add preFilterCap param for bm tunning

capture_stereo_images.py

@@ -37,18 +37,35 @@ def capture_stereo_images(left_cam, right_cam, width, height, image_pair_num, ou
     cap_right.set(cv2.CAP_PROP_FRAME_HEIGHT, height)
 
     count = 0
+    flags = (cv2.CALIB_CB_FAST_CHECK)
+    criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001)
+    rows = 6
+    cols = 8
     while count < image_pair_num:
         ret1, img1 = cap_left.read()
         ret2, img2 = cap_right.read()
         # Wait until ret1 and ret2 are true since camera setup needs some time.
         if ret1 and ret2:
-            cv2.imshow("stereo cameras", np.hstack((img1, img2)))
-
-        if cv2.waitKey(1) & 0xFF == ord('q'):
-            break
+            img1_gray = cv2.cvtColor(img1, cv2.COLOR_BGR2GRAY)
+            img2_gray = cv2.cvtColor(img2, cv2.COLOR_BGR2GRAY)
+            found_left, corners_left = cv2.findChessboardCorners(img1_gray, (rows, cols), flags)
+            found_right, corners_right = cv2.findChessboardCorners(img2_gray, (rows, cols), flags)
+            if found_left and found_right:
+#                cv2.cornerSubPix(img1_gray, corners_left, (11, 11), (-1, -1), criteria)
+#                cv2.cornerSubPix(img2_gray, corners_right, (11, 11), (-1, -1), criteria)
+
+                img1_gray = cv2.cvtColor(img1_gray, cv2.COLOR_GRAY2BGR)
+                img2_gray = cv2.cvtColor(img2_gray, cv2.COLOR_GRAY2BGR)
+
+                cv2.drawChessboardCorners(img1_gray, (rows, cols), corners_left, found_left)
+                cv2.drawChessboardCorners(img2_gray, (rows, cols), corners_right, found_right)
 
+
+#            cv2.imshow("stereo cameras", np.hstack((img1, img2)))
+            cv2.imshow("stereo cameras", np.hstack((img1_gray, img2_gray)))
+
         # When space key is pressed, save the image of left and right respectively
-        if cv2.waitKey(1) & 0xFF == ord(' '):
+        if ret1 and ret2 and cv2.waitKey(1) & 0xFF == ord(' '):
             save_images(img1, img2, count)
             count = count + 1
 
@@ -73,11 +90,13 @@ def print_prompt(output_dir):
     print 'Images will be saved in %s' % output_dir
 
 if __name__ == "__main__":
-    output_dir = './images/'
+    output_dir = './images_320x240/'
     left_cam = 1
     right_cam = 2
-    width = 480
-    height = 320
+    width = 320
+    height = 240
+#     width = 800
+#     height = 600
     image_pair_num = 50
 
     print_prompt(output_dir)

depth_map.py

@@ -43,6 +43,7 @@ def __init__(self):
         self.disp12_max_diff = 1
         self.p1 = 8 * 3 * self.block_size**2
         self.p2 = 32 * 3 * self.block_size**2
+        self.prefilter_cap = 0
 
     def __str__(self):
         return '\n'.join('%s: %s' % item for item in vars(self).items())
@@ -51,7 +52,8 @@ def save(self, file_name):
         pickle.dump(self, open(file_name, "wb"))
         print ('blockmathcer result saved into %s' % file_name)
 
-bm = pickle.load(open('blockMatcher.pkl', 'rb'))
+#bm = pickle.load(open('blockMatcher.pkl', 'rb'))
+bm = BlockMatcher()
 
 stereo = cv2.StereoSGBM_create(minDisparity = bm.min_disparity,
                                numDisparities = bm.num_disparities,
@@ -61,7 +63,8 @@ def save(self, file_name):
                                speckleRange = bm.speckle_range,
                                disp12MaxDiff = bm.disp12_max_diff,
                                P1 = bm.p1,
-                               P2 = bm.p2
+                               P2 = bm.p2,
+                               preFilterCap = bm.prefilter_cap
                                )
 
 def on_min_disparity(position):
@@ -119,6 +122,11 @@ def on_speckle_range(position):
     stereo.setSpeckleRange(position)
     bm.speckle_range = position
 
+def on_prefilter_cap(position):
+    print ('on_prefilter_cap %s' % position)
+    stereo.setPreFilterCap(position)
+    bm.prefilter_cap = position
+
 # window_size = 3
 # min_disp = 16
 # num_disp = 112-min_disp
@@ -142,7 +150,7 @@ def on_speckle_range(position):
 cv2.createTrackbar("uniquenessRatio", "disparity", bm.uniqueness_ratio, 100, on_uniqueness_ratio)
 #cv2.createTrackbar("speckleWindowSize", "disparity", bm.speckle_window_size, 1000, on_speckle_window_size)
 #cv2.createTrackbar("speckleRange", "disparity", bm.speckle_range, 1000, on_speckle_range)
-
+cv2.createTrackbar("preFilterCap", "disparity", bm.prefilter_cap, 100, on_prefilter_cap)
 # while True:
 #     disparity = stereo.compute(imgL,imgR)
 #     # Normalize the image for representation

show_cams.py

@@ -3,10 +3,10 @@
 import cv2
 import numpy as np
 
-left_cam_id = 2
-right_cam_id = 1
-width = 680
-height = 480
+left_cam_id = 1
+right_cam_id = 2
+width = 480
+height = 320
 
 def show_camera(cam_id, width, height):
     """
@@ -57,5 +57,5 @@ def show_cameras(left, right, width, height):
     cv2.destroyAllWindows()
 
 if __name__ == "__main__":
-#    show_cameras(left_cam_id, right_cam_id, width, height)
-    show_camera(0, width, height)
+    show_cameras(left_cam_id, right_cam_id, width, height)
+#    show_camera(0, width, height)