def unpackLabel(self, label):
label_ohc = np.reshape(label[:, :, :, GridParams().numBBox:],
(GridParams().numGridX, GridParams().numGridY,
GridParams().numBBox * GridParams().numClass))
label_box = np.reshape(
label[:, :, :, 0:GridParams().numBBox],
(GridParams().numGridX, GridParams().numGridY,
GridParams().numBBox * GridParams().numBBoxElements))
objIds = self.unpackOHCLabel(label_ohc)
offset, bb = self.unpackBBoxLabel(label_box)
return objIds, offset, bb
def unpackOHCLabel(self, label_ohc):
objIds = []
for i in range(0, GridParams().numGridX):
for j in range(0, GridParams().numGridY):
for k in range(0, GridParams().limNumBBoxPerGrid):
line = label_ohc[i, j, k * GridParams().numClass:(k + 1) *
GridParams().numClass]
c = np.where(line == 1)[0]
if (c.shape[0]) == 1:
objIds.append(c[0])
else:
break
return objIds
def unpackBBoxLabel(self, label_box):
bbList = []
oxyList = []
for i in range(0, GridParams().numGridX):
for j in range(0, GridParams().numGridY):
for k in range(0, GridParams().limNumBBoxPerGrid):
flag = label_box[i, j, k * GridParams().numBBoxElements]
if flag >= 0.5:
start = k * GridParams().numBBoxElements + 1
bb = label_box[i, j, start:start + 4]
oxy = np.array([i, j])
bbList.append(bb)
oxyList.append(oxy)
bb_centers_wh = np.array(bbList)
offset = None
bboxes = None
try:
bb_centers_wh[:, 0:2] *= GridParams().gridW
bb_centers_wh[:, 2:4] *= GridParams().imgW
offset = GridParams().gridW * np.array(oxyList)
bboxes = bb_centers_wh
bboxes[:, 0] += offset[:, 0] - bboxes[:, 2] / 2
bboxes[:, 1] += offset[:, 1] - bboxes[:, 3] / 2
except:
print(bb_centers_wh.shape)
return offset, bboxes.astype(int) if bboxes is not None else None
def getBBoxes_Relative(self, offset, relX, relY, bboxes):
label = np.zeros((bboxes.shape[0], GridParams().numBBoxElements))
ox, oy = np.zeros(((bboxes.shape[0])), dtype=int), np.zeros(
((bboxes.shape[0])), dtype=int)
for i in range(0, bboxes.shape[0]):
x = int(offset[i, 0] / self.gridW)
y = int(offset[i, 1] / self.gridH)
w = bboxes[i, 2] / self.imgW
h = bboxes[i, 3] / self.imgH
ox[i] = x
oy[i] = y
label[i, :] = np.array([
1, relX[i] / GridParams().gridW, relY[i] / GridParams().gridW,
w, h
])
return ox, oy, label
def packBBoxAndObj(self, res_bb, objIds):
label = np.zeros((GridParams().numGridX, GridParams().numGridY,
GridParams().numBBox, 5 + GridParams().numClass))
offset, relX, relY = self.convG2L.getBBoxCenter_Absolute(res_bb)
ox, oy, label_box = self.convG2L.getBBoxes_Relative(
offset, relX, relY, res_bb)
#print(label_box.shape)
counter = np.zeros((GridParams().numGridX, GridParams().numGridY),
dtype=int)
for i in range(0, res_bb.shape[0]):
c = counter[ox[i], oy[i]]
if c < GridParams().limNumBBoxPerGrid:
table = np.concatenate(
[label_box[i, :],
self.getOneHotCode(objIds[i])], axis=0)
label[ox[i], oy[i], c, :] = table
counter[ox[i], oy[i]] += 1
return counter, label
def isMoreThanOneObjPerGrid(self, counter):
for i in range(0, GridParams().numGridX):
for j in range(0, GridParams().numGridY):
if counter[i, j] > 1:
return True
return False
def __init__(self):
self.numGridX, self.numGridY = GridParams().numGridX, GridParams(
).numGridY
self.imgW, self.imgH = GridParams().imgW, GridParams().imgH
self.gridW = GridParams().gridW
self.gridH = GridParams().gridH