def main():
""" Displayes the image file given as first parameter on the command line. """
if len(sys.argv) > 1:
fn = sys.argv[1]
print 'loading %s ...' % fn
img = TIFF(fn)
bit = img.depth
else:
print __doc__
print 'USAGE: %s [image filename]\n' % sys.argv[0]
sys.exit(1)
print("Minimum and maximum pixel values in the image: Min: %d Max: %d" % img.minmax)
print("Rescaling to fill full 16bit space.")
img.data = img.rescale()
# determine screen size (see http://stackoverflow.com/a/3949983/183995 )
root = Tkinter.Tk()
screen_width, screen_height = root.winfo_screenwidth(), root.winfo_screenheight()
small = img
while small.dimensions[0] > screen_height or small.dimensions[1] > screen_width:
small.scale_down_to_half()
def onmouse(event, x, y, flags, param):
h, w = img.dimensions
hs, ws = small.dimensions
x, y = int(1.0*x*h/hs), int(1.0*y*h/hs)
show_zoom(x,y)
zoom_window_size = 466
zoom_factor = 3
zoom = np.zeros((zoom_window_size, zoom_window_size),img.data.dtype)
def show_zoom(x,y):
h, w = img.dimensions
img_box = rectangle()
img_box.pos = coordinates(0,0)
img_box.dim = coordinates(w,h)
box = img_box.get_rectangle_inside(zoom_window_size/zoom_factor, coordinates(x,y))
f, t = box.corners()
#zoom = cv2.getRectSubPix(img, (800, 600), (x+0.5, y+0.5))
#cv2.GetSubRect(img, (60, 70, 32, 32))
#zoom = cv2.getRectSubPix(img, (200, 200), (x, y))
#zoom = img[f.y:t.y, f.x:t.x]
## http://docs.opencv.org/modules/imgproc/doc/geometric_transformations.html#resize
cv2.resize(img.data[f.y:t.y, f.x:t.x], dsize=(zoom_window_size,zoom_window_size), dst=zoom, interpolation=cv2.INTER_NEAREST)
cv2.imshow('Detail', zoom)
cv2.namedWindow("Detail")
cv2.moveWindow("Detail", 5, 50+small.dimensions[0])
cv2.imshow('Overview', small.data)
cv2.moveWindow("Overview", 5, 20)
show_zoom(0,0)
cv2.setMouseCallback('Overview', onmouse)
cv2.waitKey()
def read_image(self, imgfile, bgfile=None):
""" imgfile and bgfile should be ('/path/to/folder','filename.tif') """
self.imgfile, self.bgfile = imgfile, bgfile
self.img = TIFF(os.path.join(imgfile))
if bgfile:
self.img.data -= TIFF(os.path.join(bgfile)).data
self.minmax = self.img.minmax
self.percentiles = self.img.percentiles([1,5,99,99.995])
self.blobs = find_blobs(self.img.data)
class MeasurementPoint(object):
"""
This class holds all data associated with a single measurement point.
This includes an XML file, the image from the spectrometer and a
background reference image.
"""
PD_SCOPE_CHANNEL = 0
ION_SCOPE_CHANNEL = 1
collection = None
def __init__(self, date, avgnum, xmlfile, imgfile, bgfile=None):
#print("Reading XML file %s" % xmlfile)
self.date = date
self.avgnum = avgnum
self.read_xml(xmlfile)
self.read_image(imgfile,bgfile)
def read_xml(self, xmlfile):
""" xmlfile should be ('/path/to/folder','filename.xml') """
self.xmlfile = xmlfile
f = open(xmlfile, "r")
tree = parse(f)
self.xml = tree.getroot()
f.close()
def read_image(self, imgfile, bgfile=None):
""" imgfile and bgfile should be ('/path/to/folder','filename.tif') """
self.imgfile, self.bgfile = imgfile, bgfile
self.img = TIFF(os.path.join(imgfile))
if bgfile:
self.img.data -= TIFF(os.path.join(bgfile)).data
self.minmax = self.img.minmax
self.percentiles = self.img.percentiles([1,5,99,99.995])
self.blobs = find_blobs(self.img.data)
def display_image(self, rescale=False, rescale_to_global_minmax=False, rescale_to_percentile_and_max=False):
""" Displayes the spectrometer image using OpenCV's function :py:func:`cv2.imshow` """
if rescale:
i = self.img
if rescale_to_global_minmax:
print("Rescaling to global min and max values (%d,%d)" % self.collection.minmax)
img_data = i.rescale(self.collection.minmax)
elif rescale_to_percentile_and_max:
print("Rescaling image using 5 percent percentile to local maximum value: (%d,%d)." % (self.percentiles[5], i.minmax[1]))
img_data = i.rescale((self.percentiles[5], i.minmax[1]))
else:
img_data = i.rescale(i.minmax)
else:
img_data = self.img.data
cv2.imshow('test',img_data)
return cv2.waitKey()
def __str__(self):
return "MeasurementPoint: (date: %s, xml: %s, image: %s, bgimage: %s)" % (self.date, self.xmlfile, self.imgfile, self.bgfile)
def dump_xml_structure(self, level=0):
""" Returns a human readable dump of the xml structure.
Implemented as a recursive function.
Therefore call without providing the `level` argument."""
output = ''
for element in self.xml:
output += ''.join(['--' for i in range(level)])
output += "> " + element.tag
if element.text != None:
content = element.text.replace("\n"," ")
output += " : "
if len(content) < 20:
output += content
else:
output += content[:20] + " ..."
output += "\n"
output += self.dump_xml_structure(element, level+1)
return output
def get_stage_positions(self):
raise NotImplementedError
def get_photodiode_scope_channel(self):
return self.get_scope_channel(self.PD_SCOPE_CHANNEL)
def get_ion_scope_channel(run):
return self.get_scope_channel(self.ION_SCOPE_CHANNEL)
def get_scope_channel(run, channel_no):
for scope in run:
if scope.tag == 'NI_TCP_Scope':
for channel in scope:
if channel.tag == 'CH' + str(channel_no):
data = channel.text
data = [float(value) for value in data.split()]
return data
def calculate_ion_signal(self):
ion_signal_point = 0.0
for ion_signal_point in self.get_ion_scope_channel():
ion_signal += ion_signal_point
return ion_signal