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@ -79,10 +79,7 @@ class BoxCoderKernel : public framework::OpKernel<T> {
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output[offset + 3] =
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std::log(std::fabs(target_box_height / prior_box_height));
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if (prior_box_var) {
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int prior_var_offset = 0;
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if (prior_box_var->dims().size() == 2) {
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prior_var_offset = j * len;
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}
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int prior_var_offset = j * len;
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output[offset] /= prior_box_var_data[prior_var_offset];
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output[offset + 1] /= prior_box_var_data[prior_var_offset + 1];
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output[offset + 2] /= prior_box_var_data[prior_var_offset + 2];
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@ -95,11 +92,12 @@ class BoxCoderKernel : public framework::OpKernel<T> {
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}
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}
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}
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template <int axis, int var_size>
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void DecodeCenterSize(const framework::Tensor* target_box,
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const framework::Tensor* prior_box,
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const framework::Tensor* prior_box_var,
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const bool normalized, const int axis,
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const std::vector<float> variance, T* output) const {
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const bool normalized, std::vector<float> variance,
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T* output) const {
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int64_t row = target_box->dims()[0];
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int64_t col = target_box->dims()[1];
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int64_t len = target_box->dims()[2];
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@ -107,19 +105,17 @@ class BoxCoderKernel : public framework::OpKernel<T> {
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auto* target_box_data = target_box->data<T>();
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auto* prior_box_data = prior_box->data<T>();
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const T* prior_box_var_data = nullptr;
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if (prior_box_var) prior_box_var_data = prior_box_var->data<T>();
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if (var_size == 2) prior_box_var_data = prior_box_var->data<T>();
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int prior_box_offset = 0;
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T var_data[4] = {1., 1., 1., 1.};
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T* var_ptr = var_data;
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#ifdef PADDLE_WITH_MKLML
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#pragma omp parallel for collapse(2)
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#endif
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for (int64_t i = 0; i < row; ++i) {
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for (int64_t j = 0; j < col; ++j) {
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size_t offset = i * col * len + j * len;
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if (axis == 0) {
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prior_box_offset = j * len;
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} else if (axis == 1) {
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prior_box_offset = i * len;
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}
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prior_box_offset = axis == 0 ? j * len : i * len;
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T prior_box_width = prior_box_data[prior_box_offset + 2] -
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prior_box_data[prior_box_offset] +
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(normalized == false);
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@ -133,26 +129,18 @@ class BoxCoderKernel : public framework::OpKernel<T> {
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T target_box_center_x = 0, target_box_center_y = 0;
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T target_box_width = 0, target_box_height = 0;
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T box_var_x = T(1), box_var_y = T(1);
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T box_var_w = T(1), box_var_h = T(1);
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if (prior_box_var) {
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int prior_var_offset = 0;
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if (prior_box_var->dims().size() == 2) {
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if (axis == 0)
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prior_var_offset = j * len;
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else if (axis == 1)
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prior_var_offset = i * len;
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}
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box_var_x = prior_box_var_data[prior_var_offset];
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box_var_y = prior_box_var_data[prior_var_offset + 1];
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box_var_w = prior_box_var_data[prior_var_offset + 2];
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box_var_h = prior_box_var_data[prior_var_offset + 3];
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} else if (!(variance.empty())) {
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box_var_x = static_cast<T>(variance[0]);
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box_var_y = static_cast<T>(variance[1]);
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box_var_w = static_cast<T>(variance[2]);
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box_var_h = static_cast<T>(variance[3]);
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int prior_var_offset = axis == 0 ? j * len : i * len;
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if (var_size == 2) {
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std::memcpy(var_ptr, prior_box_var_data + prior_var_offset,
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4 * sizeof(T));
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} else if (var_size == 1) {
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var_ptr = reinterpret_cast<T*>(variance.data());
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}
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T box_var_x = *var_ptr;
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T box_var_y = *(var_ptr + 1);
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T box_var_w = *(var_ptr + 2);
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T box_var_h = *(var_ptr + 3);
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target_box_center_x =
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box_var_x * target_box_data[offset] * prior_box_width +
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prior_box_center_x;
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@ -211,8 +199,31 @@ class BoxCoderKernel : public framework::OpKernel<T> {
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EncodeCenterSize(target_box, prior_box, prior_box_var, normalized,
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variance, output);
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} else if (code_type == BoxCodeType::kDecodeCenterSize) {
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DecodeCenterSize(target_box, prior_box, prior_box_var, normalized, axis,
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variance, output);
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if (prior_box_var) {
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if (axis == 0) {
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DecodeCenterSize<0, 2>(target_box, prior_box, prior_box_var,
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normalized, variance, output);
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} else {
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DecodeCenterSize<1, 2>(target_box, prior_box, prior_box_var,
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normalized, variance, output);
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}
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} else if (!(variance.empty())) {
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if (axis == 0) {
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DecodeCenterSize<0, 1>(target_box, prior_box, prior_box_var,
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normalized, variance, output);
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} else {
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DecodeCenterSize<1, 1>(target_box, prior_box, prior_box_var,
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normalized, variance, output);
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}
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} else {
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if (axis == 0) {
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DecodeCenterSize<0, 0>(target_box, prior_box, prior_box_var,
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normalized, variance, output);
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} else {
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DecodeCenterSize<1, 0>(target_box, prior_box, prior_box_var,
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normalized, variance, output);
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}
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}
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}
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}
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};
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xuezhong
6 years ago