def _add_fast_rcnn_head(model, add_roi_box_head_func, blob_in, dim_in,
spatial_scale_in):
"""
blob_in:
[BlobReference("gpu_0/fpn_res5_2_sum"),
BlobReference("gpu_0/fpn_res4_22_sum"),
BlobReference("gpu_0/fpn_res3_3_sum"),
BlobReference("gpu_0/fpn_res2_2_sum")]
spatial_scale_in:
[0.03125, 0.0625, 0.125, 0.25]
dim_in:
256
"""
"""Add a Fast R-CNN head to the model."""
# 对fpn中的每一层提取特征图
blob_frcn, dim_frcn = add_roi_box_head_func(model, blob_in, dim_in,
spatial_scale_in)
# 添加输出
fast_rcnn_heads.add_fast_rcnn_outputs(model, blob_frcn, dim_frcn)
if model.train:
# 添加损失，梯度以及度量方法
loss_gradients = fast_rcnn_heads.add_fast_rcnn_losses(model)
else:
loss_gradients = None
return loss_gradients
def _single_gpu_build_func(model):
"""Builds the model on a single GPU. Can be called in a loop over GPUs
with name and device scoping to create a data parallel model."""
blob, dim, spatial_scale = add_conv_body_func(model)
if not model.train:
model.conv_body_net = model.net.Clone('conv_body_net')
rfcn_heads.add_rfcn_outputs(model, blob, dim, dim_reduce, spatial_scale)
if model.train:
loss_gradients = fast_rcnn_heads.add_fast_rcnn_losses(model)
return loss_gradients if model.train else None
def _single_gpu_build_func(model):
"""Builds the model on a single GPU. Can be called in a loop over GPUs
with name and device scoping to create a data parallel model."""
blob, dim, spatial_scale = add_conv_body_func(model)
if not model.train:
model.conv_body_net = model.net.Clone('conv_body_net')
rfcn_heads.add_rfcn_outputs(model, blob, dim, dim_reduce, spatial_scale)
if model.train:
loss_gradients = fast_rcnn_heads.add_fast_rcnn_losses(model)
return loss_gradients if model.train else None
def _add_fast_rcnn_head(model, add_roi_box_head_func, blob_in, dim_in,
spatial_scale_in):
"""Add a Fast R-CNN head to the model."""
blob_frcn, dim_frcn = add_roi_box_head_func(model, blob_in, dim_in,
spatial_scale_in)
fast_rcnn_heads.add_fast_rcnn_outputs(model, blob_frcn, dim_frcn)
if model.train:
loss_gradients = fast_rcnn_heads.add_fast_rcnn_losses(model)
else:
loss_gradients = None
return loss_gradients
def _add_fast_rcnn_head(
model, add_roi_box_head_func, blob_in, dim_in, spatial_scale_in
):
"""Add a Fast R-CNN head to the model."""
blob_frcn, dim_frcn = add_roi_box_head_func(
model, blob_in, dim_in, spatial_scale_in
)
fast_rcnn_heads.add_fast_rcnn_outputs(model, blob_frcn, dim_frcn)
if model.train:
loss_gradients = fast_rcnn_heads.add_fast_rcnn_losses(model)
else:
loss_gradients = None
return loss_gradients