Add test data for layers

modules/dnn/test/test_layers.cpp

@@ -15,21 +15,24 @@ static String _tf(TString filename)
     return (getOpenCVExtraDir() + "/dnn/layers/") + filename;
 }
 
-static void testLayer(String basename, bool useCaffeModel = false)
+static void testLayer(String basename, bool useCaffeModel = false, bool useCommonInputBlob = true)
 {
-    Blob inp = blobFromNPY(_tf("blob.npy"));
-    Blob ref = blobFromNPY(_tf(basename + ".npy"));
+    String prototxt = _tf(basename + ".prototxt");
+    String caffemodel = _tf(basename + ".caffemodel");
 
-    String prototxt = basename + ".prototxt";
-    String caffemodel = basename + ".caffemodel";
+    String inpfile = (useCommonInputBlob) ? _tf("blob.npy") : _tf(basename + ".input.npy");
+    String outfile = _tf(basename + ".npy");
 
     Net net;
     {
-        Ptr<Importer> importer = createCaffeImporter(_tf(prototxt), (useCaffeModel) ? _tf(caffemodel) : String());
+        Ptr<Importer> importer = createCaffeImporter(prototxt, (useCaffeModel) ? caffemodel : String());
         ASSERT_TRUE(importer != NULL);
         importer->populateNet(net);
     }
 
+    Blob inp = blobFromNPY(inpfile);
+    Blob ref = blobFromNPY(outfile);
+
     net.setBlob(".input", inp);
     net.forward();
     Blob out = net.getBlob("output");
@@ -85,7 +88,7 @@ TEST(Layer_Test_Pooling_ave, Accuracy)
 
 TEST(Layer_Test_DeConvolution, Accuracy)
 {
-     testLayer("layer_deconvolution", true);
+     testLayer("layer_deconvolution", true, false);
 }
 
 TEST(Layer_Test_MVN, Accuracy)

modules/dnn/testdata/dnn/layers/layer_deconvolution.prototxt

@@ -2,9 +2,9 @@ name: "test_Convolution"
 input: "input"
 
 input_dim: 2
-input_dim: 6
-input_dim: 75
-input_dim: 113
+input_dim: 12
+input_dim: 36
+input_dim: 37
 
 layer {
   type: "Deconvolution"

modules/dnn/testdata/dnn/layers/layer_softmax.prototxt

@@ -2,7 +2,7 @@ name: "test_Softmax"
 input: "input"
 
 input_dim: 2
-input_dim: 5
+input_dim: 6
 input_dim: 75
 input_dim: 113
 

modules/dnn/testdata/dnn/layers/run.py

@@ -7,13 +7,13 @@ sys.path.insert(0, CAFFE_ROOT + 'python')
 
 import numpy as np
 import caffe
-import cv2
+#import cv2
 
 def get_cafe_output(inp_blob, proto_name, caffemodel_name):
     caffe.set_mode_cpu()
     net = caffe.Net(proto_name, caffe.TEST)
 
-    net.blobs['input'].reshape(*inp_blob.shape)
+    #net.blobs['input'].reshape(*inp_blob.shape)
     net.blobs['input'].data[...] = inp_blob
 
     net.forward()
@@ -28,16 +28,17 @@ def get_cafe_output(inp_blob, proto_name, caffemodel_name):
 if __name__ == '__main__':
     proto_filenames = glob.glob("layer_*.prototxt")
 
-    inp_blob = np.load('blob.npy')
-    print inp_blob.shape
-
     for proto_filename in proto_filenames:
         proto_filename = os.path.basename(proto_filename)
         proto_basename = os.path.splitext(proto_filename)[0]
         cfmod_basename = proto_basename + ".caffemodel"
         npy_filename = proto_basename + ".npy"
 
-        print cfmod_basename
+        inp_blob_name = proto_basename + ".input.npy"
+        inp_blob = np.load(inp_blob_name) if os.path.exists(inp_blob_name) else np.load('blob.npy')
+
+        print "\nGenerate data for:"
+        print cfmod_basename, inp_blob.shape
 
         out_blob = get_cafe_output(inp_blob, proto_filename, cfmod_basename)
         print out_blob.shape