         return False                                                                        # and return False
     # end try
 
     try:
         npaFlattenedImages = np.loadtxt("flattened_images.txt", np.float32)                 # read in training images
     except:                                                                                 # if file could not be opened
-        print "error, unable to open flattened_images.txt, exiting program\n"               # show error message
+        print("error, unable to open flattened_images.txt, exiting program\n")  # show error message
         os.system("pause")
         return False                                                                        # and return False
     # end try
@@ -144,7 +145,8 @@ def detectCharsInPlates(listOfPossiblePlates):
         if (len(listOfListsOfMatchingCharsInPlate) == 0):			# if no groups of matching chars were found in the plate
 
             if Main.showSteps == True: # show steps ###############################################
-                print "chars found in plate number " + str(intPlateCounter) + " = (none), click on any image and press a key to continue . . ."
+                print("chars found in plate number " + str(
+                    intPlateCounter) + " = (none), click on any image and press a key to continue . . .")
                 intPlateCounter = intPlateCounter + 1
                 cv2.destroyWindow("8")
                 cv2.destroyWindow("9")
@@ -211,15 +213,16 @@ def detectCharsInPlates(listOfPossiblePlates):
         possiblePlate.strChars = recognizeCharsInPlate(possiblePlate.imgThresh, longestListOfMatchingCharsInPlate)
 
         if Main.showSteps == True: # show steps ###################################################
-            print "chars found in plate number " + str(intPlateCounter) + " = " + possiblePlate.strChars + ", click on any image and press a key to continue . . ."
+            print("chars found in plate number " + str(
+                intPlateCounter) + " = " + possiblePlate.strChars + ", click on any image and press a key to continue . . .")
             intPlateCounter = intPlateCounter + 1
             cv2.waitKey(0)
         # end if # show steps #####################################################################
 
     # end of big for loop that takes up most of the function
 
     if Main.showSteps == True:
-        print "\nchar detection complete, click on any image and press a key to continue . . .\n"
+        print("\nchar detection complete, click on any image and press a key to continue . . .\n")
         cv2.waitKey(0)
     # end if
 

DetectPlates.py

@@ -43,7 +43,8 @@ def detectPlatesInScene(imgOriginalScene):
     listOfPossibleCharsInScene = findPossibleCharsInScene(imgThreshScene)
 
     if Main.showSteps == True: # show steps #######################################################
-        print "step 2 - len(listOfPossibleCharsInScene) = " + str(len(listOfPossibleCharsInScene))         # 131 with MCLRNF1 image
+        print("step 2 - len(listOfPossibleCharsInScene) = " + str(
+            len(listOfPossibleCharsInScene)))  # 131 with MCLRNF1 image
 
         imgContours = np.zeros((height, width, 3), np.uint8)
 
@@ -62,7 +63,8 @@ def detectPlatesInScene(imgOriginalScene):
     listOfListsOfMatchingCharsInScene = DetectChars.findListOfListsOfMatchingChars(listOfPossibleCharsInScene)
 
     if Main.showSteps == True: # show steps #######################################################
-        print "step 3 - listOfListsOfMatchingCharsInScene.Count = " + str(len(listOfListsOfMatchingCharsInScene))    # 13 with MCLRNF1 image
+        print("step 3 - listOfListsOfMatchingCharsInScene.Count = " + str(
+            len(listOfListsOfMatchingCharsInScene)))  # 13 with MCLRNF1 image
 
         imgContours = np.zeros((height, width, 3), np.uint8)
 
@@ -91,10 +93,10 @@ def detectPlatesInScene(imgOriginalScene):
         # end if
     # end for
 
-    print "\n" + str(len(listOfPossiblePlates)) + " possible plates found"          # 13 with MCLRNF1 image
+    print("\n" + str(len(listOfPossiblePlates)) + " possible plates found")  # 13 with MCLRNF1 image
 
     if Main.showSteps == True: # show steps #######################################################
-        print "\n"
+        print("\n")
         cv2.imshow("4a", imgContours)
 
         for i in range(0, len(listOfPossiblePlates)):
@@ -107,13 +109,13 @@ def detectPlatesInScene(imgOriginalScene):
 
             cv2.imshow("4a", imgContours)
 
-            print "possible plate " + str(i) + ", click on any image and press a key to continue . . ."
+            print("possible plate " + str(i) + ", click on any image and press a key to continue . . .")
 
             cv2.imshow("4b", listOfPossiblePlates[i].imgPlate)
             cv2.waitKey(0)
         # end for
 
-        print "\nplate detection complete, click on any image and press a key to begin char recognition . . .\n"
+        print("\nplate detection complete, click on any image and press a key to begin char recognition . . .\n")
         cv2.waitKey(0)
     # end if # show steps #########################################################################
 
@@ -148,8 +150,8 @@ def findPossibleCharsInScene(imgThresh):
     # end for
 
     if Main.showSteps == True: # show steps #######################################################
-        print "\nstep 2 - len(contours) = " + str(len(contours))                       # 2362 with MCLRNF1 image
-        print "step 2 - intCountOfPossibleChars = " + str(intCountOfPossibleChars)       # 131 with MCLRNF1 image
+        print("\nstep 2 - len(contours) = " + str(len(contours)))  # 2362 with MCLRNF1 image
+        print("step 2 - intCountOfPossibleChars = " + str(intCountOfPossibleChars))  # 131 with MCLRNF1 image
         cv2.imshow("2a", imgContours)
     # end if # show steps #########################################################################
 

Main.py

@@ -23,14 +23,14 @@ def main():
     blnKNNTrainingSuccessful = DetectChars.loadKNNDataAndTrainKNN()         # attempt KNN training
 
     if blnKNNTrainingSuccessful == False:                               # if KNN training was not successful
-        print "\nerror: KNN traning was not successful\n"               # show error message
+        print("\nerror: KNN traning was not successful\n")  # show error message
         return                                                          # and exit program
     # end if
 
-    imgOriginalScene  = cv2.imread("1.png")               # open image
+    imgOriginalScene  = cv2.imread("LicPlateImages/1.png")               # open image
 
     if imgOriginalScene is None:                            # if image was not read successfully
-        print "\nerror: image not read from file \n\n"      # print error message to std out
+        print("\nerror: image not read from file \n\n")  # print error message to std out
         os.system("pause")                                  # pause so user can see error message
         return                                              # and exit program
     # end if
@@ -42,7 +42,7 @@ def main():
     cv2.imshow("imgOriginalScene", imgOriginalScene)            # show scene image
 
     if len(listOfPossiblePlates) == 0:                          # if no plates were found
-        print "\nno license plates were detected\n"             # inform user no plates were found
+        print("\nno license plates were detected\n")  # inform user no plates were found
     else:                                                       # else
                 # if we get in here list of possible plates has at leat one plate
 
@@ -56,14 +56,14 @@ def main():
         cv2.imshow("imgThresh", licPlate.imgThresh)
 
         if len(licPlate.strChars) == 0:                     # if no chars were found in the plate
-            print "\nno characters were detected\n\n"       # show message
+            print("\nno characters were detected\n\n")  # show message
             return                                          # and exit program
         # end if
 
         drawRedRectangleAroundPlate(imgOriginalScene, licPlate)             # draw red rectangle around plate
 
-        print "\nlicense plate read from image = " + licPlate.strChars + "\n"       # write license plate text to std out
-        print "----------------------------------------"
+        print("\nlicense plate read from image = " + licPlate.strChars + "\n")  # write license plate text to std out
+        print("----------------------------------------")
 
         writeLicensePlateCharsOnImage(imgOriginalScene, licPlate)           # write license plate text on the image