PC updates

errordatacollection.py

@@ -99,7 +99,7 @@ Rigid_body = [[0.9998443871765447, 0.016930978475685435, 0.004954129531717574, 0
             [-0.0019197896155425946, -0.1747337675862396, 0.9846138455622852, -0.017384735431967623],
             [0., 0., 0., 1.]]
 
-num_apriltags = 12
+num_apriltags = 11
 # screen1_ids = [32, 31, 3, 5, 10, 7]
 # screen2_ids = [33, 30, 17, 6]
 # screen3_ids = [9, 2]
@@ -183,8 +183,8 @@ start = time.time()
 
 num_blinks = 0
 
-while True:   
-    
+while True:
+
     ret, frame = cap.read()
 
     bg_copy = background.copy()
@@ -205,7 +205,7 @@ while True:
         continue
     pd_left = data['left_eye']['pd']['pd']
     pd_right = data['right_eye']['pd']['pd']
-    print(pd_left, pd_right)
+    # print(pd_left, pd_right)
     if len(gaze3) < 4:
         gaze3.append(1)
     gaze3 = np.array(gaze3)
@@ -238,9 +238,11 @@ while True:
                     if H2 is not None:
                         gaze_mapped_s2 = np.dot(H2, gaze_mapped)
                         gaze_mapped_s2 = gaze_mapped_s2/gaze_mapped_s2[2]
-                        cv2.circle(s2_copy, (int(gaze_mapped_s2[0]), int(gaze_mapped_s2[1])), 2, (0,0,255), 40)
-                        vec = (gaze_mapped_s2[:2] - err_center)
-                        err.append(vec)                        
+                        cv2.circle(s2_copy, (int(gaze_mapped_s2[0]), int(gaze_mapped_s2[1])), 2, (255,0,0), 20)
+                        err_center = get_closest(gaze_mapped_s2, err_centers)
+                        if err_center is not None:
+                            vec = (gaze_mapped_s2[:2])# - err_center)
+                            err.append(vec)                        
 
                 # elif gaze_mapped_back[0] > s3_min and gaze_mapped_back[0] < s3_max and gaze_mapped_back[1] > 240:
                 #     H3 = get_hom(result, fix_s3)
@@ -253,31 +255,27 @@ while True:
             cv2.imshow('mapped gaze', bg_copy)
             # cv2.imshow("screen1", s1_copy)
             cv2.imshow("screen2", s2_copy)
-            # cv2.imshow("screen3", s3_copy)
-            elapsed = time.time() - start
-            # total_elapsed += elapsed
-            if cv2.waitKey(20) & 0xFF == ord('q'):
+            if cv2.waitKey(10) & 0xFF == ord('q'):
                 break
+            # cv2.imshow("screen3", s3_copy)
+    # elapsed = time.time() - start
+    # if elapsed > 20:
+    #     print("Done")
+    #     break
 
-            # if elapsed > 20:
-            #     print("Done")
-            #     break
-    elif pd_left == -1 or pd_right == -1:
-        num_blinks += 1
-
-dir_name = "error_data/Screen1/multiple/gazedata"
+dir_name = "error_data/Screen2_laptop/multiple/gazedata"
 
 if not os.path.exists(dir_name):
     os.makedirs(dir_name)
 
-np.save(dir_name + "/data1", err)
+np.save(dir_name + "/gaze_data", err)
 # np.save(dir_name + "/direct_gaze_1", err)
 # np.save(dir_name + "/looking_left_corner_1", err)
 # np.save(dir_name + "/looking_right_corner_1", err)
 # np.save(dir_name + "/moving_head_1", err)
-print()
-print("number of blinks", num_blinks)
-print()
+# print()
+# # print("number of blinks", num_blinks)
+# print()
 tobiiglasses.stop_streaming()
 cap.release()
 cv2.destroyAllWindows()

plotting_error.py

@@ -2,9 +2,6 @@ import numpy as np
 import matplotlib.pyplot as plt
 
 
-
-
-
 def avg(data, i, j, n):
     # print(data)
     
@@ -16,7 +13,7 @@ def remove_outliers(data):
     length = data.shape[0]
     ret_data = [[],[]]
     average_over = 2
-    threshold = 3
+    threshold = 5
     for i in range(length - average_over):
         for j in range(2):
             if i in range(average_over):
@@ -28,11 +25,11 @@ def remove_outliers(data):
     return ret_data
 
 
-data = np.load("error_data/Screen1/multiple/allpos/direct_gaze_1.npy")
+data = np.load("error_data/Screen2_laptop/multiple/gazedata/data1.npy")
 
 data = remove_outliers(data)
 
-max_length = 900
+max_length = min(1100, len(data[0]), len(data[1]))
 
 x_time = np.zeros((max_length,))
 y_time = np.zeros((max_length,))
@@ -55,6 +52,8 @@ plt.plot(x_time, x_data)
 plt.plot(x_time, [x_mean] * max_length, linewidth=3, color='black')
 plt.title("Error in mapping x coordinate")
 plt.ylabel("Error in gaze x coordinate (percentage)")
+# plt.title("Mapped x coordinate")
+# plt.ylabel("Mapped x coordinate (pixels)")
 plt.xlabel("Time (s)")
 
 plt.figure(1)
@@ -62,6 +61,8 @@ plt.plot(y_time, y_data)
 plt.plot(y_time, [y_mean] * max_length, linewidth=3, color='black')
 plt.title("Error in mapping y coordinate")
 plt.ylabel("Error in gaze y coordinate (percentage)")
+# plt.title("Mapped y coordinate")
+# plt.ylabel("Mapped y coordinate (pixels)")
 plt.xlabel("Time (s)")