test

client_lines2.py

@@ -31,7 +31,7 @@ def v2(x,y):
                      cam_DX=v(0.855/1944.,0.,0.), cam_DY=v(0.,0.,0.995/2592.), cam_resolution=v2(1944.,2592.),
                      laser_N=lN, laser_O=v(-0.37,0.,0.))
 
-for i in range(10000,10500,20):
+for i in range(12000,12500,20):
 
     start = timer()
     line = Line(path + str(i) + ".jpg", path + str(i+1) + ".jpg")

colors_hls_3d_line.py

@@ -11,7 +11,8 @@
 import matplotlib
 import pi2R.lines2d
 file_nr = 13090
-file_nr = 11050
+#file_nr = 11050
+file_nr = 12000
 
 path = './s4/'
 name1 = path + str(file_nr) + '.jpg'
@@ -25,10 +26,10 @@ def transform(disp_img, img1, img2, t=25):
     res = disp_img
     mask, (x,y) = pi2R.lines2d.transform(img1, img2, t)
 
-    res[mask] = [0.,0.,0.]
+#    res[mask] = [0.,0.,0.]
     color = [0,255,255]
     res[x,y] = color
-#    res[x+1,y] = color
+    res[x+1,y] = color
     res[x-1,y] = color
     res[x,y+1] = color
     res[x,y-1] = color

pi2R/lines.py

@@ -120,7 +120,7 @@ def get_points_2d_(self):
 #        if len(a) > 25000:
 #            print 'error rgb:', len(a)
 
-        if len(x) > 2*3500:
+        if len(x) > 3500:
             print 'error reduce:', len(x)
             return []
         return zip(y,x)

pi2R/lines2d.py

@@ -52,21 +52,24 @@ def transform(img1, img2, t=25):
     h2,l2,s2 = split(img2)
 
     y_data = l2-l1
-    y_data[y_data<0.02] = 0.02
+    dy = 0.03
+    y_data[y_data<dy] = dy
 
     kernel_size_x = 25
     kernel_size_y = 11
     kernel_x = np.ones((kernel_size_x), dtype=np.float32)*-1
-    kernel_x[kernel_size_x/4:kernel_size_x*3/4] = 1.
-    kernel = np.outer(signal.gaussian(kernel_size_y,7),kernel_x)
-    kernel/=kernel_size_y*kernel_size_x*2
-
+    kernel_x[kernel_size_x/4:(kernel_size_x*3)/4] = 1.
+    kernel = np.outer(signal.gaussian(kernel_size_y,7,),kernel_x)
+#    kernel/= kernel.sum()#kernel_size_y*kernel_size_x*2
+    kernel.astype(np.float32)
+#    a = kernel.sum()
     y_data = signal.fftconvolve(y_data, kernel, mode='same')
 
     ymax = y_data.max()
     print 'kernel sum:', kernel.sum(), 'ymax:', ymax
-    d = ymax/40
-    #d = 0
+    #d = ymax/10
+    print y_data
+    d = 0.5
     mask_not = y_data < d
     mask_not[:,0:20] = True
     mask_not[:,-20:] = True
@@ -75,6 +78,9 @@ def transform(img1, img2, t=25):
     y_data[mask_not] = d
     x,y = max_laser(y_data)
 
+#    y_data = (l2-l1)
+
+
     end = timer()
     print 'transform time:',end - start