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Python cfg.USE_GPU_NMS屬性代碼示例

本文整理匯總了Python中model.config.cfg.USE_GPU_NMS屬性的典型用法代碼示例。如果您正苦於以下問題:Python cfg.USE_GPU_NMS屬性的具體用法?Python cfg.USE_GPU_NMS怎麽用?Python cfg.USE_GPU_NMS使用的例子?那麽, 這裏精選的屬性代碼示例或許可以為您提供幫助。您也可以進一步了解該屬性所在model.config.cfg的用法示例。


在下文中一共展示了cfg.USE_GPU_NMS屬性的5個代碼示例,這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚,您的評價將有助於係統推薦出更棒的Python代碼示例。

示例1: nms

# 需要導入模塊: from model.config import cfg [as 別名]
# 或者: from model.config.cfg import USE_GPU_NMS [as 別名]
def nms(dets, thresh, force_cpu=False):
    """Dispatch to either CPU or GPU NMS implementations."""

    if dets.shape[0] == 0:
        return []
    if cfg.USE_GPU_NMS and not force_cpu:
        return gpu_nms(dets, thresh, device_id=0)
    else:
        return cpu_nms(dets, thresh) 
開發者ID:wanjinchang,項目名稱:SSH-TensorFlow,代碼行數:11,代碼來源:nms_wrapper.py

示例2: nms

# 需要導入模塊: from model.config import cfg [as 別名]
# 或者: from model.config.cfg import USE_GPU_NMS [as 別名]
def nms(dets, thresh, force_cpu=False):
    """Dispatch to either CPU or GPU NMS implementations."""

    if dets.shape[0] == 0:
        return []
    if cfg.USE_GPU_NMS and not force_cpu:
        from nms.gpu_nms import gpu_nms
        return gpu_nms(dets, thresh, device_id=0)
    else:
        from nms.cpu_nms import cpu_nms
        return cpu_nms(dets, thresh) 
開發者ID:Sanster,項目名稱:tf_ctpn,代碼行數:13,代碼來源:nms_wrapper.py

示例3: nms

# 需要導入模塊: from model.config import cfg [as 別名]
# 或者: from model.config.cfg import USE_GPU_NMS [as 別名]
def nms(dets, thresh, force_cpu=False):
  """Dispatch to either CPU or GPU NMS implementations."""

  if dets.shape[0] == 0:
    return []
  if cfg.USE_GPU_NMS and not force_cpu:
    return gpu_nms(dets, thresh, device_id=cfg.GPU_ID)
  else:
    return cpu_nms(dets, thresh) 
開發者ID:pengzhou1108,項目名稱:RGB-N,代碼行數:11,代碼來源:nms_wrapper.py

示例4: nms

# 需要導入模塊: from model.config import cfg [as 別名]
# 或者: from model.config.cfg import USE_GPU_NMS [as 別名]
def nms(dets, thresh, force_cpu=False):
  """Dispatch to either CPU or GPU NMS implementations."""

  if dets.shape[0] == 0:
    return []
  if cfg.USE_GPU_NMS and not force_cpu:
    return gpu_nms(dets, thresh, device_id=0)
  else:
    return cpu_nms(dets, thresh) 
開發者ID:endernewton,項目名稱:tf-faster-rcnn,代碼行數:11,代碼來源:nms_wrapper.py

示例5: proposal_layer

# 需要導入模塊: from model.config import cfg [as 別名]
# 或者: from model.config.cfg import USE_GPU_NMS [as 別名]
def proposal_layer(rpn_cls_prob, rpn_bbox_pred, im_info, cfg_key, anchors, num_anchors):
    """
    A simplified version compared to fast/er RCNN
    For details please see the technical report
    :param
      rpn_cls_prob: (1, H, W, Ax2) softmax result of rpn scores
      rpn_bbox_pred: (1, H, W, Ax4) 1x1 conv result for rpn bbox
    """
    if type(cfg_key) == bytes:
        cfg_key = cfg_key.decode('utf-8')
    pre_nms_topN = cfg[cfg_key].RPN_PRE_NMS_TOP_N
    post_nms_topN = cfg[cfg_key].RPN_POST_NMS_TOP_N
    nms_thresh = cfg[cfg_key].RPN_NMS_THRESH

    # Get the scores and bounding boxes for foreground (text)
    # The order in last dim is related to network.py:
    # self._reshape_layer(rpn_cls_prob_reshape, self._num_anchors * 2, "rpn_cls_prob")
    # scores = rpn_cls_prob[:, :, :, num_anchors:] # old

    height, width = rpn_cls_prob.shape[1:3]  # feature-map的高寬
    scores = np.reshape(np.reshape(rpn_cls_prob, [1, height, width, num_anchors, 2])[:, :, :, :, 1],
                        [1, height, width, num_anchors])

    rpn_bbox_pred = rpn_bbox_pred.reshape((-1, 4))
    scores = scores.reshape((-1, 1))
    proposals = bbox_transform_inv(anchors, rpn_bbox_pred)
    proposals = clip_boxes(proposals, im_info[:2])

    # Pick the top region proposals
    order = scores.ravel().argsort()[::-1]
    if pre_nms_topN > 0:
        order = order[:pre_nms_topN]
    proposals = proposals[order, :]
    scores = scores[order]

    # Non-maximal suppression
    keep = nms(np.hstack((proposals, scores)), nms_thresh, not cfg.USE_GPU_NMS)

    # Pick th top region proposals after NMS
    if post_nms_topN > 0:
        keep = keep[:post_nms_topN]
    proposals = proposals[keep, :]
    scores = scores[keep]

    # Only support single image as input
    blob = np.hstack((scores.astype(np.float32, copy=False), proposals.astype(np.float32, copy=False)))
    return blob, scores 
開發者ID:Sanster,項目名稱:tf_ctpn,代碼行數:49,代碼來源:proposal_layer.py


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