def initWithParams(self,filename="",seek=0,angle=0,pers=None,crop=[0,1000],every=1, identity=2.0, margin=0, focus=[333,666,333,666], zero=False, trailing=10, antishake=5, ):
self.filename = filename
self.cap = cv2.VideoCapture(filename)
self.every = every
self.identity = identity
self.margin = margin
self.zero = zero
self.trailing = trailing
self.angle = angle
self.focus = focus
self.antishake= antishake
self.nframes = 0 #1 is the first frame
self.crop = crop
ret = True
for i in range(seek): #skip frames
ret = self.cap.grab()
if not ret:
break
#ret, frame = cap.read()
self.nframes += 1
if not ret:
sys.exit(0)
ret, frame = self.cap.read()
self.nframes += 1
if not ret:
sys.exit(0)
self.rawframe = frame.copy()
original_h, original_w, d = frame.shape
self.rotated_h, self.rotated_w = original_h,original_w
if angle:
#Apply rotation
self.R, self.rotated_w,self.rotated_h = trainscanner.rotate_matrix(-angle*math.pi/180, original_w, original_h)
frame = cv2.warpAffine(frame, self.R, (self.rotated_w,self.rotated_h))
if pers is not None:
self.M = trainscanner.warp_matrix(pers,self.rotated_w,self.rotated_h)
frame = cv2.warpPerspective(frame,self.M,(self.rotated_w,self.rotated_h))
else:
self.M = None
#cropping
self.frame = frame[crop[0]*self.rotated_h/1000:crop[1]*self.rotated_h/1000, :, :]
self.cropped_h,self.cropped_w = self.frame.shape[0:2]
#Prepare a scalable canvas with the origin.
self.canvas = [self.cropped_w,self.cropped_h,100,0,0]
#sys.stderr.write("canvas size{0} {1} {2} {3}\n".format(self.canvas[0],self.canvas[1],*self.crop))
#sys.exit(1)
self.LOG = sys.stdout
self.LOG.write("{0}\n".format(filename))
self.LOG.write("#-r {0}\n".format(angle))
if pers is not None:
self.LOG.write("#-p {0},{1},{2},{3}\n".format(*pers))
self.LOG.write("#-c {0},{1}\n".format(*crop))
#end of the header
self.LOG.write("\n")
def show_snapshots(self, region=None):
"""
put the snapshots in the preview panes
"""
if self.frame < 0:
return
image = self.asyncimageloader.snapshots[self.frame]
h,w = image.shape[0:2]
#Left image: unwarped
R, width,height = trainscanner.rotate_matrix(-self.angle_degree*math.pi/180,w,h)
image = cv2.warpAffine(image, R, (width,height))
processed = image.copy()
#trainscanner.draw_guide(image, self.pers, gauge=False) #second is pers
#color order is different between cv2 and pyqt
self.put_cv2_image(image, self.raw_image_pane)
#Right image: warped
#M = trainscanner.warp_matrix0(self.pers,width,height)
M,wwidth = trainscanner.warp_matrix2(self.pers,width,height)
processed = cv2.warpPerspective(processed,M,(wwidth,height))
processed = processed[self.croptop*height/1000:self.cropbottom*height/1000, :, :]
if region is not None:
print(region)
#assume the QLabel size is square preview_size x preview_size
top, left, bottom, right = region.top(), region.left(), region.bottom(), region.right()
if top < 0:
top = 0
if left < 0:
left = 0
if right > self.preview_size:
right = self.preview_size
if bottom > self.preview_size:
bottom = self.preview_size
#and also assume that the cropped image is centered and sometimes shrinked.
top -= self.preview_size/2
bottom -= self.preview_size/2
left -= self.preview_size/2
right -= self.preview_size/2
#expected image size in the window
height, width = processed.shape[0:2]
if height > width:
if height > self.preview_size:
width = width * self.preview_size / height
height = self.preview_size
else:
if width > self.preview_size:
height = height * self.preview_size / width
width = self.preview_size
#indicate the region size relative to the image size
#print(left,right,top,bottom)
top = top * 1000 / height + 500
bottom = bottom * 1000 / height + 500
left = left * 1000 / width + 500
right = right * 1000 / width + 500
#print(left,right,top,bottom)
if top < 0:
top = 0
if top > 1000:
top = 1000
if bottom < 0:
bottom = 0
if bottom > 1000:
bottom = 1000
if left < 0:
left = 0
if left > 1000:
left = 1000
if right < 0:
right = 0
if right > 1000:
right = 1000
self.focus = left,right,top,bottom
#print(self.focus)
#trainscanner.draw_focus_area(processed, self.focus)
#draw_slitpos(processed, self.slitpos)
self.put_cv2_image(processed, self.processed_pane)