def postprocess(output):
score = output[self._output_layers['rnet']['probabilities']][:, 1]
regions = output[self._output_layers['rnet']['regions']]
return utils.calibrate_bboxes(prev_stage_output,
score,
regions,
nms_type='union')
def postprocess(output):
score = output[self._output_layers['onet']['probabilities']][:, 1]
regions = output[self._output_layers['onet']['regions']]
bboxes = utils.calibrate_bboxes(prev_stage_output, score, regions)
pick = utils.nms(bboxes, 0.7, 'min')
bboxes_to_remove = np.setdiff1d(np.arange(len(bboxes)), pick)
return np.delete(bboxes, bboxes_to_remove, axis=0)
def postprocess(output):
score = output[[
i for i, _ in output.items()
if i.any_name == self._output_layers['rnet']['probabilities']
][0]][:, 1]
regions = output[[
i for i, _ in output.items()
if i.any_name == self._output_layers['rnet']['regions']
][0]]
return utils.calibrate_bboxes(prev_stage_output,
score,
regions,
nms_type='union')
