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select the device (video capture)

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cabelo 2018-05-08 01:07:23 -03:00 committed by Dmitry Kurtaev
parent 107b3f328b
commit 1b3e0783f4
4 changed files with 16 additions and 14 deletions
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4
doc/tutorials/dnn/dnn_yolo/dnn_yolo.markdown
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@ -29,7 +29,7 @@ Execute in webcam:
@code{.bash}
$ example_dnn_object_detection --config=[PATH-TO-DARKNET]/cfg/yolo.cfg --model=[PATH-TO-DARKNET]/yolo.weights --classes=object_detection_classes_pascal_voc.txt --width=416 --height=416 --scale=0.00392
$ example_dnn_object_detection --config=[PATH-TO-DARKNET]/cfg/yolo.cfg --model=[PATH-TO-DARKNET]/yolo.weights --classes=object_detection_classes_pascal_voc.txt --width=416 --height=416 --scale=0.00392 --rgb
@endcode
@ -37,7 +37,7 @@ Execute with image or video file:
@code{.bash}
$ example_dnn_object_detection --config=[PATH-TO-DARKNET]/cfg/yolo.cfg --model=[PATH-TO-DARKNET]/yolo.weights --classes=object_detection_classes_pascal_voc.txt --width=416 --height=416 --scale=0.00392 --input=[PATH-TO-IMAGE-OR-VIDEO-FILE]
$ example_dnn_object_detection --config=[PATH-TO-DARKNET]/cfg/yolo.cfg --model=[PATH-TO-DARKNET]/yolo.weights --classes=object_detection_classes_pascal_voc.txt --width=416 --height=416 --scale=0.00392 --input=[PATH-TO-IMAGE-OR-VIDEO-FILE] --rgb
@endcode

9
samples/dnn/object_detection.cpp
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@ -7,12 +7,13 @@
const char* keys =
"{ help h | | Print help message. }"
"{ input i | | Path to input image or video file. Skip this argument to capture frames from a camera.}"
"{ device | 0 | camera device number. }"
"{ input i | | Path to input image or video file. Skip this argument to capture frames from a camera. }"
"{ model m | | Path to a binary file of model contains trained weights. "
"It could be a file with extensions .caffemodel (Caffe), "
".pb (TensorFlow), .t7 or .net (Torch), .weights (Darknet) }"
".pb (TensorFlow), .t7 or .net (Torch), .weights (Darknet).}"
"{ config c | | Path to a text file of model contains network configuration. "
"It could be a file with extensions .prototxt (Caffe), .pbtxt (TensorFlow), .cfg (Darknet) }"
"It could be a file with extensions .prototxt (Caffe), .pbtxt (TensorFlow), .cfg (Darknet).}"
"{ framework f | | Optional name of an origin framework of the model. Detect it automatically if it does not set. }"
"{ classes | | Optional path to a text file with names of classes to label detected objects. }"
"{ mean | | Preprocess input image by subtracting mean values. Mean values should be in BGR order and delimited by spaces. }"
@ -91,7 +92,7 @@ int main(int argc, char** argv)
if (parser.has("input"))
cap.open(parser.get<String>("input"));
else
cap.open(0);
cap.open(parser.get<int>("device"));
// Process frames.
Mat frame, blob;

8
samples/dnn/openpose.cpp
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@ -61,12 +61,16 @@ int main(int argc, char **argv)
"{ p proto | | (required) model configuration, e.g. hand/pose.prototxt }"
"{ m model | | (required) model weights, e.g. hand/pose_iter_102000.caffemodel }"
"{ i image | | (required) path to image file (containing a single person, or hand) }"
"{ width | 368 | Preprocess input image by resizing to a specific width. }"
"{ height | 368 | Preprocess input image by resizing to a specific height. }"
"{ t threshold | 0.1 | threshold or confidence value for the heatmap }"
);
String modelTxt = parser.get<string>("proto");
String modelBin = parser.get<string>("model");
String imageFile = parser.get<String>("image");
int W_in = parser.get<int>("width");
int H_in = parser.get<int>("height");
float thresh = parser.get<float>("threshold");
if (parser.get<bool>("help") || modelTxt.empty() || modelBin.empty() || imageFile.empty())
{
@ -75,10 +79,6 @@ int main(int argc, char **argv)
return 0;
}
// fixed input size for the pretrained network
int W_in = 368;
int H_in = 368;
// read the network model
Net net = readNetFromCaffe(modelTxt, modelBin);

9
samples/dnn/segmentation.cpp
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@ -7,12 +7,13 @@
const char* keys =
"{ help h | | Print help message. }"
"{ input i | | Path to input image or video file. Skip this argument to capture frames from a camera.}"
"{ device | 0 | camera device number. }"
"{ input i | | Path to input image or video file. Skip this argument to capture frames from a camera. }"
"{ model m | | Path to a binary file of model contains trained weights. "
"It could be a file with extensions .caffemodel (Caffe), "
".pb (TensorFlow), .t7 or .net (Torch), .weights (Darknet) }"
".pb (TensorFlow), .t7 or .net (Torch), .weights (Darknet). }"
"{ config c | | Path to a text file of model contains network configuration. "
"It could be a file with extensions .prototxt (Caffe), .pbtxt (TensorFlow), .cfg (Darknet) }"
"It could be a file with extensions .prototxt (Caffe), .pbtxt (TensorFlow), .cfg (Darknet). }"
"{ framework f | | Optional name of an origin framework of the model. Detect it automatically if it does not set. }"
"{ classes | | Optional path to a text file with names of classes. }"
"{ colors | | Optional path to a text file with colors for an every class. "
@ -111,7 +112,7 @@ int main(int argc, char** argv)
if (parser.has("input"))
cap.open(parser.get<String>("input"));
else
cap.open(0);
cap.open(parser.get<int>("device"));
//! [Open a video file or an image file or a camera stream]
// Process frames.