When a pixel is mapped to an infinite location, it is assigned with the default value of zero.

PiperOrigin-RevId: 202208466

2 files changed, 22 insertions, 0 deletions

diff --git a/tensorflow/contrib/image/kernels/image_ops.h b/tensorflow/contrib/image/kernels/image_ops.h
index f1dbd1becc..209aa24548 100644
--- a/tensorflow/contrib/image/kernels/image_ops.h
+++ b/tensorflow/contrib/image/kernels/image_ops.h
@@ -59,6 +59,11 @@ class ProjectiveGenerator {
             ? transforms_.data()
             : &transforms_.data()[transforms_.dimension(1) * coords[0]];
     float projection = transform[6] * output_x + transform[7] * output_y + 1.f;
+    if (projection == 0) {
+      // Return the fill value (0) for infinite coordinates,
+      // which are outside the input image
+      return T(0);
+    }
     const float input_x =
         (transform[0] * output_x + transform[1] * output_y + transform[2]) /
         projection;
diff --git a/tensorflow/contrib/image/python/kernel_tests/image_ops_test.py b/tensorflow/contrib/image/python/kernel_tests/image_ops_test.py
index 88a5c9f079..62a22dcf34 100644
--- a/tensorflow/contrib/image/python/kernel_tests/image_ops_test.py
+++ b/tensorflow/contrib/image/python/kernel_tests/image_ops_test.py
@@ -128,6 +128,23 @@ class ImageOpsTest(test_util.TensorFlowTestCase):
                              [0, 1, 0, 1],
                              [0, 1, 1, 1]])
 
+  def test_extreme_projective_transform(self):
+    for dtype in _DTYPES:
+      with self.test_session():
+        image = constant_op.constant(
+            [[1, 0, 1, 0],
+             [0, 1, 0, 1],
+             [1, 0, 1, 0],
+             [0, 1, 0, 1]], dtype=dtype)
+        transformation = constant_op.constant([1, 0, 0, 0, 1, 0, -1, 0],
+                                              dtypes.float32)
+        image_transformed = image_ops.transform(image, transformation)
+        self.assertAllEqual(image_transformed.eval(),
+                            [[1, 0, 0, 0],
+                             [0, 0, 0, 0],
+                             [1, 0, 0, 0],
+                             [0, 0, 0, 0]])
+
   def test_bilinear(self):
     with self.test_session():
       image = constant_op.constant(