def labels2output_map(label,lppts,dim,stride): side = ((float(dim) + 40.)/2.)/stride # 7.75 when dim = 208 and stride = 16 outsize = dim/stride Y = np.zeros((outsize,outsize,2*4+1),dtype='float32') MN = np.array([outsize,outsize]) WH = np.array([dim,dim],dtype=float) tlx,tly = np.floor(np.maximum(label.tl(),0.)*MN).astype(int).tolist() brx,bry = np.ceil (np.minimum(label.br(),1.)*MN).astype(int).tolist() for x in range(tlx,brx): for y in range(tly,bry): mn = np.array([float(x) + .5, float(y) + .5]) iou = IOU_centre_and_dims(mn/MN,label.wh(),label.cc(),label.wh()) if iou > .5: p_WH = lppts*WH.reshape((2,1)) p_MN = p_WH/stride p_MN_center_mn = p_MN - mn.reshape((2,1)) p_side = p_MN_center_mn/side Y[y,x,0] = 1. Y[y,x,1:] = p_side.T.flatten() return Y
def labels2output_map(label,lppts,dim_w, dim_h,stride, cls):
side = ((float(dim_w) + 40.)/2.)/stride # 7.75 when dim = 208 and stride = 16
outsize = int(dim_w/stride)
Y = np.zeros((outsize,outsize,2*4+3),dtype='float32')
non_object_probs_template = np.ones((outsize,outsize),dtype='float32')
Y[...,10] = non_object_probs_template.copy()
MN = np.array([outsize,outsize])
WH = np.array([dim_w,dim_h],dtype=float)
tlx,tly = np.floor(np.maximum(label.tl(),0.)*MN).astype(int).tolist()
brx,bry = np.ceil (np.minimum(label.br(),1.)*MN).astype(int).tolist()
is_there_plate = False
for x in range(tlx,brx):
for y in range(tly,bry):
mn = np.array([float(x) + .5, float(y) + .5])
iou = IOU_centre_and_dims(mn/MN,label.wh(),label.cc(),label.wh())
iou2 = iou_alternative(mn/MN, label.wh(), label.cc(), label.wh())
iou_max = max(iou, iou2)
if iou_max > .5:
is_there_plate = True
p_WH = lppts*WH.reshape((2,1))
p_MN = p_WH/stride
p_MN_center_mn = p_MN - mn.reshape((2,1))
p_side = p_MN_center_mn/side
if cls=='0':
Y[y,x,0] = 1.
Y[y,x,9] = 0.
else:
Y[y, x, 0] = 0.
Y[y, x, 9] = 1.
Y[y,x,1:9] = p_side.T.flatten()
Y[y, x, 10] = 0.
# if not is_there_plate:
# print('sem placa na amostra: %s' % image_abs_path)
return Y, is_there_plate