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Merge pull request #26394 from alexlyulkov:al/new-engine-tf-parser

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Modified tensorflow parser for the new dnn engine #26394

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [x] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [x] The feature is well documented and sample code can be built with the project CMake
This commit is contained in:
alexlyulkov
2024-11-27 09:15:20 +03:00
committed by GitHub
parent b9914065e8
commit 3672a14b42
14 changed files with 491 additions and 408 deletions
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modules/dnn/misc/java/test/DnnTensorFlowTest.java
+10 -15
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@@ -74,20 +74,15 @@ public class DnnTensorFlowTest extends OpenCVTestCase {
}
public void testGetLayer() {
List<String> layernames = net.getLayerNames();
assertFalse("Test net returned no layers!", layernames.isEmpty());
String testLayerName = layernames.get(0);
DictValue layerId = new DictValue(testLayerName);
assertEquals("DictValue did not return the string, which was used in constructor!", testLayerName, layerId.getStringValue());
Layer layer = net.getLayer(layerId);
assertEquals("Layer name does not match the expected value!", testLayerName, layer.get_name());
List<String> layerNames = net.getLayerNames();
assertFalse("Test net returned no layers!", layerNames.isEmpty());
int layerId = 0;
for (String layerName: layerNames) {
Layer layer = net.getLayer(layerId);
assertEquals("Layer name does not match the expected value!", layerName, layer.get_name());
layerId++;
}
}
public void checkInceptionNet(Net net)
@@ -98,12 +93,12 @@ public class DnnTensorFlowTest extends OpenCVTestCase {
Mat inputBlob = Dnn.blobFromImage(image, 1.0, new Size(224, 224), new Scalar(0), true, true);
assertNotNull("Converting image to blob failed!", inputBlob);
net.setInput(inputBlob, "input");
net.setInput(inputBlob, "");
Mat result = new Mat();
try {
net.setPreferableBackend(Dnn.DNN_BACKEND_OPENCV);
result = net.forward("softmax2");
result = net.forward("");
}
catch (Exception e) {
fail("DNN forward failed: " + e.getMessage());