From 2027a3399076b099930fc8eb2721d8c028fdabc0 Mon Sep 17 00:00:00 2001
From: SamareshSingh <97642706+ssam18@users.noreply.github.com>
Date: Mon, 30 Mar 2026 02:06:54 -0500
Subject: [PATCH] Merge pull request #28724 from
 ssam18:fix/resize-ngraph-two-inputs-28707

dnn: fix Resize initNgraph for two-input case #28724

## Summary

Fixes the issue #28707

When a Resize/Upsample layer has two inputs, the data tensor and a reference tensor whose **shape** defines the output spatial size, the OpenVINO/NGRAPH backend's `initNgraph()` was ignoring `nodes[1]` entirely and relying solely on the `outHeight`/`outWidth` member variables.

These variables are set by `finalize()` from the pre-computed output blob dimensions. However, when the output shape is determined dynamically at runtime from the second input, `finalize()` sets them from the live tensor, but the OpenVINO backend calls `initNgraph()` to build a static compiled graph. If the member variables are 0 at that point, the compiled `Interpolate` node gets hardcoded with `{0, 0}` output dimensions, causing CV_Assert failure: {N,C,0,0} vs {N,C,H2,W2}
---
 modules/dnn/src/layers/resize_layer.cpp | 31 ++++++++++++++++++-------
 1 file changed, 22 insertions(+), 9 deletions(-)

diff --git a/modules/dnn/src/layers/resize_layer.cpp b/modules/dnn/src/layers/resize_layer.cpp
index 3d904db67a..89732fbe85 100644
--- a/modules/dnn/src/layers/resize_layer.cpp
+++ b/modules/dnn/src/layers/resize_layer.cpp
@@ -400,17 +400,30 @@ public:
 
         attrs.nearest_mode = ov::op::v4::Interpolate::NearestMode::ROUND_PREFER_FLOOR;
 
-
-        std::vector<int64_t> shape = {outHeight, outWidth};
-        auto out_shape = std::make_shared<ov::op::v0::Constant>(ov::element::i64, ov::Shape{2}, shape.data());
-
-        auto& input_shape = ieInpNode.get_shape();
-        CV_Assert_N(input_shape[2] != 0, input_shape[3] != 0);
-        std::vector<float> scales = {static_cast<float>(outHeight) / input_shape[2], static_cast<float>(outWidth) / input_shape[3]};
-        auto scales_shape = std::make_shared<ov::op::v0::Constant>(ov::element::f32, ov::Shape{2}, scales.data());
+        std::shared_ptr<ov::Node> out_shape_node;
+        std::shared_ptr<ov::Node> scales_node;
+        if (nodes.size() == 2)
+        {
+            auto& ieRefNode = nodes[1].dynamicCast<InfEngineNgraphNode>()->node;
+            auto ref_shape = std::make_shared<ov::op::v3::ShapeOf>(ieRefNode, ov::element::i64);
+            auto hw_indices = std::make_shared<ov::op::v0::Constant>(ov::element::i64, ov::Shape{2}, std::vector<int64_t>{2, 3});
+            auto gather_axis = std::make_shared<ov::op::v0::Constant>(ov::element::i64, ov::Shape{}, 0LL);
+            out_shape_node = std::make_shared<ov::op::v8::Gather>(ref_shape, hw_indices, gather_axis);
+            std::vector<float> dummy_scales = {1.0f, 1.0f};
+            scales_node = std::make_shared<ov::op::v0::Constant>(ov::element::f32, ov::Shape{2}, dummy_scales.data());
+        }
+        else
+        {
+            std::vector<int64_t> shape = {outHeight, outWidth};
+            out_shape_node = std::make_shared<ov::op::v0::Constant>(ov::element::i64, ov::Shape{2}, shape.data());
+            auto& input_shape = ieInpNode.get_shape();
+            CV_Assert_N(input_shape[2] != 0, input_shape[3] != 0);
+            std::vector<float> scales = {static_cast<float>(outHeight) / input_shape[2],static_cast<float>(outWidth) / input_shape[3]};
+            scales_node = std::make_shared<ov::op::v0::Constant>(ov::element::f32, ov::Shape{2}, scales.data());
+        }
 
         auto axes = std::make_shared<ov::op::v0::Constant>(ov::element::i64, ov::Shape{2}, std::vector<int64_t>{2, 3});
-        auto interp = std::make_shared<ov::op::v4::Interpolate>(ieInpNode, out_shape, scales_shape, axes, attrs);
+        auto interp = std::make_shared<ov::op::v4::Interpolate>(ieInpNode, out_shape_node, scales_node, axes, attrs);
         return Ptr<BackendNode>(new InfEngineNgraphNode(interp));
     }
 #endif  // HAVE_DNN_NGRAPH