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!7035 Add validation for input image size of affine transformation 

Merge pull request !7035 from jiangzhiwen/fix/check_affine_size
This commit is contained in:
mindspore-ci-bot 2020-10-13 15:03:46 +08:00 committed by Gitee
parent b3d43aa616 197f0cabe0
commit 4a077f6341
3 changed files with 30 additions and 8 deletions
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23
mindspore/ccsrc/minddata/dataset/kernels/image/lite_cv/image_process.cc
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@ -373,6 +373,13 @@ static bool CheckZero(const std::vector<float> &vs) {
return false;
}
static bool CheckZero(const std::vector<size_t> &vs) {
for (int i = 0; i < vs.size(); i++) {
if (vs[i] == 0) return true;
}
return false;
}
static bool CheckMeanAndStd(int channel, const std::vector<float> &mean, const std::vector<float> &std) {
if (mean.size() == 0 && std.size() == 0) {
return false;
@ -638,7 +645,11 @@ std::vector<int> ApplyNms(const std::vector<std::vector<float>> &all_boxes, std:
}
template <typename Pixel_Type>
void ImplementAffine(LiteMat &src, LiteMat &out_img, double M[6], std::vector<size_t> &dsize, Pixel_Type borderValue) {
bool ImplementAffine(LiteMat &src, LiteMat &out_img, double M[6], std::vector<size_t> &dsize, Pixel_Type borderValue) {
if (dsize.size() != 2 || CheckZero(dsize)) {
return false;
}
double IM[6];
for (int i = 0; i < 6; i++) {
IM[i] = M[i];
@ -669,14 +680,16 @@ void ImplementAffine(LiteMat &src, LiteMat &out_img, double M[6], std::vector<si
}
}
}
return true;
}
void Affine(LiteMat &src, LiteMat &out_img, double M[6], std::vector<size_t> dsize, UINT8_C1 borderValue) {
ImplementAffine(src, out_img, M, dsize, borderValue);
bool Affine(LiteMat &src, LiteMat &out_img, double M[6], std::vector<size_t> dsize, UINT8_C1 borderValue) {
return ImplementAffine(src, out_img, M, dsize, borderValue);
}
void Affine(LiteMat &src, LiteMat &out_img, double M[6], std::vector<size_t> dsize, UINT8_C3 borderValue) {
ImplementAffine(src, out_img, M, dsize, borderValue);
bool Affine(LiteMat &src, LiteMat &out_img, double M[6], std::vector<size_t> dsize, UINT8_C3 borderValue) {
return ImplementAffine(src, out_img, M, dsize, borderValue);
}
} // namespace dataset

4
mindspore/ccsrc/minddata/dataset/kernels/image/lite_cv/image_process.h
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@ -71,10 +71,10 @@ bool Pad(const LiteMat &src, LiteMat &dst, int top, int bottom, int left, int ri
uint8_t fill_b_or_gray, uint8_t fill_g, uint8_t fill_r);
/// \brief Apply affine transformation for 1 channel image
void Affine(LiteMat &src, LiteMat &out_img, double M[6], std::vector<size_t> dsize, UINT8_C1 borderValue);
bool Affine(LiteMat &src, LiteMat &out_img, double M[6], std::vector<size_t> dsize, UINT8_C1 borderValue);
/// \brief Apply affine transformation for 3 channel image
void Affine(LiteMat &src, LiteMat &out_img, double M[6], std::vector<size_t> dsize, UINT8_C3 borderValue);
bool Affine(LiteMat &src, LiteMat &out_img, double M[6], std::vector<size_t> dsize, UINT8_C3 borderValue);
/// \brief Get default anchor boxes for Faster R-CNN, SSD, YOLO etc
std::vector<std::vector<float>> GetDefaultBoxes(const BoxesConfig config);

11
tests/ut/cpp/dataset/image_process_test.cc
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@ -271,6 +271,15 @@ TEST_F(MindDataImageProcess, TestApplyNms) {
ASSERT_TRUE(keep[2] == 1);
}
TEST_F(MindDataImageProcess, TestAffineInput) {
LiteMat src(3, 3);
LiteMat dst;
double M[6] = {1};
EXPECT_FALSE(Affine(src, dst, M, {}, UINT8_C1(0)));
EXPECT_FALSE(Affine(src, dst, M, {3}, UINT8_C1(0)));
EXPECT_FALSE(Affine(src, dst, M, {0, 0}, UINT8_C1(0)));
}
TEST_F(MindDataImageProcess, TestAffine) {
// The input matrix
// 0 0 1 0 0
@ -325,7 +334,7 @@ TEST_F(MindDataImageProcess, TestAffine) {
}
std::cout << std::endl;
LiteMat dst;
Affine(src, dst, M, {rows, cols}, UINT8_C1(0));
EXPECT_TRUE(Affine(src, dst, M, {rows, cols}, UINT8_C1(0)));
for (size_t i = 0; i < rows; i++) {
for (size_t j = 0; j < cols; j++) {