diff --git a/mediapipe/calculators/tensor/image_to_tensor_converter_opencv.cc b/mediapipe/calculators/tensor/image_to_tensor_converter_opencv.cc
index 76e46f99..95e38f89 100644
--- a/mediapipe/calculators/tensor/image_to_tensor_converter_opencv.cc
+++ b/mediapipe/calculators/tensor/image_to_tensor_converter_opencv.cc
@@ -76,31 +76,49 @@ class OpenCvProcessor : public ImageToTensorConverter {
       return InvalidArgumentError(absl::StrCat(
           "Unsupported format: ", static_cast<uint32_t>(input.image_format())));
     }
-    // TODO: Remove the check once tensor_buffer_offset > 0 is
-    // supported.
-    RET_CHECK_EQ(tensor_buffer_offset, 0)
-        << "The non-zero tensor_buffer_offset input is not supported yet.";
+
+    RET_CHECK_GE(tensor_buffer_offset, 0)
+        << "The input tensor_buffer_offset needs to be non-negative.";
     const auto& output_shape = output_tensor.shape();
     MP_RETURN_IF_ERROR(ValidateTensorShape(output_shape));
 
     const int output_height = output_shape.dims[1];
     const int output_width = output_shape.dims[2];
     const int output_channels = output_shape.dims[3];
+    const int num_elements_per_img =
+        output_height * output_width * output_channels;
     auto buffer_view = output_tensor.GetCpuWriteView();
     cv::Mat dst;
     const int dst_data_type = output_channels == 1 ? mat_gray_type_ : mat_type_;
     switch (tensor_type_) {
       case Tensor::ElementType::kInt8:
-        dst = cv::Mat(output_height, output_width, dst_data_type,
-                      buffer_view.buffer<int8>());
+        RET_CHECK_GE(output_shape.num_elements(),
+                     tensor_buffer_offset / sizeof(int8) + num_elements_per_img)
+            << "The buffer offset + the input image size is larger than the "
+               "allocated tensor buffer.";
+        dst = cv::Mat(
+            output_height, output_width, dst_data_type,
+            buffer_view.buffer<int8>() + tensor_buffer_offset / sizeof(int8));
         break;
       case Tensor::ElementType::kFloat32:
-        dst = cv::Mat(output_height, output_width, dst_data_type,
-                      buffer_view.buffer<float>());
+        RET_CHECK_GE(
+            output_shape.num_elements(),
+            tensor_buffer_offset / sizeof(float) + num_elements_per_img)
+            << "The buffer offset + the input image size is larger than the "
+               "allocated tensor buffer.";
+        dst = cv::Mat(
+            output_height, output_width, dst_data_type,
+            buffer_view.buffer<float>() + tensor_buffer_offset / sizeof(float));
         break;
       case Tensor::ElementType::kUInt8:
-        dst = cv::Mat(output_height, output_width, dst_data_type,
-                      buffer_view.buffer<uint8>());
+        RET_CHECK_GE(
+            output_shape.num_elements(),
+            tensor_buffer_offset / sizeof(uint8) + num_elements_per_img)
+            << "The buffer offset + the input image size is larger than the "
+               "allocated tensor buffer.";
+        dst = cv::Mat(
+            output_height, output_width, dst_data_type,
+            buffer_view.buffer<uint8>() + tensor_buffer_offset / sizeof(uint8));
         break;
       default:
         return InvalidArgumentError(
@@ -153,9 +171,8 @@ class OpenCvProcessor : public ImageToTensorConverter {
   absl::Status ValidateTensorShape(const Tensor::Shape& output_shape) {
     RET_CHECK_EQ(output_shape.dims.size(), 4)
         << "Wrong output dims size: " << output_shape.dims.size();
-    RET_CHECK_EQ(output_shape.dims[0], 1)
-        << "Handling batch dimension not equal to 1 is not implemented in this "
-           "converter.";
+    RET_CHECK_GE(output_shape.dims[0], 1)
+        << "The batch dimension needs to be equal or larger than 1.";
     RET_CHECK(output_shape.dims[3] == 3 || output_shape.dims[3] == 1)
         << "Wrong output channel: " << output_shape.dims[3];
     return absl::OkStatus();