!30429 BUG][MD][FUNC]RandomAutoContrast

Merge pull request !30429 from yangwm/autocontrast

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

@@ -13,10 +13,10 @@
  * See the License for the specific language governing permissions and
  * limitations under the License.
  */
+
 #include "minddata/dataset/kernels/image/random_auto_contrast_op.h"
 
 #include "minddata/dataset/kernels/image/image_utils.h"
-#include "minddata/dataset/util/status.h"
 
 namespace mindspore {
 namespace dataset {
@@ -26,6 +26,20 @@ const float RandomAutoContrastOp::kDefProbability = 0.5;
 
 Status RandomAutoContrastOp::Compute(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *output) {
   IO_CHECK(input, output);
+  // Check input
+  if (input->Rank() != DEFAULT_IMAGE_RANK) {
+    RETURN_STATUS_UNEXPECTED("RandomAutoContrast: image shape is not <H,W,C>, got rank: " +
+                             std::to_string(input->Rank()));
+  }
+  if (input->shape()[CHANNEL_INDEX] != DEFAULT_IMAGE_CHANNELS) {
+    RETURN_STATUS_UNEXPECTED(
+      "RandomAutoContrast: image shape is incorrect, expected num of channels is 3, "
+      "but got:" +
+      std::to_string(input->shape()[CHANNEL_INDEX]));
+  }
+  CHECK_FAIL_RETURN_UNEXPECTED(input->type().AsCVType() != kCVInvalidType,
+                               "RandomAutoContrast: Cannot convert from OpenCV type, unknown CV type. Currently "
+                               "supported data type: [int8, uint8, int16, uint16, int32, float16, float32, float64].");
   if (distribution_(rnd_)) {
     return AutoContrast(input, output, cutoff_, ignore_);
   }

tests/ut/python/dataset/test_random_auto_contrast.py

@@ -177,6 +177,71 @@ def test_random_auto_contrast_invalid_cutoff():
         assert "Input cutoff is not within the required interval of [0, 50)." in str(error)
 
 
+def test_random_auto_contrast_one_channel():
+    """
+    Feature: RandomAutoContrast
+    Description: test with one channel images
+    Expectation: raise errors as expected
+    """
+    logger.info("test_random_auto_contrast_one_channel")
+
+    c_op = c_vision.RandomAutoContrast()
+
+    try:
+        data_set = ds.ImageFolderDataset(dataset_dir=data_dir, shuffle=False)
+        data_set = data_set.map(operations=[c_vision.Decode(), c_vision.Resize((224, 224)),
+                                            lambda img: np.array(img[:, :, 0])], input_columns=["image"])
+
+        data_set = data_set.map(operations=c_op, input_columns="image")
+
+    except RuntimeError as e:
+        logger.info("Got an exception in DE: {}".format(str(e)))
+        assert "image shape is incorrect, expected num of channels is 3." in str(e)
+
+
+def test_random_auto_contrast_four_dim():
+    """
+    Feature: RandomAutoContrast
+    Description: test with four dimension images
+    Expectation: raise errors as expected
+    """
+    logger.info("test_random_auto_contrast_four_dim")
+
+    c_op = c_vision.RandomAutoContrast()
+
+    try:
+        data_set = ds.ImageFolderDataset(dataset_dir=data_dir, shuffle=False)
+        data_set = data_set.map(operations=[c_vision.Decode(), c_vision.Resize((224, 224)),
+                                            lambda img: np.array(img[2, 200, 10, 32])], input_columns=["image"])
+
+        data_set = data_set.map(operations=c_op, input_columns="image")
+
+    except ValueError as e:
+        logger.info("Got an exception in DE: {}".format(str(e)))
+        assert "image shape is not <H,W,C>" in str(e)
+
+
+def test_random_auto_contrast_invalid_input():
+    """
+    Feature: RandomAutoContrast
+    Description: test with images in uint32 type
+    Expectation: raise errors as expected
+    """
+    logger.info("test_random_invert_invalid_input")
+
+    c_op = c_vision.RandomAutoContrast()
+
+    try:
+        data_set = ds.ImageFolderDataset(dataset_dir=data_dir, shuffle=False)
+        data_set = data_set.map(operations=[c_vision.Decode(), c_vision.Resize((224, 224)),
+                                            lambda img: np.array(img[2, 32, 3], dtype=uint32)], input_columns=["image"])
+        data_set = data_set.map(operations=c_op, input_columns="image")
+
+    except TypeError as e:
+        logger.info("Got an exception in DE: {}".format(str(e)))
+        assert "Cannot convert from OpenCV type, unknown CV type" in str(e)
+
+
 if __name__ == "__main__":
     test_random_auto_contrast_pipeline(plot=True)
     test_random_auto_contrast_eager()
@@ -184,3 +249,6 @@ if __name__ == "__main__":
     test_random_auto_contrast_invalid_prob()
     test_random_auto_contrast_invalid_ignore()
     test_random_auto_contrast_invalid_cutoff()
+    test_random_auto_contrast_one_channel()
+    test_random_auto_contrast_four_dim()
+    test_random_auto_contrast_invalid_input()