Update leap_listener.py

Author: gruossomonica

leap_listener.py

@@ -16,8 +16,6 @@ class LeapEventListener(Leap.Listener):
     Subclass of Leap.Listener implementing the callback functions for some interesting events
     '''
 
-    maps_initialized = False
-    
     def on_init(self, controller):
         maps_initialized = False
         print("Controller initialized")
@@ -48,91 +46,5 @@ def on_images(self, controller):
         images = controller.images
         left_image = images[0]
         right_image = images[1]
+        # you can correct the distortion here...
 
-        if left_image.is_valid and right_image.is_valid:
-            #print("left_image w - h: ", left_image.width, " - ", left_image.height) # 640 - 240
-            ## Display distorted raw images
-            # cv2.imshow('Left image', self.get_image_as_numpy_array(left_image))
-            # cv2.imshow('Right image', self.get_image_as_numpy_array(right_image))
-            
-            if not self.maps_initialized: # The following code doesn’t handle the cases where the distortion maps can change
-                print("Converting distortion maps...")
-                left_coordinates, left_coefficients = self.convert_distortion_maps(left_image)
-                right_coordinates, right_coefficients = self.convert_distortion_maps(right_image)
-                maps_initialized = True
-
-            print("Start computing undistorted images...")
-            undistorted_left = self.undistort(left_image, left_coordinates, left_coefficients, 400, 400)
-            undistorted_right = self.undistort(right_image, right_coordinates, right_coefficients, 400, 400)
-
-            # display images
-            cv2.imshow('Left Camera', undistorted_left)
-            cv2.imshow('Right Camera', undistorted_right)
-            
-            if cv2.waitKey(1) & 0xFF == ord('q'):
-                #closing all open windows  
-                cv2.destroyAllWindows()
-            
-    def get_image_as_numpy_array(self, image):
-        '''
-        Get the numpy array related to the leap motion infrared image data
-        It is useful to show the image (e.g., using the cv2.imshow method)
-        '''
-        image_buffer_ptr = image.data_pointer # pointer to the image data buffer to directly access the memory in the data buffer using ctypes or numpy
-        ctype_array_def = ctypes.c_ubyte * image.width * image.height
-
-        # as ctypes array
-        as_ctype_array = ctype_array_def.from_address(int(image_buffer_ptr))
-        # as numpy array
-        as_numpy_array = np.ctypeslib.as_array(as_ctype_array)
-        return as_numpy_array
-        
-    def convert_distortion_maps(self, image):
-        distortion_length = image.distortion_width * image.distortion_height
-        xmap = np.zeros(distortion_length//2, dtype=np.float32)
-        ymap = np.zeros(distortion_length//2, dtype=np.float32)
-
-        for i in range(0, distortion_length, 2):
-            xmap[distortion_length//2 - i//2 - 1] = image.distortion[i] * image.width
-            ymap[distortion_length//2 - i//2 - 1] = image.distortion[i + 1] * image.height
-
-        xmap = np.reshape(xmap, (image.distortion_height, image.distortion_width//2))
-        ymap = np.reshape(ymap, (image.distortion_height, image.distortion_width//2))
-
-        #resize the distortion map to equal desired destination image size
-        resized_xmap = cv2.resize(xmap,
-                                  (image.width, image.height),
-                                  0, 0,
-                                  cv2.INTER_LINEAR)
-        resized_ymap = cv2.resize(ymap,
-                                  (image.width, image.height),
-                                  0, 0,
-                                  cv2.INTER_LINEAR)
-
-        #Use faster fixed point maps
-        coordinate_map, interpolation_coefficients = cv2.convertMaps(resized_xmap,
-                                                                     resized_ymap,
-                                                                     cv2.CV_32FC1,
-                                                                     nninterpolation = False)
-
-        return coordinate_map, interpolation_coefficients
-        
-    def undistort(self, image, coordinate_map, coefficient_map, width, height):
-        destination = np.empty((width, height), dtype = np.ubyte)
-
-        #wrap image data in numpy array
-        as_numpy_array = self.get_image_as_numpy_array(image)
-        img = np.reshape(as_numpy_array, (image.height, image.width))
-
-        #remap image to destination
-        destination = cv2.remap(img,
-                                coordinate_map,
-                                coefficient_map,
-                                interpolation = cv2.INTER_LINEAR)
-
-        #resize output to desired destination size
-        destination = cv2.resize(destination,
-                                 (width, height),
-                                 0, 0,
-                                 cv2.INTER_LINEAR)
-        return destination