fixed minor bug and added more informative displays

find_pupil.py

@@ -83,7 +83,12 @@ def pupil_contour(img, threshold, debug=1):
     #for this image
     #print(threshold)
     contours, _ = cv2.findContours(thresh_img, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
-    best_contour = np.empty(contours[1].shape) #Empty Contour
+
+
+    if len(contours) == 1 :
+        best_contour = np.empty(contours[0].shape) #Empty Contour
+    else:
+        best_contour = np.empty(contours[1].shape) #Empty Contour
     for contour in contours:
         area = cv2.contourArea(contour)
         if PUPIL_MAX > area > PUPIL_MIN:
@@ -108,7 +113,10 @@ def pupil_contour(img, threshold, debug=1):
 
     # pylint: disable=R1715
     if contour_candidates == []: #if nothing found
-        return np.empty(contours[1].shape)
+        if len(contours) > 1:
+            return np.empty(contours[1].shape)
+        else:
+            return np.empty(contours[0].shape)
     else:
         #get best candidate (top circularity for now)
         sorted_contour_candidates = sorted(contour_candidates, \

graph_variance.py

@@ -14,7 +14,6 @@
 import matplotlib.pyplot as plt
 from find_pupil import pupillometry
 import numpy
-import pandas as pd
 #text
 FONT = cv2.FONT_HERSHEY_SIMPLEX
 SMI_DIM = (720, 480) # Dimension from SMI System
@@ -83,6 +82,16 @@ def display_main(frame, cap):
     cv2.imshow('Frame', resized_frame)
     #cv2.waitKey(0)
 
+def display_left(left):
+    """ Display the Left Eye"""
+    resized_left = resize_with_aspect_ratio(left, width=640) #Resize by\
+    # pylint: disable=C0103
+    L_STRING = "Left"
+    cv2.putText(resized_left, L_STRING, (0, 20), FONT, 0.8, (0, 255, 0), 2, cv2.LINE_AA)
+    cv2.imshow('Left Eye', resized_left)
+    #cv2.waitKey(0)
+    # resized_frame = ResizeWithAspectRatio(frame, height = 480)
+
 def best_fit(rads, radius):
     fitted = numpy.polyfit(rads, radius, 7)
     #print('best fit: ', fitted)
@@ -146,9 +155,11 @@ def main(frame=-1, filename=DEFAULT_FILE_NAME):
                     cv2.imwrite("frame.bmp", frame)
 
 
-            _, rads, radius = pupillometry(frame, debug)
+            image_edit, rads, radius = pupillometry(frame, debug)
 
             display_main(frame, cap)
+            display_left(image_edit)
+
             try:
                 best_fit(rads, radius)
             except numpy.linalg.LinAlgError as er:

outputcsv.csv

@@ -0,0 +1 @@
+timestamp (ms),data (radius,radians)