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2019-08-20 08:45:24 -0600	commented question	Cross-compile for ARM Somethink like /usr/bin/arm-linux-gnueabihf-pkg-config --cflags harfbuzz does seem to work however and returns -I/usr/in
2019-08-20 08:34:57 -0600	commented question	Cannot use Tensorflow model with batch normalization I think there is already an issue on the topic here. Have you frozen the graph_def file like described in the comment?
2019-08-20 08:29:18 -0600	commented question	Cross-compile for ARM I think the reason for the error might be some issue with the pkg-config, have a lot of plugin needed to handle lto obje
2019-08-20 08:28:38 -0600	commented question	Cross-compile for ARM I think the reason for the problem might be some problem with the pkg-config, have a lot of plugin needed to handle lto
2019-08-20 08:28:14 -0600	commented question	Cross-compile for ARM I think the reason for the problem might be some problem with the pkg-config, have a lot of plugin needed to handle lto
2019-08-20 06:47:29 -0600	commented question	Cross-compile for ARM So zlib is installed but apparently it is still not found by the linker during make. So I tough adding the extra liker f
2019-08-19 17:02:18 -0600	edited question	Cross-compile for ARM Cross-compile for ARM Hi, I'm trying to cross-build OpenCV for ARM using a Docker image, but I'm getting linking error
2019-08-19 17:02:01 -0600	edited question	Cross-compile for ARM Cross-compile for ARM Hi, I'm trying to cross-build OpenCV for ARM using a Docker image, but I'm getting linking error
2019-08-19 04:08:56 -0600	asked a question	Build Raspbain Segmentation fault Build Raspbain Segmentation fault OpenCV build fails with Segmentation fault. Does anyone has an idea why? CMake Comman
2019-08-14 10:35:07 -0600	asked a question	Cross-compile for ARM Cross-compile for ARM Hi, I'm trying to cross-build OpenCV for ARM using a Docker image, but I'm getting linking error
2019-07-28 07:51:45 -0600	edited answer	How can i load a onnx with opencv? @vealocia did you verify the model: import onnx onnx_model = onnx.load( 'model.onnx') onnx.checker.check_model(onnx_mod
2019-07-28 07:50:25 -0600	answered a question	How can i load a onnx with opencv? @vealocia did you verify the model: import onnx onnx_model = onnx.load( 'model.onnx') onnx.checker.check_model(onnx_mod
2019-07-28 07:41:35 -0600	received badge	● Supporter (source)
2019-07-28 07:41:23 -0600	marked best answer	Access output of a Caffe Slice Layer I have a caffe model containing a Slice Layer. The input dimension is `(1, 96, 128, 128)` `layer { name: "63_64" type: "Slice" bottom: "62" top: "63" top: "64" slice_param { slice_point: 48 axis: 1 } }` and I want to get both resulting arrays (63 & 64). So what I thought I had to do was the following: `model = cv2.dnn.readNetFromCaffe("model.prototxt", "model.caffemodel") model.setInput(blob) r = model.forward(["63_64"])` Which should have given me two matrices with a dimension of `(1, 48, 128, 128)`, but I only got the first one. How do I access the second matrix
2019-07-28 07:41:23 -0600	received badge	● Scholar (source)
2019-07-28 07:41:17 -0600	commented answer	Access output of a Caffe Slice Layer @dkurt Thanks for the answer, r = model.forwardAndRetrieve(["63_64"]) did work as expected.
2019-07-28 07:28:15 -0600	commented question	Access output of a Caffe Slice Layer The squere brackets are still there because originally I wanted to receive multiple layers. Removing them does not make
2019-07-28 07:10:56 -0600	commented answer	Access output of a Caffe Slice Layer @supra56 I was using r = model.forward(["63_64"]) by intention to receive the output of that specific layer. model.forwa
2019-07-28 06:58:14 -0600	received badge	● Editor (source)
2019-07-28 06:58:14 -0600	edited question	Access output of a Caffe Slice Layer Access output of a Caffe Slice Layer I have a caffe model containing a Slice Layer. The input dimension is (1, 96, 128,
2019-07-23 10:09:47 -0600	asked a question	Access output of a Caffe Slice Layer Access output of a Caffe Slice Layer I have a caffe model containing a Slice Layer. The input dimension is (1, 96, 128,