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opencv · Apr 9, 2024 · b3e4e58 · b3e4e58
1 parent 5a22a1f
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Showing 2 changed files with 38 additions and 11 deletions.
diff --git a/modules/dnn/src/layers/padding_layer.cpp b/modules/dnn/src/layers/padding_layer.cpp
@@ -62,6 +62,12 @@ class PaddingLayerImpl CV_FINAL : public PaddingLayer
         const MatShape& inpShape = inputs[0];
         std::cout << "inpShape.size() = " << inpShape << std::endl;
         // std::cout << "paddings: " << paddings << std::endl;
+        if (inpShape.empty()){
+            std::cout << "in the new branch" << std::endl;
+            outputs.resize(1, MatShape(1, paddings.size() + 1));
+            std::cout << "outputs: " << outputs[0] << std::endl;
+            return false;
+        }
         CV_Assert(inpShape.size() >= paddings.size());
 
         CV_Assert(inputDims == -1 || inpShape.size() == inputDims || inpShape.size() > paddings.size());

diff --git a/modules/dnn/test/test_layers_1d.cpp b/modules/dnn/test/test_layers_1d.cpp
@@ -513,32 +513,53 @@ INSTANTIATE_TEST_CASE_P(/*nothing*/,  Layer_Permute_Test,
             std::vector<int>{4, 1}
 ));
 
-TEST(Layer_Padding_Test, Accuracy){
+typedef testing::TestWithParam<tuple<std::vector<int>>> Layer_Padding_Test;
+TEST_P(Layer_Padding_Test, Accuracy_01D){
+
+    std::vector<int> input_shape = get<0>(GetParam());
+    float pad_value = 10;
+
     LayerParams lp;
     lp.type = "Padding";
     lp.name = "PaddingLayer";
-    // std::vector<int>paddings = {1};
-    // lp.set("paddings", DictValue::arrayInt(paddings.begin(), paddings.size()));
     std::vector<int> paddings = {1, 1}; // Pad before and pad after for one dimension
     lp.set("paddings", DictValue::arrayInt(paddings.data(), paddings.size()));
+    lp.set("value", pad_value);
+    lp.set("input_dims", (input_shape.size() == 1) ? -1 : 0);
     Ptr<PaddingLayer> layer = PaddingLayer::create(lp);
 
-    std::vector<int> input_shape = {0};
-    std::vector<int> output_shape = {1};
-
-    cv::Mat input(0, input_shape.data(), CV_32F, 1.0);
-    // cv::randn(input, 0.0, 1.0);
+    cv::Mat input(input_shape.size(), input_shape.data(), CV_32F);
+    cv::randn(input, 0.0, 1.0);
 
-    float data[] = {0, 1, 0};
-    cv::Mat output_ref(output_shape, CV_32F, data);
+    // create a refence
+    cv::Mat output_ref;
+    cv::copyMakeBorder(input, output_ref, 0, 0, 1, 1, 0, (Scalar) pad_value);
+    if (input_shape.size() == 0 || input_shape.size() == 1){
+        std::cout << "shape output_ref: " << shape(output_ref) << std::endl;
+        std::cout << "total: " << output_ref.total() << std::endl;
+        // output_ref = output_ref.reshape(1, {3});
+        output_ref.dims = 1;
+    }
+    std::cout << "input: " << input << std::endl;
+    std::cout << "output_ref: " << output_ref << std::endl;
+    std::cout << "shape output_ref: " << shape(output_ref) << std::endl;
 
     std::vector<Mat> inputs{input};
     std::vector<Mat> outputs;
 
     runLayer(layer, inputs, outputs);
+    std::cout << "output[0]: " << outputs[0] << std::endl;
+    std::cout << "output[0] shape: " << shape(outputs[0]) << std::endl;
+    ASSERT_EQ(outputs.size(), 1);
     ASSERT_EQ(shape(output_ref), shape(outputs[0]));
     normAssert(output_ref, outputs[0]);
 }
-
+INSTANTIATE_TEST_CASE_P(/*nothing*/,  Layer_Padding_Test,
+/*input blob shape*/ testing::Values(
+            std::vector<int>{},
+            std::vector<int>{1},
+            std::vector<int>{1, 4},
+            std::vector<int>{4, 1}
+));
 
 }}