script/imgproc/CoverDetection2.py

@@ -7,13 +7,12 @@ FRAMES_INTEGRATION = 3
 STEP_SIZE = 2
 POSITION_NAMES = [ 'A','B','C','D', 'E', 'F']
 POSITION_ANGLES = [330, 30, 90, 150, 210, 270]
-POSITION_TOLERANCE = 10
+POSITION_TOLERANCE = 3
 MINIMUM_CONFIDENCE = 10
 DEBUG = True
 PLOT = True
 REFERENCE_IMG = "ref2"
 
-
 #Load reference image
 ref = load_image(str("{images}/cover/" + REFERENCE_IMG + ".png") , title="Line")
 
@@ -31,6 +30,7 @@ ip = sub_image(ip, cx-ref.width/2, cy-ref.height/2, ref.width, ref.height)
 #Show ROI of pre-processed image 
 image_panel = show_panel(ip.bufferedImage)
 
+
 #Calculate correlation between image and reference, rotating the reference from 0 to 360
 import ch.psi.pshell.imaging.Utils.integrateVertically as integrateVertically
 ydata = []
@@ -39,12 +39,12 @@ for i in xdata:
     r = ref.duplicate()
     r.getProcessor().setBackgroundValue(0.0)
     r.getProcessor().rotate(float(i))
-    op = op_fft(ip, r, "correlate") 
+    op = op_fft(r, ip, "correlate") 
     bi = op.getBufferedImage()
     p = integrateVertically(bi)
     ydata.append(sum(p))
     #image_panel = show_panel(op.bufferedImage)
-    #time.sleep(0.001)
+    #time.sleep(1.0)
 
 
 #Calculate angle of the highest correlation, and confidence level
@@ -72,7 +72,7 @@ if DEBUG:
     print "Peak values:  " + str(peaks_y)
     print "Angle:  " , angle
     print "Position:  " , position
-    print "Confifdence:  " , confidence
+    print "Confidence:  " , confidence
 
 #Set return value
 set_return  ([position, angle, confidence])

script/imgproc/LedDetectionProc.py

@@ -51,10 +51,10 @@ set_led_state(False)
 
 op_image(image, background, "subtract", float_result=True, in_place=True)
 
-if RENDERER is None:
+if RENDERER is not None:
+    RENDERER.setImage(None, image.getBufferedImage(), None)    
+else:    
     RENDERER = show_panel(image.getBufferedImage())
-else:
-    RENDERER.setImage(None, image.getBufferedImage(), None)
 RENDERER.clearOverlays()
 
 invert(image)
@@ -73,15 +73,14 @@ for row in range (r.counter):
         x, y = int(r.getValue("XM", row)), int(r.getValue("YM", row))
         cx, cy = img.getCalibration().convertToAbsoluteX(x), img.getCalibration().convertToAbsoluteY(y)
         points.append([cx,cy])
-        RENDERER.addOverlay(Crosshairs(Pen(java.awt.Color.MAGENTA),  java.awt.Point(x,y), java.awt.Dimension(15,15)))
+        if RENDERER is not None:
+            RENDERER.addOverlay(Crosshairs(Pen(java.awt.Color.MAGENTA),  java.awt.Point(x,y), java.awt.Dimension(15,15)))
 
 
-
-#RENDERER.addOverlays(ovs)
-
 clear_detection(block_id)
 detect_pucks(points, block_id)
-plot_base_plate(points, p=PLOT)    
+if PLOT is not None:
+    plot_base_plate(points, p=PLOT)    
 
 ret = get_puck_detection_dict(block_id)
 

script/imgproc/Utils.py

@@ -15,6 +15,14 @@ def get_img_cover_pos():
     [position, angle, confidence] = run("imgproc/CoverDetection2") 
     return position
 
+def assert_img_in_cover_pos(pos = None):
+    if pos==None: 
+        pos = hexiposi.take()
+    img_segment = get_img_cover_pos()
+    if img_segment != segment:
+        raise Excepton ("Image detection of cover does not match hexiposi: " + str(img_segment))
+    
+
 def in_roi(x,y):
     global roi_center, roi_radius, roi_border
     return math.hypot(x-roi_center[0], y-roi_center[1]) < (roi_radius-roi_border)