提交 11f1baa4 编写于 作者: J jerrywgz

refine code, test=develop

上级 57e5f61e
......@@ -41,14 +41,6 @@ class BoxClipOp : public framework::OperatorWithKernel {
ctx->ShareDim("Input", /*->*/ "Output");
ctx->ShareLoD("Input", /*->*/ "Output");
}
/*
protected:
framework::OpKernelType GetExpectedKernelType(
const framework::ExecutionContext& ctx) const override {
auto data_type = framework::GetDataTypeOfVar(ctx.InputVar("Input"));
return framework::OpKernelType(data_type, platform::CPUPlace());
}
*/
};
class BoxClipOpMaker : public framework::OpProtoAndCheckerMaker {
......@@ -68,11 +60,17 @@ class BoxClipOpMaker : public framework::OpProtoAndCheckerMaker {
AddComment(R"DOC(
This operator clips input boxes to original input images.
The formula is given as follows:
For each input box, The formula is given as follows:
$$height_out = \max(\min(height_loc, im_h), 0)$$
$$width_out = \max(\min(width_loc, im_w), 0)$$
$$xmin = \max(\min(xmin, im_w - 1), 0)$$
$$ymin = \max(\min(ymin, im_h - 1), 0)$$
$$xmax = \max(\min(xmax, im_w - 1), 0)$$
$$ymax = \max(\min(ymax, im_h - 1), 0)$$
where im_w and im_h are computed from ImInfo, the formula is given as follows:
$$im_w = \round(width / im_scale)$$
$$im_h = \round(height / im_scale)$$
)DOC");
}
};
......
......@@ -30,13 +30,13 @@ template <typename T, int BlockSize>
static __global__ void GPUBoxClip(const T *input, const size_t *lod,
const size_t width, const T *im_info,
T *output) {
T im_w = round(im_info[blockIdx.x * ImInfoSize + 1] /
im_info[blockIdx.x * ImInfoSize + 2]);
T im_h = round(im_info[blockIdx.x * ImInfoSize] /
im_info[blockIdx.x * ImInfoSize + 2]);
for (int i = threadIdx.x; i < (lod[blockIdx.x + 1] - lod[blockIdx.x]) * width;
i += BlockSize) {
int idx = lod[blockIdx.x] * width + i;
T im_w = round(im_info[blockIdx.x * ImInfoSize + 1] /
im_info[blockIdx.x * ImInfoSize + 2]);
T im_h = round(im_info[blockIdx.x * ImInfoSize] /
im_info[blockIdx.x * ImInfoSize + 2]);
T im_size = (idx % 2 == 0) ? im_w : im_h;
output[idx] = max(min(input[idx], im_size - 1), T(0.));
}
......@@ -57,9 +57,9 @@ class GPUBoxClipKernel : public framework::OpKernel<T> {
framework::LoD abs_offset_lod = framework::ToAbsOffset(lod);
auto &dev_ctx = context.template device_context<DeviceContext>();
auto stream = dev_ctx.stream();
const size_t num_lod = lod.back().size() - 1;
const size_t batch_size = lod.back().size() - 1;
T *output_data = output->mutable_data<T>(dev_ctx.GetPlace());
GPUBoxClip<T, 512><<<num_lod, 512, 0, stream>>>(
GPUBoxClip<T, 512><<<batch_size, 512, 0, stream>>>(
input->data<T>(), abs_offset_lod[0].CUDAMutableData(dev_ctx.GetPlace()),
bbox_width, im_info->data<T>(), output_data);
}
......
......@@ -1816,26 +1816,35 @@ def generate_proposals(scores,
def box_clip(input, im_info, inplace=False, name=None):
"""
Clip the box into the size given by im_info
The formula is given as follows:
For each input box, The formula is given as follows:
.. code-block:: text
height_out = max(min(height_loc, im_h), 0)
width_out = max(min(width_loc, im_w), 0)
xmin = max(min(xmin, im_w - 1), 0)
ymin = max(min(ymin, im_h - 1), 0)
xmax = max(min(xmax, im_w - 1), 0)
ymax = max(min(ymax, im_h - 1), 0)
where im_w and im_h are computed from im_info:
.. code-block:: text
im_h = round(height / scale)
im_w = round(weight / scale)
Args:
input_box(variable): The input box, the last dimension is 4.
input(variable): The input box, the last dimension is 4.
im_info(variable): The information of image with shape [N, 3] with
layout (height, width, scale). height and width
is the input size and scale is the ratio of input
size and original size.
inplace(bool): Must use :attr:`False` if :attr:`input_box` is used in
inplace(bool): Must use :attr:`False` if :attr:`input` is used in
multiple operators. If this flag is set :attr:`True`,
reuse input :attr:`input_box` to clip, which will
change the value of tensor variable :attr:`input_box`
and might cause errors when :attr:`input_box` is used
reuse input :attr:`input` to clip, which will
change the value of tensor variable :attr:`input`
and might cause errors when :attr:`input` is used
in multiple operators. If :attr:`False`, preserve the
value pf :attr:`input_box` and create a new output
value pf :attr:`input` and create a new output
tensor variable whose data is copied from input x but
cliped.
name (str): The name of this layer. It is optional.
......@@ -1850,16 +1859,13 @@ def box_clip(input, im_info, inplace=False, name=None):
name='data', shape=[8, 4], dtype='float32', lod_level=1)
im_info = fluid.layers.data(name='im_info', shape=[3])
out = fluid.layers.box_clip(
input_box=boxes, im_info=im_info, inplace=True)
input=boxes, im_info=im_info, inplace=True)
"""
helper = LayerHelper("box_clip", **locals())
output = helper.create_variable_for_type_inference(dtype=input.dtype)
output = x if inplace else helper.create_variable_for_type_inference(\
dtype=input.dtype)
inputs = {"Input": input, "ImInfo": im_info}
helper.append_op(
type="box_clip",
inputs=inputs,
attrs={"inplace:": inplace},
outputs={"Output": output})
helper.append_op(type="box_clip", inputs=inputs, outputs={"Output": output})
return output
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