Binary data for batch normalization test from Torch

8 years ago · 410d44d67d
parent a6c02af099
commit 410d44d67d
2 changed files with 2 additions and 2 deletions
--- a/modules/dnn/test/test_torch_importer.cpp
+++ b/modules/dnn/test/test_torch_importer.cpp
@ -169,7 +169,7 @@ TEST(Torch_Importer, run_deconv)

 TEST(Torch_Importer, run_batch_norm)
 {
-    runTorchNet("net_batch_norm");
+    runTorchNet("net_batch_norm", DNN_TARGET_CPU, "", false, true);
 }

 TEST(Torch_Importer, net_prelu)
--- a/samples/dnn/resnet_ssd_face_python.py
+++ b/samples/dnn/resnet_ssd_face_python.py
@ -24,7 +24,7 @@ if __name__ == '__main__':
        cols = frame.shape[1]
        rows = frame.shape[0]

-        net.setInput(dnn.blobFromImage(frame, 1.0, (inWidth, inHeight), (104.0, 177.0, 123.0), False))
+        net.setInput(dnn.blobFromImage(frame, 1.0, (inWidth, inHeight), (104.0, 177.0, 123.0), False, False))
        detections = net.forward()

        perf_stats = net.getPerfProfile()