def transform_loc(loc, loc_base_idx, anchor, anchor_base_idx, clip, vx, vy,
vw, vh):
"""Transform prior anchor box to output box through location predictions."""
al = anchor[anchor_base_idx]
at = anchor[anchor_base_idx + 1]
ar = anchor[anchor_base_idx + 2]
ab = anchor[anchor_base_idx + 3]
aw = ar - al
ah = ab - at
ax = (al + ar) / 2.0
ay = (at + ab) / 2.0
px = loc[loc_base_idx]
py = loc[loc_base_idx + 1]
pw = loc[loc_base_idx + 2]
ph = loc[loc_base_idx + 3]
ox = px * vx * aw + ax
oy = py * vy * ah + ay
ow = exp(pw * vw) * aw / 2.0
oh = exp(ph * vh) * ah / 2.0
return (
tvm.tir.if_then_else(clip, tvm.te.max(0.0,
tvm.te.min(1.0, ox - ow)),
ox - ow),
tvm.tir.if_then_else(clip, tvm.te.max(0.0,
tvm.te.min(1.0, oy - oh)),
oy - oh),
tvm.tir.if_then_else(clip, tvm.te.max(0.0,
tvm.te.min(1.0, ox + ow)),
ox + ow),
tvm.tir.if_then_else(clip, tvm.te.max(0.0,
tvm.te.min(1.0, oy + oh)),
oy + oh),
)
def _hybridy_transform_loc(box, pred_loc, variance, clip):
"""Transform prior anchor box to output box through location predictions.
"""
al = box[0]
at = box[1]
ar = box[2]
ab = box[3]
px = pred_loc[0]
py = pred_loc[1]
pw = pred_loc[2]
ph = pred_loc[3]
vx = variance[0]
vy = variance[1]
vw = variance[2]
vh = variance[3]
output = output_tensor((4, ), pred_loc.dtype)
aw = ar - al
ah = ab - at
ax = (al + ar) / 2.0
ay = (at + ab) / 2.0
ox = px * vx * aw + ax
oy = py * vy * ah + ay
ow = exp(pw * vw) * aw / 2.0
oh = exp(ph * vh) * ah / 2.0
output[0] = max(0.0, min(1.0, ox - ow)) if clip else ox - ow
output[1] = max(0.0, min(1.0, oy - oh)) if clip else oy - oh
output[2] = max(0.0, min(1.0, ox + ow)) if clip else ox + ow
output[3] = max(0.0, min(1.0, oy + oh)) if clip else oy + oh
return output