def load_next_image(self,loss_task):
if loss_task == 0:
if self.cls_cur == len(self.cls_list):
self.cls_cur = 0
random.shuffle(self.cls_list)
cur_data = self.cls_list[self.cls_cur] # Get the image index
im = cur_data[0]
label = cur_data[1]
roi = [-1,-1,-1,-1]
pts = [-1,-1,-1,-1,-1,-1,-1,-1,-1,-1]
if random.choice([0,1])==1:
im = cv2.flip(im,random.choice([-1,0,1]))
self.cls_cur += 1
return im, label, roi, pts
if loss_task == 1:
if self.roi_cur == len(self.roi_list):
self.roi_cur = 0
random.shuffle(self.roi_list)
cur_data = self.roi_list[self.roi_cur] # Get the image index
im = cur_data[0]
label = -1
roi = cur_data[2]
pts = [-1,-1,-1,-1,-1,-1,-1,-1,-1,-1]
self.roi_cur += 1
return im, label, roi, pts
if loss_task == 2:
if self.pts_cur == len(self.pts_list):
self.pts_cur = 0
random.shuffle(self.pts_list)
cur_data = self.pts_list[self.pts_cur] # Get the image index
im = cur_data[0]
label = -1
roi = [-1,-1,-1,-1]
pts = cur_data[3]
self.pts_cur += 1
return im, label, roi, pts
################################################################################
######################Regression Loss Layer By Python###########################
################################################################################
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