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bogdan.deac last won the day on November 4 2019

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  1. Hi @PearSoup, I think that you should read the frames in the following way: #define MAX_HEIGHT 1080 #define MAX_WIDTH 1920 #define FILTER_WIDTH 3 float sigma = 0.5f; uint8_t *src = (uint8_t *) v4l2_help.buffers[v4l2_buf_index].start[V4L2_FORMAT_Y_PLANE]; uint32_t stridePixels = drm.create_dumb[drm.current_fb].pitch; /* ------------------------ read rgb frame ---------------------------------- */ /* read_input_rgb function from hls_helper reads each channel in turn so we need a matrix for each rgb channel */ xf::Mat<XF_8UC1, MAX_HEIGHT, MAX_WIDTH, XF_NPPC1> img_input_r(MAX_HEIGHT, MAX_WIDTH); xf::Mat<XF_8UC1, MAX_HEIGHT, MAX_WIDTH, XF_NPPC1> img_input_g(MAX_HEIGHT, MAX_WIDTH); xf::Mat<XF_8UC1, MAX_HEIGHT, MAX_WIDTH, XF_NPPC1> img_input_b(MAX_HEIGHT, MAX_WIDTH); /* read the r, g, and b channels */ read_input_rgb(src, img_input_r, img_input_g, img_input_b, stridePixels); /* now if you want you can combine the channels in one matrix. some xf functions require 4 channel matrix */ /* declare a new matrix with four channels: red, green, blue and alfa */ xf::Mat<XF_8UC4, MAX_HEIGHT, MAX_WIDTH, XF_NPPC1> img_combined(MAX_HEIGHT, MAX_WIDTH); /* we are non interested in alfa channel so it is initialized with 0 */ uchar zero_data[MAX_HEIGHT * MAX_WIDTH] = { 0 }; xf::Mat<XF_8UC1, MAX_HEIGHT, MAX_WIDTH, XF_NPPC1> img_alfa(MAX_HEIGHT, MAX_WIDTH, zero_data); /* combine the channels in one matrix */ xf::merge<XF_8UC1, XF_8UC4, MAX_HEIGHT, MAX_WIDTH, XF_NPPC1>(img_input_r, img_input_g, img_input_b, img_alfa, img_combined); /* -------------------------------------------------------------------------- */ /* ------------------------ read gray frame ---------------------------------- */ xf::Mat<XF_8UC1, MAX_HEIGHT, MAX_WIDTH, XF_NPPC1> img_input_gray(MAX_HEIGHT, MAX_WIDTH); read_input_rgb(src, img_input_gray, stridePixels); /* -------------------------------------------------------------------------- */ /* ------------------------ apply gaussian blur ----------------------------- */ xf::Mat<XF_8UC1, MAX_HEIGHT, MAX_WIDTH, XF_NPPC1> img_output_gauss(MAX_HEIGHT, MAX_WIDTH); xf::GaussianBlur<FILTER_WIDTH, XF_BORDER_CONSTANT, XF_8UC1, MAX_HEIGHT, MAX_WIDTH, XF_NPPC1>(img_input_gray, img_output_gauss, sigma); If you work on grayscale images use "read gray frame" method and ignore "read rgb frame". I suggest to read the frames and to process them in a while loop because there is the possibility to encounter video frame loss. Also, I advise you to have a look on xfopencv documentation. Here you will find examples for all xfopencv functions. Here you will find an example for gaussian filter. Regards, Bogdan D.
  2. I am sorry, but I don't understand your last question.
  3. Comment out the imshow("Image",img); line, build the application and run it. Do you get the same error message?
  4. Hello @kotra sharmila, Can you show the application's code?
  5. Hi @ahmedengr.bilal, You have three options: 1. Use standard OpenCV library which can be included in Petalinux rootfs. After that you can develop your application using OpenCV functions. 2. Use xfOpenCV library from Xilinx. Find the documentation here. Some examples here. It offers a subset of standard OpenCV library functions, modified to be easily accelerated in FPGA. 3. Use standard OpenCV and xfOpenCV libraries. This options is suitable for more complex algorithms where you process some functions on ARM processor and another ones in FPGA for better performance. For all mentioned options you have to implement the image acquisition mechanism from a camera if you don't intend to use static images. Usually, the easiest way to develop video processing apps using xfOpenCV and OpenCV on Xilinx SoC is SDSoC. Find more info here. Using SDSoC you have a hardware platform which describes your hardware configuration and another important aspects like libraries, sample projects, etc. Usually, this platform is provided by the development board manufacturer, in this case Digilent. Two SDSoC platform aspects are important for you: 1. The hardware configuration which implements the image acquisition mechanism. Find Digilent Zybo Z7-20 SDSoC Platform here. 2. Sample projects. Find sample projects for the above mentioned platform here.
  6. bogdan.deac

    OpenCV and Pcam5-c

    To start the application run: ./ ./filter2d_test.elf
  7. bogdan.deac

    OpenCV and Pcam5-c

    Hi @Esti.A, I attached the files.
  8. bogdan.deac

    OpenCV and Pcam5-c

    @Esti.A, I get that warning message but the application starts normally. I will try to discover the cause of that message.
  9. bogdan.deac

    OpenCV and Pcam5-c

    I launched the application in vga resolution configuration and tried different switches combinations to change the filter type.
  10. bogdan.deac

    OpenCV and Pcam5-c

    Hi @Esti.A, Until now, I conclude that the system works very slow. I obtained filtered images with a very low frame rate (aprox. 1 frame / 7 sec. ). Still I don't know which is the component that generates the bottleneck. I am trying to modify the project and to simplify it's structure to solve this issue. I will post here any updates that I have.
  11. bogdan.deac

    OpenCV and Pcam5-c

    Hi @Esti.A, I am still working on this issue. Do you have any updates? Partially, I encounter the same problems. If I wait for aprox. 2 min I get a single frame displayed on monitor but that'a all. What output do you get if you run v4l2-ctl -d /dev/video0 --list-inputs ?
  12. bogdan.deac

    OpenCV and Pcam5-c

    What ZYNQ part is loaded on your board, 7010 or 7020? Did you try to turn on and off the switches? The filter are controlled using them.
  13. bogdan.deac

    OpenCV and Pcam5-c

    What setup do you use? Do you have PCam and a HDMI monitor connected to Zybo Z7? Make sure that the connection is done before board power up.
  14. bogdan.deac

    OpenCV and Pcam5-c

    Please answer the following questions: 1. Did you follow these steps? 2. Have you got any error message on one of them? 3. Have you mount /dev/mmcblk0p1? How do you launch the opencv application?