/// <summary>
/// Setup the layer.
/// </summary>
/// <param name="colBottom">Specifies the collection of bottom (input) Blobs.</param>
/// <param name="colTop">Specifies the collection of top (output) Blobs.</param>
public override void LayerSetUp(BlobCollection <T> colBottom, BlobCollection <T> colTop)
{
base.LayerSetUp(colBottom, colTop);
if (m_param.propagate_down.Count == 0)
{
m_param.propagate_down.Add(true);
m_param.propagate_down.Add(true);
m_param.propagate_down.Add(false);
m_param.propagate_down.Add(false);
}
m_nNum = colBottom[0].num;
m_nNumPriors = colBottom[2].height / 4;
// Get other parameters.
m_nNumClasses = (int)m_param.multiboxloss_param.num_classes;
m_log.CHECK_GE(m_nNumClasses, 1, "The num_classes should not be less than 1.");
m_bShareLocation = m_param.multiboxloss_param.share_location;
m_nLocClasses = (m_bShareLocation) ? 1 : m_nNumClasses;
m_nBackgroundLabelId = (int)m_param.multiboxloss_param.background_label_id;
m_bUseDifficultGt = m_param.multiboxloss_param.use_difficult_gt;
m_miningType = m_param.multiboxloss_param.mining_type;
if (m_param.multiboxloss_param.do_neg_mining.HasValue)
{
m_log.WriteLine("WARNING: do_neg_mining is depreciated, use mining_type instead.");
m_bDoNegMining = m_param.multiboxloss_param.do_neg_mining.Value;
m_log.CHECK(m_bDoNegMining == (m_miningType != MultiBoxLossParameter.MiningType.NONE), "The mining type specified is inconsistent with do_neg_mining.");
}
else
{
m_bDoNegMining = (m_miningType != MultiBoxLossParameter.MiningType.NONE);
}
if (m_bDoNegMining)
{
m_log.CHECK(m_bShareLocation, "Currently only support negative mining if share_location is true.");
}
// Setup localization loss layer.
m_fLocWeight = m_param.multiboxloss_param.loc_weight;
m_locLossType = m_param.multiboxloss_param.loc_loss_type;
// fake shape
List <int> rgLocShape = Utility.Create <int>(1, 1);
rgLocShape.Add(4);
m_blobLocPred.Reshape(rgLocShape);
m_blobLocGt.Reshape(rgLocShape);
m_colLocBottom.Add(m_blobLocPred);
m_colLocBottom.Add(m_blobLocGt);
List <int> rgLossShape = Utility.Create <int>(1, 1);
m_blobLocLoss.Reshape(rgLossShape);
m_colLocTop.Add(m_blobLocLoss);
if (m_locLossType == MultiBoxLossParameter.LocLossType.L2)
{
LayerParameter p = new LayerParameter(LayerParameter.LayerType.EUCLIDEAN_LOSS);
p.name += "_l2_loc";
p.loss_weight.Add(m_fLocWeight);
m_locLossLayer = Layer <T> .Create(m_cuda, m_log, p, null);
m_locLossLayer.Setup(m_colLocBottom, m_colLocTop);
}
else if (m_locLossType == MultiBoxLossParameter.LocLossType.SMOOTH_L1)
{
LayerParameter p = new LayerParameter(LayerParameter.LayerType.SMOOTHL1_LOSS);
p.name += "_smooth_l1_loc";
p.loss_weight.Add(m_fLocWeight);
m_locLossLayer = Layer <T> .Create(m_cuda, m_log, p, null);
m_locLossLayer.Setup(m_colLocBottom, m_colLocTop);
}
else
{
m_log.FAIL("Unknown localization loss type.");
}
// Setup confidence loss layer.
m_confLossType = m_param.multiboxloss_param.conf_loss_type;
m_colConfBottom.Add(m_blobConfPred);
m_colConfBottom.Add(m_blobConfGt);
m_blobConfLoss.Reshape(rgLossShape);
m_colConfTop.Add(m_blobConfLoss);
List <int> rgConfShape = Utility.Create <int>(1, 1);
if (m_confLossType == MultiBoxLossParameter.ConfLossType.SOFTMAX)
{
m_log.CHECK_GE(m_nBackgroundLabelId, 0, "The background_label_id should be within [0, num_classes) for Softmax.");
m_log.CHECK_LT(m_nBackgroundLabelId, m_nNumClasses, "The background_label_id should be within [0, num_classes) for Softmax.");
LayerParameter p = new LayerParameter(LayerParameter.LayerType.SOFTMAXWITH_LOSS);
p.name += "_softmax_conf";
p.loss_weight.Add(1);
p.loss_param.normalization = LossParameter.NormalizationMode.NONE;
p.softmax_param.axis = 1;
// Fake shape.
m_blobConfGt.Reshape(rgConfShape);
rgConfShape.Add(m_nNumClasses);
m_blobConfPred.Reshape(rgConfShape);
m_confLossLayer = Layer <T> .Create(m_cuda, m_log, p, null);
m_confLossLayer.Setup(m_colConfBottom, m_colConfTop);
}
else if (m_confLossType == MultiBoxLossParameter.ConfLossType.LOGISTIC)
{
LayerParameter p = new LayerParameter(LayerParameter.LayerType.SIGMOIDCROSSENTROPY_LOSS);
p.name += "_logistic_conf";
p.loss_weight.Add(1);
// Fake shape
rgConfShape.Add(m_nNumClasses);
m_blobConfGt.Reshape(rgConfShape);
m_blobConfPred.Reshape(rgConfShape);
m_confLossLayer = Layer <T> .Create(m_cuda, m_log, p, null);
m_confLossLayer.Setup(m_colConfBottom, m_colConfTop);
}
else
{
m_log.FAIL("Unknown confidence loss type.");
}
}
/// <summary>
/// Setup the layer.
/// </summary>
/// <param name="colBottom">Specifies the collection of bottom (input) Blobs.</param>
/// <param name="colTop">Specifies the collection of top (output) Blobs.</param>
public override void LayerSetUp(BlobCollection <T> colBottom, BlobCollection <T> colTop)
{
base.LayerSetUp(colBottom, colTop);
if (m_param.propagate_down.Count == 0)
{
m_param.propagate_down.Add(true);
m_param.propagate_down.Add(true);
m_param.propagate_down.Add(false);
m_param.propagate_down.Add(false);
}
m_nNum = colBottom[0].num;
m_nNumPriors = colBottom[2].height / 4;
// Get other parameters.
m_nNumClasses = (int)m_param.multiboxloss_param.num_classes;
m_log.CHECK_GE(m_nNumClasses, 1, "The num_classes should not be less than 1.");
m_bShareLocation = m_param.multiboxloss_param.share_location;
m_nLocClasses = (m_bShareLocation) ? 1 : m_nNumClasses;
m_nBackgroundLabelId = (int)m_param.multiboxloss_param.background_label_id;
m_bUseDifficultGt = m_param.multiboxloss_param.use_difficult_gt;
m_miningType = m_param.multiboxloss_param.mining_type;
if (m_param.multiboxloss_param.do_neg_mining.HasValue)
{
m_log.WriteLine("WARNING: do_neg_mining is depreciated, use mining_type instead.");
m_bDoNegMining = m_param.multiboxloss_param.do_neg_mining.Value;
m_log.CHECK(m_bDoNegMining == (m_miningType != MultiBoxLossParameter.MiningType.NONE), "The mining type specified is inconsistent with do_neg_mining.");
}
m_bDoNegMining = (m_miningType != MultiBoxLossParameter.MiningType.NONE);
if (m_bDoNegMining)
{
m_log.CHECK(m_bShareLocation, "Currently only support negative mining if share_location is true.");
}
// Setup localization loss layer.
m_fLocWeight = m_param.multiboxloss_param.loc_weight;
m_locLossType = m_param.multiboxloss_param.loc_loss_type;
// fake shape
List <int> rgLocShape = Utility.Create <int>(1, 1);
rgLocShape.Add(4);
m_blobLocPred.Reshape(rgLocShape);
m_blobLocGt.Reshape(rgLocShape);
m_colLocBottom.Add(m_blobLocPred);
m_colLocBottom.Add(m_blobLocGt);
List <int> rgLossShape = Utility.Create <int>(1, 1);
m_blobLocLoss.Reshape(rgLossShape);
m_colLocTop.Add(m_blobLocLoss);
if (m_locLossType == MultiBoxLossParameter.LocLossType.L2)
{
LayerParameter p = new LayerParameter(LayerParameter.LayerType.EUCLIDEAN_LOSS);
p.name += "_l2_loc";
p.loss_weight.Add(m_fLocWeight);
m_locLossLayer = Layer <T> .Create(m_cuda, m_log, p, null);
m_locLossLayer.Setup(m_colLocBottom, m_colLocTop);
}
else if (m_locLossType == MultiBoxLossParameter.LocLossType.SMOOTH_L1)
{
LayerParameter p = new LayerParameter(LayerParameter.LayerType.SMOOTHL1_LOSS);
p.name += "_smooth_l1_loc";
p.loss_weight.Add(m_fLocWeight);
m_locLossLayer = Layer <T> .Create(m_cuda, m_log, p, null);
m_locLossLayer.Setup(m_colLocBottom, m_colLocTop);
}
else
{
m_log.FAIL("Unknown localization loss type.");
}
// Setup confidence loss layer.
m_confLossType = m_param.multiboxloss_param.conf_loss_type;
m_colConfBottom.Add(m_blobConfPred);
m_colConfBottom.Add(m_blobConfGt);
m_blobConfLoss.Reshape(rgLossShape);
m_colConfTop.Add(m_blobConfLoss);
List <int> rgConfShape = Utility.Create <int>(1, 1);
if (m_confLossType == MultiBoxLossParameter.ConfLossType.SOFTMAX)
{
m_log.CHECK_GE(m_nBackgroundLabelId, 0, "The background_label_id should be within [0, num_classes) for Softmax.");
m_log.CHECK_LT(m_nBackgroundLabelId, m_nNumClasses, "The background_label_id should be within [0, num_classes) for Softmax.");
LayerParameter p = new LayerParameter(LayerParameter.LayerType.SOFTMAXWITH_LOSS);
p.name += "_softmax_conf";
p.loss_weight.Add(1);
p.loss_param.normalization = LossParameter.NormalizationMode.NONE;
p.softmax_param.axis = 1;
// Fake shape.
m_blobConfGt.Reshape(rgConfShape);
rgConfShape.Add(m_nNumClasses);
m_blobConfPred.Reshape(rgConfShape);
m_confLossLayer = Layer <T> .Create(m_cuda, m_log, p, null);
m_confLossLayer.Setup(m_colConfBottom, m_colConfTop);
}
else if (m_confLossType == MultiBoxLossParameter.ConfLossType.LOGISTIC)
{
LayerParameter p = new LayerParameter(LayerParameter.LayerType.SIGMOIDCROSSENTROPY_LOSS);
p.name += "_logistic_conf";
p.loss_weight.Add(1);
// Fake shape
rgConfShape.Add(m_nNumClasses);
m_blobConfGt.Reshape(rgConfShape);
m_blobConfPred.Reshape(rgConfShape);
m_confLossLayer = Layer <T> .Create(m_cuda, m_log, p, null);
m_confLossLayer.Setup(m_colConfBottom, m_colConfTop);
}
else
{
m_log.FAIL("Unknown confidence loss type.");
}
// Create the low-level SSD support.
if (m_param.multiboxloss_param.use_gpu)
{
float?fNmsThreshold = null;
int? nNmsTopK = null;
float?fNmsEta = null;
bool bNmsParam = false;
if (m_param.multiboxloss_param.nms_param != null && m_param.multiboxloss_param.nms_param.Active)
{
bNmsParam = true;
fNmsThreshold = m_param.multiboxloss_param.nms_param.nms_threshold;
nNmsTopK = m_param.multiboxloss_param.nms_param.top_k;
fNmsEta = m_param.multiboxloss_param.nms_param.eta;
}
m_hSsd = m_cuda.CreateSSD(m_nNumClasses,
m_bShareLocation,
m_nLocClasses,
m_nBackgroundLabelId,
m_bUseDifficultGt,
(SSD_MINING_TYPE)(int)m_miningType,
(SSD_MATCH_TYPE)(int)m_param.multiboxloss_param.match_type,
m_param.multiboxloss_param.overlap_threshold,
m_param.multiboxloss_param.use_prior_for_matching,
(SSD_CODE_TYPE)(int)m_param.multiboxloss_param.code_type,
m_param.multiboxloss_param.encode_variance_in_target,
m_param.multiboxloss_param.bp_inside,
m_param.multiboxloss_param.ignore_cross_boundary_bbox,
m_param.multiboxloss_param.use_prior_for_nms,
(SSD_CONF_LOSS_TYPE)(int)m_param.multiboxloss_param.conf_loss_type,
(SSD_LOC_LOSS_TYPE)(int)m_param.multiboxloss_param.loc_loss_type,
m_param.multiboxloss_param.neg_pos_ratio,
m_param.multiboxloss_param.neg_overlap,
m_param.multiboxloss_param.sample_size,
m_param.multiboxloss_param.map_object_to_agnostic,
bNmsParam,
fNmsThreshold,
nNmsTopK,
fNmsEta);
if (m_hSsd == 0)
{
throw new Exception("Could not create the SSD!");
}
}
}
