!7997 [Data]fix lite_cv bug for codex_c++ warning

Merge pull request !7997 from xulei/lite_test0905

mindspore/ccsrc/minddata/dataset/kernels/image/lite_cv/image_process.cc

@@ -130,7 +130,7 @@ static void ResizeBilinear3C(const unsigned char *src, int src_width, int src_he
     for (int k = 0; k < dst_width * 3; k++) {
       int16_t t0 = (int16_t)((y_weight[0] * (int16_t)(*row0_ptr0++)) >> 16);
       int16_t t1 = (int16_t)((y_weight[1] * (int16_t)(*row1_ptr1++)) >> 16);
-      *dst_ptr++ = (unsigned char)((t0 + t1 + 2) >> 2);
+      *dst_ptr++ = static_cast<unsigned char>((t0 + t1 + 2) >> 2);
     }
     y_weight += 2;
   }
@@ -202,7 +202,7 @@ static void ResizeBilinear1C(const unsigned char *src, int src_width, int src_he
     for (int k = 0; k < dst_width; k++) {
       int16_t t0 = (int16_t)((y_weight[0] * (int16_t)(*row0_ptr0++)) >> 16);
       int16_t t1 = (int16_t)((y_weight[1] * (int16_t)(*row1_ptr1++)) >> 16);
-      *dst_ptr++ = (unsigned char)((t0 + t1 + 2) >> 2);
+      *dst_ptr++ = static_cast<unsigned char>((t0 + t1 + 2) >> 2);
     }
 
     y_weight += 2;
@@ -873,7 +873,8 @@ std::vector<int> ApplyNms(const std::vector<std::vector<float>> &all_boxes, std:
 }
 
 template <typename Pixel_Type>
-bool ImplementAffine(LiteMat &src, LiteMat &out_img, double M[6], std::vector<size_t> &dsize, Pixel_Type borderValue) {
+bool ImplementAffine(LiteMat &src, LiteMat &out_img, const double M[6], std::vector<size_t> &dsize,
+                     Pixel_Type borderValue) {
   if (dsize.size() != 2 || CheckZero(dsize)) {
     return false;
   }
@@ -912,11 +913,11 @@ bool ImplementAffine(LiteMat &src, LiteMat &out_img, double M[6], std::vector<si
   return true;
 }
 
-bool Affine(LiteMat &src, LiteMat &out_img, double M[6], std::vector<size_t> dsize, UINT8_C1 borderValue) {
+bool Affine(LiteMat &src, LiteMat &out_img, const double M[6], std::vector<size_t> dsize, UINT8_C1 borderValue) {
   return 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) {
+bool Affine(LiteMat &src, LiteMat &out_img, const double M[6], std::vector<size_t> dsize, UINT8_C3 borderValue) {
   return ImplementAffine(src, out_img, M, dsize, borderValue);
 }
 

mindspore/ccsrc/minddata/dataset/kernels/image/lite_cv/image_process.h

@@ -91,10 +91,10 @@ bool Split(const LiteMat &src, std::vector<LiteMat> &mv);
 bool Merge(const std::vector<LiteMat> &mv, LiteMat &dst);
 
 /// \brief Apply affine transformation for 1 channel image
-bool Affine(LiteMat &src, LiteMat &out_img, double M[6], std::vector<size_t> dsize, UINT8_C1 borderValue);
+bool Affine(LiteMat &src, LiteMat &out_img, const double M[6], std::vector<size_t> dsize, UINT8_C1 borderValue);
 
 /// \brief Apply affine transformation for 3 channel image
-bool Affine(LiteMat &src, LiteMat &out_img, double M[6], std::vector<size_t> dsize, UINT8_C3 borderValue);
+bool Affine(LiteMat &src, LiteMat &out_img, const 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);

mindspore/ccsrc/minddata/dataset/kernels/image/lite_cv/lite_mat.cc

@@ -26,6 +26,7 @@ LiteMat::LiteMat() {
   channel_ = 0;
   c_step_ = 0;
   dims_ = 0;
+  size_ = 0;
   data_type_ = LDataType::UINT8;
   ref_count_ = 0;
 }
@@ -199,7 +200,10 @@ void *LiteMat::AlignMalloc(unsigned int size) {
   return nullptr;
 }
 
-void LiteMat::AlignFree(void *ptr) { (void)free(reinterpret_cast<void **>(ptr)[-1]); }
+void LiteMat::AlignFree(void *ptr) {
+  (void)free(reinterpret_cast<void **>(ptr)[-1]);
+  ptr = nullptr;
+}
 
 inline void LiteMat::InitElemSize(LDataType data_type) { elem_size_ = data_type.SizeInBytes(); }