107 lines
3.1 KiB
Python
107 lines
3.1 KiB
Python
###################################################################################################
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# Procedure to detect the puck light spots.
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###################################################################################################
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assert_imaging_enabled()
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COVER_PRESENT = True
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ROOM_TEMP = is_room_temp()
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USE_MASK = True
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if get_exec_pars().source == CommandSource.ui:
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PLOT = None
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RENDERER = None
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TEXT = None
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if COVER_PRESENT:
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cover_position = hexiposi.readback.take()
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if (cover_position is None) or (cover_position == "Unknown"):
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raise Exception("Unknown cover position")
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else:
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block_id = cover_position.upper()[0]
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else:
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block_id = None
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print "Block id: ", block_id
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number_frames = 5 if ROOM_TEMP else 10
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number_backgrounds = 5 if ROOM_TEMP else 5
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minimum_size = 78 # r = 5 # 150
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maximum_size = 750 # r = 15 #1500
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min_circ = 0.2
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threshold_method = "MaxEntropy" if ROOM_TEMP else "Default" #Apparently good for LN2: Default, Intermodes, IsoData, Otsu
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threshold_method,threshold_range = "Manual", (0, 215)
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exclude_edges = True
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led_latency = 0.5 #0.1
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set_led_state(False)
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time.sleep(led_latency)
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img.waitNext(2000)
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background = average_frames(number_backgrounds)
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#background = integrate_frames(number_backgrounds)
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set_led_state(True)
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time.sleep(led_latency)
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img.waitNext(2000)
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image = average_frames(number_frames)
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#image = integrate_frames(number_frames)
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set_led_state(False)
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op_image(image, background, "subtract", float_result=True, in_place=True)
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image=grayscale(image)
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if RENDERER is not None and RENDERER.isShowing():
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RENDERER.setImage(None, image.getBufferedImage(), None)
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else:
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RENDERER = show_panel(image.getBufferedImage())
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RENDERER.clearOverlays()
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if USE_MASK:
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mask_img = run("imgproc/CreateMask")
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#mask_img=grayscale(mask_img)
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#show_panel( mask_img.getBufferedImage())
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op_image(image, mask_img, "and", float_result=False, in_place=True)
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RENDERER.setImage(None, image.getBufferedImage(), None)
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invert(image)
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if threshold_method == "Manual":
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threshold(image, threshold_range[0], threshold_range[1])
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else:
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auto_threshold(image, method = threshold_method) #Tested ok: MaxEntropy, Triangle, Yen
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(r,output) = analyse_particles(image, minimum_size,maximum_size,
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fill_holes = True, exclude_edges = exclude_edges, print_table=False,
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output_image = "outlines", minCirc = min_circ
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, maxCirc = 1.0)
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points = []
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for row in range (r.counter):
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if in_roi(r.getValue("XM",row), r.getValue("YM",row)):
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x, y = int(r.getValue("XM", row)), int(r.getValue("YM", row))
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cx, cy = img.getCalibration().convertToAbsoluteX(x), img.getCalibration().convertToAbsoluteY(y)
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points.append([cx,cy])
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if RENDERER is not None:
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RENDERER.addOverlay(Crosshairs(Pen(java.awt.Color.MAGENTA), java.awt.Point(x,y), java.awt.Dimension(15,15)))
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clear_detection(block_id)
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detect_pucks(points, block_id)
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if PLOT is not None:
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plot_base_plate(points, p=PLOT)
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ret = get_puck_detection_dict(block_id)
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if TEXT is not None:
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TEXT.setText(str(ret))
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set_return(ret)
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