class Chunk(object):
"""
when the app is off: 0
when app is on: 1
when maze on refresh: 0
"""
tif = None
csv = None
prev_state = None # should be neither True nor False
open_state = False # but app's initial state was designed to be 1
def __init__(self, path, u3, did_refresh):
self.path = path
self.u3 = u3
self.did_refresh = did_refresh
# to have initial chunk
self.close()
self.nudge_path()
self.open()
self.did_refresh(self.tifpath)
def tick(self):
state = self.u3.getFIOState(6)
if self.prev_state is state: # same state
if state: # is rising
pass # self.open_state = True
else: # is falling
pass # self.open_state = False
else: # new state
# could write simpler code, future me will be suffering
if state: # is rising
self.open_state = True
else: # is falling
self.open_state = False
self.refresh()
self.prev_state = state
def save(self, frame):
if not self.open_state:
return
self.tif.save(frame)
self.csv.write(u'{}\n'.format(time.time()))
def refresh(self):
self.close()
self.nudge_path()
self.open()
self.did_refresh(self.tifpath)
def open(self):
self.tif = TiffWriter(self.tifpath.str, bigtiff=True)
self.csv = self.csvpath.open('w')
def nudge_path(self):
self.tifpath = self.path.joinpath('{}.tif'.format(time.time()))
self.csvpath = self.path.joinpath('{}.csv'.format(time.time()))
def close(self):
if self.tif:
self.tif.close()
if self.csv:
self.csv.close()
self.is_rising = False
def did_refresh(self, tifpath):
pass
class WriterHandler(BaseHandler):
def sync_name(self, member, filedir, filename):
path = ip1_datapath.joinpath(member, filedir)
if not path.is_dir():
os.makedirs(path.str)
self.tifpath = path.joinpath(filename).with_suffix('.tif')
self.csvpath = path.joinpath(filename).with_suffix('.csv')
return True # self.ready()
def check(self, filename):
pass
def ready(self):
if self.tifpath.is_file() or self.csvpath.is_file():
raise Exception(
'Filename already exists. Please provide new one...')
else:
return True
def register(self):
super(WriterHandler, self).register()
self.ready_at = time.time()
def enter(self):
print 'enter'
self.tif = TiffWriter(self.tifpath.str, bigtiff=True)
self.csv = self.csvpath.open('w')
def exposure_end(self, frame, _ts):
if self.svc.bypass:
return
ts = time.time() - self.ready_at
self.tif.save(frame)
# self.tif.save(frame, extratags=[(
# 306, 's', 0, str(ts), False
# )])
self.csv.write(u'{}\n'.format(ts))
def exit(self):
print 'exit'
self.tif.close()
self.csv.close()
def analysis_txt(widget,
imagelist,
roiname,
outlist,
expand_pixel,
roi_enlarge_pixel,
expand_f=0,
meth=None):
num = int(len(outlist))
"""
我们新建了一个QProgressDialog对象progress，设置它的标题、标签、增加取消的按钮。
"""
progress = QProgressDialog(widget)
progress.setWindowTitle("请稍等")
progress.setLabelText("正在操作...")
progress.setCancelButtonText("取消")
"""
如果任务的预期持续时间小于minimumDuration，则对话框根本不会出现。这样可以防止弹出对话框，快速完成任务。对于预期超过minimumDuration的任务，对话框将在minimumDuration时间之后或任何进度设置后立即弹出。如果设置为0，则只要设置任何进度，将始终显示对话框。 默认值为4000毫秒,即4秒。
"""
progress.setMinimumDuration(5) #此属性保留对话框出现之前必须通过的时间。
"""
此属性保留由模态小部件阻止的窗口。
这个属性只对Windows有意义。 模态小部件防止其他窗口中的小部件获取输入。 该属性的值控制在窗口小部件可见时阻止哪些窗口。 窗口可见时更改此属性无效; 您必须首先hide（）小部件，然后再次show（）。
默认情况下，此属性为Qt.NonModal。
"""
progress.setWindowModality(Qt.WindowModal)
"""
由上面我们知道：使用setMinimum() 和setMaximum() 或构造函数来设置操作中的“steps”数量，并在操作进行时调用setValue()。setRange(0,num)就是设置其最小和最大值，这里最小值0，最大值num，num是根据输入框中的数字确定的。
"""
progress.setRange(0, num)
"""
setValue()该属性持有当前的进度。要使进度对话框按预期的方式工作，您应该首先将此属性设置为QProgressDialog的最大最小值， 您可以在中间调用setValue()任意次数。
通过wasCanceled()判断我们是否按下取消按钮，如果按下则提示失败。若for循环顺利结束，执行else后的语句，表明成功
"""
roi2 = ImagejRoi.fromfile(roiname)
outfilename = outlist[0] + "_shift.zip"
if os.path.exists(outfilename):
os.remove(outfilename)
print('outfile:', outfilename)
zip1 = zipfile.ZipFile(outfilename, 'w')
zip1.close()
#os.mkdir(os.path.join(pathway,name))
for roi in roi2:
roi.tofile(outfilename)
img = Image.open(imagelist[0])
img = np.asarray(img, dtype=np.float32)
img_ori = img.copy()
imgs = []
path, filename = os.path.split(outlist[0])
mergefile = os.path.join(path, "_merge.tif")
tifroifile = os.path.join(path, "batch_sequence.txt")
img_ori = draw_roi_onimage(roi2, img_ori)
imgs.append(np.array(img_ori, dtype=np.uint16))
count = 1
for imagefile, outname, templatefile in zip(imagelist[1:], outlist[1:],
imagelist[:-1]):
progress.setValue(count)
if progress.wasCanceled():
QMessageBox.warning(widget, "提示", "操作失败")
break
count += 1
roi2 = ImagejRoi.fromfile(outfilename)
image_template = Image.open(templatefile)
image_template = np.asarray(image_template, dtype=np.float32)
print('processing file:', imagefile)
img = Image.open(imagefile)
print(img.format, img.size, img.mode)
img = np.asarray(img, dtype=np.float32)
img_ori = img.copy()
img = match_histograms(img, image_template, multichannel=False)
height, width = img.shape
outofborder = 0
# align first
alignx, aligny = align.caculate_shift(image_template, img)
alignx = stats.mode(alignx)[0][0]
aligny = stats.mode(aligny)[0][0]
print('alignx', -alignx, 'align_y', -aligny)
img = np.roll(img, aligny, axis=0)
img = np.roll(img, alignx, axis=1)
# padding edge ,top,bottom,left,right
# expand pixel
# print(image_template.shape)
image_template = cv2.copyMakeBorder(image_template,
expand_pixel,
expand_pixel,
expand_pixel,
expand_pixel,
borderType=cv2.BORDER_REPLICATE)
img = cv2.copyMakeBorder(img,
expand_pixel,
expand_pixel,
expand_pixel,
expand_pixel,
borderType=cv2.BORDER_REPLICATE)
# print(image_template.shape)
for roi in roi2:
a, b, c, d = roi.left, roi.bottom, roi.right, roi.top
if a < 0 or b < 0 or c >= width or d >= height:
print('err', a, b, c, d)
roi.left = roi.left + expand_pixel
roi.top = roi.top + expand_pixel
roi.right = roi.right + expand_pixel
roi.bottom = roi.bottom + expand_pixel
roi_corners, roi_imgs, roi_offsets = _get_template_img_from_roi(
image_template,
roi2,
expand_pixel=roi_enlarge_pixel,
expand_f=expand_f)
# match template
pre_image = image_template
roi_corners, roi_imgs, roi_offsets = _get_roiimg_from_match(
img, pre_image, roi_corners, roi_imgs, roi_offsets, roi2,
expand_pixel, expand_f, meth)
pre_image = Image.open(imagefile)
pre_image = np.asarray(pre_image)
# write new roi
outfilename = outname + "_shift.zip"
if os.path.exists(outfilename):
os.remove(outfilename)
print('outfile:', outfilename)
zip1 = zipfile.ZipFile(outfilename, 'w')
zip1.close()
#os.mkdir(os.path.join(pathway,name))
for roi in roi2:
shiftx, shifty = roi_offsets[roi.name][1] # 0 is roi shift
shiftx = int(shiftx)
shifty = int(shifty)
roi.left = roi.left + shiftx - expand_pixel - alignx
roi.top = roi.top + shifty - expand_pixel - aligny
roi.right = roi.right + shiftx - expand_pixel - alignx
roi.bottom = roi.bottom + shifty - expand_pixel - aligny
roi.tofile(outfilename)
img_ori = draw_roi_onimage(roi2, img_ori)
imgs.append(np.array(img_ori, dtype=np.uint16))
else:
progress.setValue(num)
QMessageBox.information(widget, "提示", "操作成功")
# write roi and image merge
tif = TiffWriter(mergefile)
for img in imgs:
tif.write(img, contiguous=True)
tif.close()
# write batch txt for caculate roi
with open(tifroifile, "w") as f:
for imagefile, outname in zip(imagelist, outlist):
outfilename = outname + "_shift.zip"
f.write(imagefile + "\n")
f.write(outfilename + "\n")
laser = TopticaiBeam(port="COM1")
# initialise buffer as a queue
image_buffer = Queue()
# configure camera, pass the buffer queue and enable.
camera.set_client(image_buffer)
camera.exposure_time = exposure_seconds
camera.set_trigger(TriggerType.SOFTWARE, TriggerMode.ONCE)
camera.enable()
# configure laser
laser.power = power_level
laser.set_trigger(TriggerType.HIGH, TriggerMode.BULB)
laser.enable()
# main loop to collect images.
for i in range(n_repeats):
camera.trigger()
time.sleep(interval_seconds)
# shutdown hardware devices
laser.shutdown()
camera.shutdown()
# write out image data to a file.
writer = TiffWriter("data.tif")
for i in range(n_repeats):
writer.save(image_buffer.get())
writer.close()
