fix upper bound

mindspore/ccsrc/minddata/dataset/kernels/image/center_crop_op.cc

@@ -36,6 +36,10 @@ Status CenterCropOp::Compute(const std::shared_ptr<Tensor> &input, std::shared_p
   int32_t top = crop_het_ - input->shape()[0];  // number of pixels to pad (top and bottom)
   int32_t left = crop_wid_ - input->shape()[1];
   std::shared_ptr<Tensor> pad_image;
+
+  CHECK_FAIL_RETURN_UNEXPECTED((top < input->shape()[0] * 10 && left < input->shape()[1] * 10),
+                               "CenterCropOp padding size is too big, it's more than 10 times the original size.");
+
   if (top > 0 && left > 0) {  // padding only
     return Pad(input, output, top / 2 + top % 2, top / 2, left / 2 + left % 2, left / 2, BorderType::kConstant);
   } else if (top > 0) {

mindspore/ccsrc/minddata/dataset/kernels/image/random_crop_op.cc

@@ -56,6 +56,10 @@ Status RandomCropOp::ImagePadding(const std::shared_ptr<Tensor> &input, std::sha
   *t_pad_left = pad_left_;
   *t_pad_right = pad_right_;
 
+  CHECK_FAIL_RETURN_UNEXPECTED(pad_top_ < input->shape()[0] * 3 && pad_bottom_ < input->shape()[0] * 3 &&
+                                 pad_left_ < input->shape()[1] * 3 && pad_right_ < input->shape()[1] * 3,
+                               "RandomCropBBoxOp padding size is too big, it's more than 3 times the original size.");
+
   RETURN_IF_NOT_OK(
     Pad(input, pad_image, pad_top_, pad_bottom_, pad_left_, pad_right_, border_type_, fill_r_, fill_g_, fill_b_));
   CHECK_FAIL_RETURN_UNEXPECTED((*pad_image)->shape().Size() >= 2, "Abnormal shape");

tests/ut/cpp/dataset/center_crop_op_test.cc

@@ -20,17 +20,17 @@
 #include "utils/log_adapter.h"
 
 using namespace mindspore::dataset;
-using mindspore::MsLogLevel::INFO;
-using mindspore::ExceptionType::NoExceptionType;
 using mindspore::LogStream;
+using mindspore::ExceptionType::NoExceptionType;
+using mindspore::MsLogLevel::INFO;
 
 class MindDataTestCenterCropOp : public UT::CVOP::CVOpCommon {
  public:
   MindDataTestCenterCropOp() : CVOpCommon() {}
 };
 
-TEST_F(MindDataTestCenterCropOp, TestOp) {
-  MS_LOG(INFO) << "Doing MindDataTestCenterCropOp::TestOp.";
+TEST_F(MindDataTestCenterCropOp, TestOp1) {
+  MS_LOG(INFO) << "Doing MindDataTestCenterCropOp::TestOp1.";
   std::shared_ptr<Tensor> output_tensor;
   int het = 256;
   int wid = 128;
@@ -42,3 +42,16 @@ TEST_F(MindDataTestCenterCropOp, TestOp) {
   EXPECT_EQ(wid, output_tensor->shape()[1]);
   std::shared_ptr<CVTensor> p = CVTensor::AsCVTensor(output_tensor);
 }
+
+TEST_F(MindDataTestCenterCropOp, TestOp2) {
+  MS_LOG(INFO) << "MindDataTestCenterCropOp::TestOp2. Cap valid crop size at 10 times the input size";
+  std::shared_ptr<Tensor> output_tensor;
+
+  int64_t wid = input_tensor_->shape()[0] * 10 + 1;
+  int64_t het = input_tensor_->shape()[1] * 10 + 1;
+
+  std::unique_ptr<CenterCropOp> op(new CenterCropOp(het, wid));
+  Status s = op->Compute(input_tensor_, &output_tensor);
+  EXPECT_TRUE(s.IsError());
+  ASSERT_TRUE(s.get_code() == StatusCode::kUnexpectedError);
+}

tests/ut/cpp/dataset/random_crop_with_bbox_op_test.cc

@@ -66,6 +66,7 @@ TEST_F(MindDataTestRandomCropWithBBoxOp, TestOp1) {
     }
     GlobalContext::config_manager()->set_seed(current_seed);
   }
+  MS_LOG(INFO) << "testRandomCropWithBBoxOp1 end.";
 }
 
 TEST_F(MindDataTestRandomCropWithBBoxOp, TestOp2) {
@@ -87,5 +88,22 @@ TEST_F(MindDataTestRandomCropWithBBoxOp, TestOp2) {
     EXPECT_EQ(s, Status::OK());
     EXPECT_EQ(4, output_tensor_row_[1]->shape()[1]);  // check for existence of 4 columns
   }
-  MS_LOG(INFO) << "testRandomCropWithBBoxOp end.";
+  MS_LOG(INFO) << "testRandomCropWithBBoxOp2 end.";
 }
+
+TEST_F(MindDataTestRandomCropWithBBoxOp, TestOp3) {
+  MS_LOG(INFO) << "Doing testRandomCropWithBBoxOp3.";
+  // Crop params
+  unsigned int crop_height = 1280;
+  unsigned int crop_width = 1280;
+  std::unique_ptr<RandomCropWithBBoxOp> op(new RandomCropWithBBoxOp(crop_height, crop_width, crop_height * 3 + 1,
+                                                                    crop_height * 3 + 1, crop_width * 3 + 1,
+                                                                    crop_width * 3 + 1, BorderType::kConstant, false));
+
+  for (auto tensor_row_ : images_and_annotations_) {
+    Status s = op->Compute(tensor_row_, &output_tensor_row_);
+    EXPECT_TRUE(s.IsError());
+    ASSERT_TRUE(s.get_code() == StatusCode::kUnexpectedError);
+  }
+  MS_LOG(INFO) << "testRandomCropWithBBoxOp3 end.";
+}
\ No newline at end of file

tests/ut/python/dataset/test_center_crop.py

@@ -138,6 +138,17 @@ def test_crop_grayscale(height=375, width=375):
         assert (c_image.ndim == 3 and c_image.shape[2] == 1)
 
 
+def test_center_crop_errors():
+    """
+    Test that CenterCropOp errors with bad input
+    """
+    try:
+        test_center_crop_op(16777216, 16777216)
+    except RuntimeError as e:
+        assert "Unexpected error. CenterCropOp padding size is too big, it's more than 10 times the original size." in \
+               str(e)
+
+
 if __name__ == "__main__":
     test_center_crop_op(600, 600, plot=True)
     test_center_crop_op(300, 600)

tests/ut/python/dataset/test_random_crop_with_bbox.py

@@ -241,7 +241,7 @@ def test_random_crop_with_bbox_op_bad_c():
     check_bad_bbox(data_voc2, test_op, InvalidBBoxType.WrongShape, "4 features")
 
 
-def test_random_crop_with_bbox_op_negative_padding():
+def test_random_crop_with_bbox_op_bad_padding():
     """
     Test RandomCropWithBBox Op on invalid constructor parameters, expected to raise ValueError
     """
@@ -263,6 +263,20 @@ def test_random_crop_with_bbox_op_negative_padding():
         logger.info("Got an exception in DE: {}".format(str(err)))
         assert "Input padding is not within the required interval of (0 to 2147483647)." in str(err)
 
+    try:
+        test_op = c_vision.RandomCropWithBBox([512, 512], padding=[16777216, 16777216, 16777216, 16777216])
+
+        dataVoc2 = dataVoc2.map(input_columns=["image", "annotation"],
+                                output_columns=["image", "annotation"],
+                                columns_order=["image", "annotation"],
+                                operations=[test_op])
+
+        for _ in dataVoc2.create_dict_iterator():
+            break
+    except RuntimeError as err:
+        logger.info("Got an exception in DE: {}".format(str(err)))
+        assert "RandomCropBBoxOp padding size is too big, it\'s more than 3 times the original size." in str(err)
+
 
 if __name__ == "__main__":
     test_random_crop_with_bbox_op_c(plot_vis=True)
@@ -272,4 +286,4 @@ if __name__ == "__main__":
     test_random_crop_with_bbox_op_edge_c(plot_vis=True)
     test_random_crop_with_bbox_op_invalid_c()
     test_random_crop_with_bbox_op_bad_c()
-    test_random_crop_with_bbox_op_negative_padding()
+    test_random_crop_with_bbox_op_bad_padding()