single object detection

git-svn-id: http://newslabx.csie.ntu.edu.tw/svn/Ginger@38 5747cdd2-2146-426f-b2b0-0570f90b98ed

trunk/code/detect_object.py

@@ -0,0 +1,73 @@
+import readGridEyeData
+
+import sys
+import numpy as np
+import cv2
+
+SIZE = 8
+visible_size = 128
+distanceBetweenSensors_w = 2.6 #cm
+distanceBetweenSensors_h = 2.6 #cm
+distance2Object = 60.0 #cm
+OFFSET = ((0, 0), ())
+
+TEMP_SCALE = 20
+RED = (0, 0, 255)
+GREEN = (0, 255, 0)
+BLUE = (255, 0, 0)
+
+background = readGridEyeData.GridEyeData(sys.argv[1])
+
+background_frames = [np.zeros((SIZE,SIZE)), np.zeros((SIZE,SIZE)),
+                     np.zeros((SIZE,SIZE)), np.zeros((SIZE,SIZE))]
+cnt = 1
+Horizon_array = np.array([[x for x in range(8)] for _ in range(8)])
+Vertical_array = np.array([[x for _ in range(8)] for x in range(8)])
+
+# Gets background of each pixel.
+while background.readFrame():
+  frames = background.frames
+  for i in range(4):
+    background_frames[i] += np.array(frames[i].data)
+  cnt += 1
+  
+for i in range(4):
+  background_frames[i]/=cnt
+
+# Reads data from object frames.
+objects = readGridEyeData.GridEyeData(sys.argv[2])
+
+while objects.readFrame():
+  frames = objects.frames
+  imgs = []
+  heat_points = []
+
+  # Subtracts background and scale the value.
+  for i in range(4):
+    frame = np.array(frames[i].data) - background_frames[i]
+    frame[frame < 0] = 0.0
+    frame *= TEMP_SCALE
+    frame[frame > 255] = 255
+    imgs.append(frame.astype(np.uint8))
+    x = int(sum(sum(frame * Horizon_array)) / sum(sum(frame)) / (SIZE - 1) *
+        (visible_size - 1))
+    y = int(sum(sum(frame * Vertical_array)) / sum(sum(frame)) / (SIZE - 1) *
+        (visible_size - 1))
+    heat_points.append((x,y))
+    print (x, y)
+  all_img = np.concatenate((np.concatenate((imgs[0], imgs[1]), axis = 1),
+                            np.concatenate((imgs[2], imgs[3]), axis = 1)),
+                           axis = 0)
+  all_img = cv2.cvtColor(all_img, cv2.COLOR_GRAY2RGB)
+  all_img = cv2.resize(all_img, (visible_size*2, visible_size*2),
+      interpolation = cv2.INTER_NEAREST)
+  cv2.circle(all_img, heat_points[0], 5, RED, -1)
+  cv2.circle(all_img, (heat_points[1][0]+visible_size, heat_points[1][1]), 5, RED, -1)
+  
+  cv2.imshow('sample', all_img)
+
+
+  while cv2.getWindowProperty('sample', 0) >= 0:
+    key = cv2.waitKey(50)
+    if key >= 0:
+      break

trunk/code/readGridEyeData.py

@@ -23,6 +23,7 @@ if __name__ == '__main__':
     import cv2
     import numpy as np
     import sys
+    from functools import reduce
     def exponential(img, value):
         tmp = cv2.pow(img.astype(np.double), value)*(255.0/(255.0**value))
         return tmp.astype(np.uint8)
@@ -38,6 +39,9 @@ if __name__ == '__main__':
     MIN_EXIST_TIME = 0.1
     cnt = 0
     avers = []
+
+    raw_aver = np.array([0]*64*4, np.float64)
+    raw_aver2 = np.array([0]*64*4, np.float64)
     
     fourcc = cv2.VideoWriter_fourcc(*'XVID')
     videoWriter = cv2.VideoWriter('output.avi', fourcc, 10.0, (SIZE*2,SIZE*4))
@@ -53,19 +57,32 @@ if __name__ == '__main__':
     innerStartTime = 0
     path = []
     speed = 0
+    avers.append(np.zeros((SIZE,SIZE), np.uint16))
+    avers.append(np.zeros((SIZE,SIZE), np.uint16))
+    avers.append(np.zeros((SIZE,SIZE), np.uint16))
+    avers.append(np.zeros((SIZE,SIZE), np.uint16))
     while gridEye.readFrame():
         frames = gridEye.frames
         imgs = []
+        raw = []
         for frame in frames:
             img = (np.array(frame.data)-15)*10
             img = cv2.resize(img.astype(np.uint8), (SIZE,SIZE), interpolation = cv2.INTER_LINEAR) # INTER_LINEAR, INTER_CUBIC
             imgs.append(img)
-            avers.append(np.zeros((SIZE,SIZE), np.uint16))
+            raw += reduce(lambda x,y: x+y, frame.data)
+        raw_aver += np.array(raw)
+        raw_aver2 += np.array(raw)**2
         if cnt < AVERAGE_FRAME:
             cnt += 1
             for i in range(len(imgs)):
                 avers[i] += imgs[i]
             if cnt == AVERAGE_FRAME:
+                b = (raw_aver/AVERAGE_FRAME)**2
+                a = raw_aver2/AVERAGE_FRAME
+                print ('aver', raw_aver/AVERAGE_FRAME)
+                print ((a-b)**0.5)
+                print (sum((a-b)**0.5)/64/4)
+                exit()
                 for i in range(len(avers)):
                     avers[i] = avers[i]/AVERAGE_FRAME
                     avers[i] = avers[i].astype(np.uint8)
@@ -227,4 +244,4 @@ if __name__ == '__main__':
             break
             
     videoWriter.release()
-    cv2.destroyAllWindows()
+    cv2.destroyAllWindows()