# Sample applications
## Implement and deploy OpenCV sample application
## Prerequisites
- Install the Platform eSDK using either of the following methods:
- [Using the Qualcomm release archive](https://docs.qualcomm.com/bundle/publicresource/topics/80-70020-51/install-sdk.html#download-and-install-esdk)
- [Manually compiling the Qualcomm Linux SDK](https://docs.qualcomm.com/bundle/publicresource/topics/80-70020-254/how_to.html#generate-an-esdk)
## Implement OpenCV rotate application with FastCV
See [OpenCV rotate()](https://docs.qualcomm.com/doc/80-70023-21/topic/sample-applications.html#opencv-rotate) for API usage details.
1. Go to your SDK installation path on the Linux host and set the SDK environment by running the following command:
source environment-setup-armv8-2a-qcom-linux
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2. Run the following command to set the SDKTARGETSYSROOT.
export SDKTARGETSYSROOT={}/tmp/sysroots
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3. Run the following commands to create and change the `/opencv_rotate/` directory in the SDK install directory.
mkdir opencv_rotate
cd opencv_rotate
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4. Create the following [configure.ac](https://docs.qualcomm.com/doc/80-70023-21/topic/sample-applications.html#configureac3), [Makefile.am](https://docs.qualcomm.com/doc/80-70023-21/topic/sample-applications.html#makefile3), and [opencv\_rotate.cpp](https://docs.qualcomm.com/doc/80-70023-21/topic/sample-applications.html#opencv-rotate-cpp3) files in the `/opencv_rotate/` directory.
Note
The JPG image referenced in this example is from [https://github.com/opencv/opencv_extra/blob/4.x/testdata/stitching/boat1.jpg](https://github.com/opencv/opencv_extra/blob/4.x/testdata/stitching/boat1.jpg), and can be changed.
- `configure.ac`
>
>
> AC_PREREQ([2.71])
> AC_INIT([opencv_rotate],[1.0.0])
> AM_INIT_AUTOMAKE([-Wall gnu foreign subdir-objects])
> AC_CONFIG_SRCDIR([Makefile.am])
> AC_CONFIG_HEADERS([config.h])
> AC_CONFIG_MACRO_DIR([m4])
>
> AC_ARG_WITH([sanitized-headers],
> [AS_HELP_STRING([--with-sanitized-headers=DIR],[location of the sanitized Linux headers])],
> [CPPFLAGS="$CPPFLAGS -I$withval"])
>
> AM_PROG_AS
> AM_PROG_AR
> AC_PROG_CC
> AM_PROG_CC_C_O
> AC_PROG_CPP
> AC_PROG_CXX
> LT_INIT
> AC_PROG_AWK
> AC_PROG_INSTALL
> AC_PROG_LN_S
> AC_PROG_MAKE_SET
>
> AC_ARG_WITH([opencv-path],
> [AS_HELP_STRING([--with-opencv-path=DIR],[path to opencv])],
> [OPENCV_PATH="$withval"])
>
> # The toolchain parameter passed by the bitbake is consumed here
> AC_ARG_WITH([toolchain-used],
> AS_HELP_STRING([--with-toolchain-used],
> [Specify the toolchain-used for compilation]),
> [toolchain_used=$withval],
> toolchain_used=sdllvm)
> AM_CONDITIONAL(GCC_ENABLE, test "x$toolchain_used" = "xgcc")
> AM_CONDITIONAL(SDLLVM_ENABLE, test "x$toolchain_used" = "xsdllvm")
>
> AC_SUBST([OPENCV_PATH])
>
> AC_CONFIG_FILES([ Makefile])
> AC_OUTPUT
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- `Makefile.am`
>
>
> #ACLOCAL_AMFLAGS = -I m4
> # ---------------------------------------------------------------------------------
> # Make the libfastcvOPT library (libfastcvopt)
> # ---------------------------------------------------------------------------------
>
> common_flags = -O3 \
> -fPIC \
> -Wall \
> -Wno-error \
> -Wno-error=uninitialized \
> -flax-vector-conversions \
> -I${OPENCV_PATH}
>
> AM_CFLAGS = $(common_flags)
>
> AM_CPPFLAGS = $(common_flags)
>
> test_sources = opencv_rotate.cpp
>
> bin_PROGRAMS = opencv_rotate_test
> opencv_rotate_test_SOURCES = $(test_sources)
> opencv_rotate_test_CPPFLAGS = $(AM_CPPFLAGS)
> opencv_rotate_test_CFLAGS = $(AM_CFLAGS)
> opencv_rotate_test_LDADD = -ldl -lpthread -lopencv_core -lopencv_imgproc -lopencv_imgcodecs -lopencv_fastcv
> Copy to clipboard
- `opencv_rotate.cpp`
>
>
> #include
> #include
> #include "opencv2/opencv.hpp"
> #include "opencv2/imgcodecs.hpp"
> #include "opencv2/fastcv/scale.hpp"
>
> using namespace cv;
>
> int main()
> {
> Mat input = imread("/tmp/test/samples/boat1.jpg");
> Mat dst;
> auto start = std::chrono::high_resolution_clock::now();
> rotate(input, dst, ROTATE_90_CLOCKWISE);
> imwrite("/tmp/test/samples/output.jpg", dst);
> auto end = std::chrono::high_resolution_clock::now();
> std::chrono::microseconds time_span = std::chrono::duration_cast(end - start);
> std::cout << "Total time taken: " << time_span.count() << " us.\n";
>
> return 0;
> }
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### Compile OpenCV rotate application
1. Run the following commands.
mkdir -p m4
aclocal
autoconf
touch NEWS README AUTHORS ChangeLog
autoreconf --install
automake -a
./configure ${CONFIGURE_FLAGS} --with-opencv_path=${SDKTARGETSYSROOT}//usr/include/opencv4
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Replace `` with your device’s machine name. See [Build BSP image](https://docs.qualcomm.com/bundle/publicresource/topics/80-70020-254/github_workflow_unregistered_users.html#build-bsp-image)
for instructions to find your machine name.
2. Run the `make` command to compile the application.
make
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The `opencv_rotate_test` test application generates in the `/opencv_rotate/` directory.
### Run the OpenCV rotate application
1. To push the test bin, run the following command on the host.
scp -r opencv_rotate_test root@{[IP-ADDR]}:/usr/bin/
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Note
If you are unable to copy the file, remount using the following commands:
mount -o remount,rw /usr
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Check permissions using:
mount | grep /
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2. Run the following command to change directories (`cd`) to the path (for example `/images/boat1.jpg`) of the test image.
cd {}
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3. Create a directory (for example `/tmp/test/samples/`) on the device to push the test image.
This `/tmp/test/samples/` directory is also the location of the output image in test code.
Modify this directory according to the specified output location on your machine.
4. Run the following command to push the test image to the device.
scp -r boat1.jpg root@{[IP-ADDR]}:{/tmp/test/samples/}
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5. To start the test on the target device, run the following commands.
chmod 777 /usr/bin/opencv_rotate_test
/usr/bin/opencv_rotate_test
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6. To get the results, run the following command.
scp -r root@{[IP-ADDR]}:/tmp/test/samples/output.jpg user2@{[HOST IP-ADDR]}:/workspace
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The `/tmp/test/samples/` directory is the location of the output image in test code.
Modify according to your specified output location.
The following is the expected result.
| Input | Rotate | Output |
| --- | --- | --- |
|  | ROTATE\_90\_CLOCKWISE |  |
## Implement OpenCV resize application with FastCV extension
See [OpenCV resize()](https://docs.qualcomm.com/doc/80-70023-21/topic/sample-applications.html#opencv-resize) for API usage details.
1. Once the eSDK is installed, run the following commands to create and change the
`/opencv_resize_extension/` directory in the SDK install directory.
mkdir opencv_resize_extension
cd opencv_resize_extension
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2. Create the following `configure.ac`, `Makefile.am`, and `opencv_resize_extension.cpp` files in the `/opencv_resize_extension/` directory.
Note
The PNG image referenced in this example is [https://github.com/opencv/opencv/blob/4.x/samples/data/box_in_scene.png](https://github.com/opencv/opencv/blob/4.x/samples/data/box_in_scene.png), but you can use another image if you want.
- `configure.ac`
AC_PREREQ([2.71])
AC_INIT([opencv_resize],[1.0.0])
AM_INIT_AUTOMAKE([-Wall gnu foreign subdir-objects])
AC_CONFIG_SRCDIR([Makefile.am])
AC_CONFIG_HEADERS([config.h])
AC_CONFIG_MACRO_DIR([m4])
AC_ARG_WITH([sanitized-headers],
[AS_HELP_STRING([--with-sanitized-headers=DIR],[location of the sanitized Linux headers])],
[CPPFLAGS="$CPPFLAGS -I$withval"])
AM_PROG_AS
AM_PROG_AR
AC_PROG_CC
AM_PROG_CC_C_O
AC_PROG_CPP
AC_PROG_CXX
LT_INIT
AC_PROG_AWK
AC_PROG_INSTALL
AC_PROG_LN_S
AC_PROG_MAKE_SET
AC_ARG_WITH([opencv-path],
[AS_HELP_STRING([--with-opencv-path=DIR],[path to opencv])],
[OPENCV_PATH="$withval"])
# The toolchain parameter passed by the bitbake is consumed here
AC_ARG_WITH([toolchain-used],
AS_HELP_STRING([--with-toolchain-used],
[Specify the toolchain-used for compilation]),
[toolchain_used=$withval],
toolchain_used=sdllvm)
AM_CONDITIONAL(GCC_ENABLE, test "x$toolchain_used" = "xgcc")
AM_CONDITIONAL(SDLLVM_ENABLE, test "x$toolchain_used" = "xsdllvm")
AC_SUBST([OPENCV_PATH])
AC_CONFIG_FILES([ Makefile])
AC_OUTPUT
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- `Makefile.am`
#ACLOCAL_AMFLAGS = -I m4
# ---------------------------------------------------------------------------------
# Make the libfastcvOPT library (libfastcvopt)
# ---------------------------------------------------------------------------------
common_flags = -O3 \
-fPIC \
-Wall \
-Wno-error \
-Wno-error=uninitialized \
-flax-vector-conversions \
-I${OPENCV_PATH}
AM_CFLAGS = $(common_flags)
AM_CPPFLAGS = $(common_flags)
test_sources = opencv_resize_extension.cpp
bin_PROGRAMS = opencv_resize_test
opencv_resize_test_SOURCES = $(test_sources)
opencv_resize_test_CPPFLAGS = $(AM_CPPFLAGS)
opencv_resize_test_CFLAGS = $(AM_CFLAGS)
opencv_resize_test_LDADD = -ldl -lpthread -lopencv_core -lopencv_imgproc -lopencv_imgcodecs -lopencv_fastcv
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- `opencv_resize_extension.cpp`
#include
#include
#include "opencv2/opencv.hpp"
#include "opencv2/imgcodecs.hpp"
#include "opencv2/fastcv/scale.hpp"
using namespace cv;
int main()
{
Mat input = imread("/tmp/test/samples/box_in_scene.png", IMREAD_GRAYSCALE);
Mat dst ;
auto start = std::chrono::high_resolution_clock::now();
fastcv::resizeDownBy2(input, dst);
//resize(input, dst, Size(), 0.5, 0.5, INTER_LINEAR);
imwrite("/tmp/test/samples/output.png", dst);
auto end = std::chrono::high_resolution_clock::now();
std::chrono::microseconds time_span = std::chrono::duration_cast(end - start);
std::cout << "Total time taken: " << time_span.count() << " us.\n";
// if(!dst) std::cout << "Test not executed properly" << std::endl;
return 0;
}
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### Compile OpenCV resize application
1. Run the following commands.
mkdir -p m4
aclocal
autoconf
touch NEWS README AUTHORS ChangeLog
autoreconf --install
automake -a
./configure ${CONFIGURE_FLAGS} --with-opencv_path=${SDKTARGETSYSROOT}//usr/include/opencv4
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Replace `` with your device’s machine name. See [Build BSP image](https://docs.qualcomm.com/bundle/publicresource/topics/80-70020-254/github_workflow_unregistered_users.html#build-bsp-image) for instructions to find your machine name.
2. Run the make command to compile the application.
make
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The `opencv_resize_test` test application generates in the `/opencv_resize_extension/` directory.
### Run OpenCV resize application
1. To push the test bin, run the following command on the host.
scp -r opencv_resize_test root@{[IP-ADDR]}:/usr/bin/
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2. Run the following command to change directories (`cd`) to the path of the test image (for example `/images/box_in_scene.png`).
cd {}
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3. Create a directory on the device to copy the test image to (for example `/tmp/test/samples/`).
This `/tmp/test/samples/` directory is also the location of the output image in the sample code.
Modify this directory according to the specified output location on your machine.
4. Run the following command to copy the test image to the device.
scp -r box_in_scene.png root@{[IP-ADDR]}:{/tmp/test/samples/}
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5. To start the test on the target device, run the following commands.
chmod 777 /usr/bin/opencv_resize_test
/usr/bin/opencv_resize_test
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6. To get the results, run the following command.
scp -r root@{[IP-ADDR]}:/tmp/test/samples/output.png user2@{[HOST IP-ADDR]}:/workspace
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The `/tmp/test/samples/` directory is the location of the output image in the sample code.
Modify this location according to your specified output location.
The following is the expected result.
| Input | Resize factor | Output |
| --- | --- | --- |
|  | fx=1/2 fy=1/2 |  |
## OpenCV rotate function usage
Rotates a 2D array in multiples of 90 degrees. The `rotate()` function rotates the array in one of the following ways.
- 90 degrees clockwise: `rotateCode = ROTATE_90_CLOCKWISE`
- 180 degrees clockwise: `rotateCode = ROTATE_180`
- 270 degrees clockwise: `rotateCode = ROTATE_90_COUNTERCLOCKWISE`
| Type | Parameter | Description |
| --- | --- | --- |
| InputArray | src | Input array. |
| OutputArray | dst | Output array of the same type as the source.
The size is the same with `ROTATE_180` and the rows and columns are switched for `ROTATE_90_CLOCKWISE` and `ROTATE_90_COUNTERCLOCKWISE`. |
| int | code | An enum to specify how to rotate the array; see the `RotateFlags` enum.
RotateFlags:
ROTATE_90_CLOCKWISE
ROTATE_180
ROTATE_90_COUNTERCLOCKWISE
|
For more information about `rotate()`, see
[the full API documentation](https://docs.opencv.org/3.4/d2/de8/group__core__array.html#ga4ad01c0978b0ce64baa246811deeac24)
## OpenCV resize function usage
Input to the OpenCV resize() function is a source (src) image in the form of CVMatrix.
Note
Only grayscale images are supported.
Output is a destination image in the form of CVMatrix.
The FastCV namespace is used to call the FastCV extension APIs.
The resizeDownBy2() extension API requires the input image and destination image as parameters.
| Type | Parameter | Description |
| --- | --- | --- |
| InputArray | input | Input image. |
| OutputArray | dst | Output image. |
For more information about `resize()`, see
[the full API documentation](https://docs.opencv.org/4.11.0/da/d54/group__imgproc__transform.html#ga47a974309e9102f5f08231edc7e7529d).
Last Published: Dec 16, 2025
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