From 8a05c195f70fc4f5b65a7351a9a5abc9c98ae476 Mon Sep 17 00:00:00 2001 From: lzx1413 Date: Sun, 8 Oct 2017 21:10:25 +0800 Subject: [PATCH 1/2] in python, false should be False --- samples/dnn/mobilenet_ssd_python.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/samples/dnn/mobilenet_ssd_python.py b/samples/dnn/mobilenet_ssd_python.py index cc11aa4bf6..039c244457 100644 --- a/samples/dnn/mobilenet_ssd_python.py +++ b/samples/dnn/mobilenet_ssd_python.py @@ -41,7 +41,7 @@ if __name__ == "__main__": while True: # Capture frame-by-frame ret, frame = cap.read() - blob = cv.dnn.blobFromImage(frame, inScaleFactor, (inWidth, inHeight), meanVal, false) + blob = cv.dnn.blobFromImage(frame, inScaleFactor, (inWidth, inHeight), meanVal, False) net.setInput(blob) detections = net.forward() From 9661d60f74b3e0afac5aa851c83f491f05dfdbc8 Mon Sep 17 00:00:00 2001 From: Alexander Alekhin Date: Sun, 8 Oct 2017 19:17:40 +0300 Subject: [PATCH 2/2] dnn(samples): fix python syntax (false -> False) --- samples/dnn/googlenet_python.py | 2 +- samples/dnn/resnet_ssd_face_python.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/samples/dnn/googlenet_python.py b/samples/dnn/googlenet_python.py index 85d56a992d..0a5caaab4e 100644 --- a/samples/dnn/googlenet_python.py +++ b/samples/dnn/googlenet_python.py @@ -11,7 +11,7 @@ def get_class_list(): with open('synset_words.txt', 'rt') as f: return [x[x.find(" ") + 1:] for x in f] -blob = dnn.blobFromImage(cv2.imread('space_shuttle.jpg'), 1, (224, 224), (104, 117, 123), false) +blob = dnn.blobFromImage(cv2.imread('space_shuttle.jpg'), 1, (224, 224), (104, 117, 123), False) print("Input:", blob.shape, blob.dtype) net = dnn.readNetFromCaffe('bvlc_googlenet.prototxt', 'bvlc_googlenet.caffemodel') diff --git a/samples/dnn/resnet_ssd_face_python.py b/samples/dnn/resnet_ssd_face_python.py index e385a0c7a0..172ee23b67 100644 --- a/samples/dnn/resnet_ssd_face_python.py +++ b/samples/dnn/resnet_ssd_face_python.py @@ -27,7 +27,7 @@ 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)) detections = net.forward() perf_stats = net.getPerfProfile()