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
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.if_then_else(clip, tvm.max(0.0, tvm.min(1.0, ox - ow)), ox - ow), \ tvm.if_then_else(clip, tvm.max(0.0, tvm.min(1.0, oy - oh)), oy - oh), \ tvm.if_then_else(clip, tvm.max(0.0, tvm.min(1.0, ox + ow)), ox + ow), \ tvm.if_then_else(clip, tvm.max(0.0, tvm.min(1.0, oy + oh)), oy + oh)