Vfrdtyky

I am trying to capture images from an EVOCAM II Microscope from Vision Engineering using OpenCV. It says in its manual that it can be plugged into a computer using a USB 3.0 cable and then used as a normal webcam.

I am therefore using this very simple snippet to capture images from the camera:

import cv2

camera = cv2.VideoCapture(0)

ret, frame = camera.read()

if ret:

   cv2.imwrite('./test.png', frame)

However, when I should get 1920px x 1080px RGB pictures, I am getting 640px x 480px images with weird artifacts:

I tried to test the camera on other software like VLC or AMCap but I either get a 640px x 480px black image or the software can't even start the capture.

I am wondering if this is a problem of encoding or could it be something about how the camera declares itself to the computer.

Can I solve this problem by modifying some parameters in OpenCV or is it something different?

Thanks a lot for your time,

EDIT 1:

Output of opencv_version -v in my conda environment:

General configuration for OpenCV 3.4.2 =====================================

  Version control:               unknown



  Extra modules:

    Location (extra):            /opt/conda/conda-bld/opencv-suite_1533641454250/work/opencv_contrib-3.4.2/modules

    Version control (extra):     unknown



  Platform:

    Timestamp:                   2018-08-07T11:32:43Z

    Host:                        Linux 2.6.32-696.10.1.el6.x86_64 x86_64

    CMake:                       3.12.0

    CMake generator:             Unix Makefiles

    CMake build tool:            /usr/bin/gmake

    Configuration:               Release



  CPU/HW features:

    Baseline:                    SSE SSE2 SSE3

      requested:                 SSE3

    Dispatched code generation:  SSE4_1 SSE4_2 FP16 AVX AVX2 AVX512_SKX

      requested:                 SSE4_1 SSE4_2 AVX FP16 AVX2 AVX512_SKX

      SSE4_1 (3 files):          + SSSE3 SSE4_1

      SSE4_2 (1 files):          + SSSE3 SSE4_1 POPCNT SSE4_2

      FP16 (1 files):            + SSSE3 SSE4_1 POPCNT SSE4_2 FP16 AVX

      AVX (5 files):             + SSSE3 SSE4_1 POPCNT SSE4_2 AVX

      AVX2 (9 files):            + SSSE3 SSE4_1 POPCNT SSE4_2 FP16 FMA3 AVX AVX2

      AVX512_SKX (1 files):      + SSSE3 SSE4_1 POPCNT SSE4_2 FP16 FMA3 AVX AVX2 AVX_512F AVX512_SKX



  C/C++:

    Built as dynamic libs?:      YES

    C++11:                       YES

    C++ Compiler:                /opt/conda/conda-bld/opencv-suite_1533641454250/_build_env/bin/x86_64-conda_cos6-linux-gnu-c++  (ver 7.2.0)

    C++ flags (Release):         -fvisibility-inlines-hidden -std=c++11 -fmessage-length=0 -march=nocona -mtune=haswell -ftree-vectorize -fPIC -fstack-protector-strong -fno-plt -O2 -pipe -I/home/lucas/anaconda3/envs/p35_gpu_jupyter/include -fdebug-prefix-map=${SRC_DIR}=/usr/local/src/conda/${PKG_NAME}-${PKG_VERSION} -fdebug-prefix-map=${PREFIX}=/usr/local/src/conda-prefix   -fsigned-char -W -Wall -Werror=return-type -Werror=non-virtual-dtor -Werror=address -Werror=sequence-point -Wformat -Werror=format-security -Wmissing-declarations -Wundef -Winit-self -Wpointer-arith -Wshadow -Wsign-promo -Wuninitialized -Winit-self -Wno-narrowing -Wno-delete-non-virtual-dtor -Wno-comment -Wimplicit-fallthrough=3 -Wno-strict-overflow -fdiagnostics-show-option -Wno-long-long -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections  -msse -msse2 -msse3 -fopenmp -O3 -DNDEBUG  -DNDEBUG

    C++ flags (Debug):           -fvisibility-inlines-hidden -std=c++11 -fmessage-length=0 -march=nocona -mtune=haswell -ftree-vectorize -fPIC -fstack-protector-strong -fno-plt -O2 -pipe -I/home/lucas/anaconda3/envs/p35_gpu_jupyter/include -fdebug-prefix-map=${SRC_DIR}=/usr/local/src/conda/${PKG_NAME}-${PKG_VERSION} -fdebug-prefix-map=${PREFIX}=/usr/local/src/conda-prefix   -fsigned-char -W -Wall -Werror=return-type -Werror=non-virtual-dtor -Werror=address -Werror=sequence-point -Wformat -Werror=format-security -Wmissing-declarations -Wundef -Winit-self -Wpointer-arith -Wshadow -Wsign-promo -Wuninitialized -Winit-self -Wno-narrowing -Wno-delete-non-virtual-dtor -Wno-comment -Wimplicit-fallthrough=3 -Wno-strict-overflow -fdiagnostics-show-option -Wno-long-long -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections  -msse -msse2 -msse3 -fopenmp -g  -DDEBUG -D_DEBUG

    C Compiler:                  /opt/conda/conda-bld/opencv-suite_1533641454250/_build_env/bin/x86_64-conda_cos6-linux-gnu-cc

    C flags (Release):           -march=nocona -mtune=haswell -ftree-vectorize -fPIC -fstack-protector-strong -fno-plt -O2 -pipe -I/home/lucas/anaconda3/envs/p35_gpu_jupyter/include -fdebug-prefix-map=${SRC_DIR}=/usr/local/src/conda/${PKG_NAME}-${PKG_VERSION} -fdebug-prefix-map=${PREFIX}=/usr/local/src/conda-prefix   -fsigned-char -W -Wall -Werror=return-type -Werror=non-virtual-dtor -Werror=address -Werror=sequence-point -Wformat -Werror=format-security -Wmissing-declarations -Wmissing-prototypes -Wstrict-prototypes -Wundef -Winit-self -Wpointer-arith -Wshadow -Wuninitialized -Winit-self -Wno-narrowing -Wno-comment -Wimplicit-fallthrough=3 -Wno-strict-overflow -fdiagnostics-show-option -Wno-long-long -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections  -msse -msse2 -msse3 -fopenmp -O3 -DNDEBUG  -DNDEBUG

    C flags (Debug):             -march=nocona -mtune=haswell -ftree-vectorize -fPIC -fstack-protector-strong -fno-plt -O2 -pipe -I/home/lucas/anaconda3/envs/p35_gpu_jupyter/include -fdebug-prefix-map=${SRC_DIR}=/usr/local/src/conda/${PKG_NAME}-${PKG_VERSION} -fdebug-prefix-map=${PREFIX}=/usr/local/src/conda-prefix   -fsigned-char -W -Wall -Werror=return-type -Werror=non-virtual-dtor -Werror=address -Werror=sequence-point -Wformat -Werror=format-security -Wmissing-declarations -Wmissing-prototypes -Wstrict-prototypes -Wundef -Winit-self -Wpointer-arith -Wshadow -Wuninitialized -Winit-self -Wno-narrowing -Wno-comment -Wimplicit-fallthrough=3 -Wno-strict-overflow -fdiagnostics-show-option -Wno-long-long -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections  -msse -msse2 -msse3 -fopenmp -g  -DDEBUG -D_DEBUG

    Linker flags (Release):      -Wl,-O2 -Wl,--sort-common -Wl,--as-needed -Wl,-z,relro -Wl,-z,now -Wl,-rpath,/home/lucas/anaconda3/envs/p35_gpu_jupyter/lib -L/home/lucas/anaconda3/envs/p35_gpu_jupyter/lib   

    Linker flags (Debug):        -Wl,-O2 -Wl,--sort-common -Wl,--as-needed -Wl,-z,relro -Wl,-z,now -Wl,-rpath,/home/lucas/anaconda3/envs/p35_gpu_jupyter/lib -L/home/lucas/anaconda3/envs/p35_gpu_jupyter/lib   

    ccache:                      NO

    Precompiled headers:         YES

    Extra dependencies:          dl m pthread rt

    3rdparty dependencies:



  OpenCV modules:

    To be built:                 aruco bgsegm bioinspired calib3d ccalib core datasets dnn dnn_objdetect dpm face features2d flann freetype fuzzy hdf hfs highgui img_hash imgcodecs imgproc java java_bindings_generator line_descriptor ml objdetect optflow phase_unwrapping photo plot python2 python3 python_bindings_generator reg rgbd saliency shape stereo stitching structured_light superres surface_matching text tracking video videoio videostab xfeatures2d ximgproc xobjdetect xphoto

    Disabled:                    js world

    Disabled by dependency:      -

    Unavailable:                 cnn_3dobj cudaarithm cudabgsegm cudacodec cudafeatures2d cudafilters cudaimgproc cudalegacy cudaobjdetect cudaoptflow cudastereo cudawarping cudev cvv matlab ovis sfm ts viz

    Applications:                apps

    Documentation:               NO

    Non-free algorithms:         NO



  GUI: 



  Media I/O: 

    ZLib:                        /home/lucas/anaconda3/envs/p35_gpu_jupyter/lib/libz.so (ver 1.2.11)

    JPEG:                        /home/lucas/anaconda3/envs/p35_gpu_jupyter/lib/libjpeg.so (ver 90)

    WEBP:                        build (ver encoder: 0x020e)

    PNG:                         /home/lucas/anaconda3/envs/p35_gpu_jupyter/lib/libpng.so (ver 1.6.34)

    TIFF:                        /home/lucas/anaconda3/envs/p35_gpu_jupyter/lib/libtiff.so (ver 42 / 4.0.9)

    JPEG 2000:                   /home/lucas/anaconda3/envs/p35_gpu_jupyter/lib/libjasper.so (ver 2.0.14)

    OpenEXR:                     build (ver 1.7.1)

    HDR:                         YES

    SUNRASTER:                   YES

    PXM:                         YES



  Video I/O:

    DC1394:                      NO

    FFMPEG:                      YES

      avcodec:                   YES (ver 58.18.100)

      avformat:                  YES (ver 58.12.100)

      avutil:                    YES (ver 56.14.100)

      swscale:                   YES (ver 5.1.100)

      avresample:                YES (ver 4.0.0)

    GStreamer:                   NO

    libv4l/libv4l2:              NO

    v4l/v4l2:                    linux/videodev.h linux/videodev2.h

    gPhoto2:                     NO



  Parallel framework:            OpenMP



  Trace:                         YES (with Intel ITT)



  Other third-party libraries:

    Intel IPP:                   2017.0.3 [2017.0.3]

           at:                   /opt/conda/conda-bld/opencv-suite_1533641454250/work/build/3rdparty/ippicv/ippicv_lnx

    Intel IPP IW:                sources (2017.0.3)

              at:                /opt/conda/conda-bld/opencv-suite_1533641454250/work/build/3rdparty/ippicv/ippiw_lnx

    Lapack:                      NO

    Eigen:                       YES (ver 3.3.3)

    Custom HAL:                  NO

    Protobuf:                    /home/lucas/anaconda3/envs/p35_gpu_jupyter/lib/libprotobuf.so (3.5.1)



  Python 2:

    Interpreter:                 /opt/conda/conda-bld/opencv-suite_1533641454250/work/py2/bin/python (ver 2.7.15)

    Libraries:                   /opt/conda/conda-bld/opencv-suite_1533641454250/work/py2/lib/libpython2.7m.so (ver 2.7.15)

    numpy:                       /opt/conda/conda-bld/opencv-suite_1533641454250/work/py2/lib/python2.7/site-packages/numpy/core/include (ver 1.11.3)

    packages path:               /opt/conda/conda-bld/opencv-suite_1533641454250/work/py2/lib/python2.7/site-packages



  Python 3:

    Interpreter:                 /opt/conda/conda-bld/opencv-suite_1533641454250/work/py3/bin/python (ver 3.7)

    Libraries:                   /opt/conda/conda-bld/opencv-suite_1533641454250/work/py3/lib/libpython3.7m.so (ver 3.7.0)

    numpy:                       /opt/conda/conda-bld/opencv-suite_1533641454250/work/py3/lib/python3.7/site-packages/numpy/core/include (ver 1.11.3)

    packages path:               /opt/conda/conda-bld/opencv-suite_1533641454250/work/py3/lib/python3.7/site-packages



  Python (for build):            /opt/conda/conda-bld/opencv-suite_1533641454250/work/py2/bin/python



  Java:                          

    ant:                         /usr/bin/ant (ver 1.7.1)

    JNI:                         /usr/lib/jvm/java/include /usr/lib/jvm/java/include/linux /usr/lib/jvm/java/include

    Java wrappers:               YES

    Java tests:                  NO



  Install to:                    /home/lucas/anaconda3/envs/p35_gpu_jupyter

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TL;DR The cable used was USB 2.0, replacing it by a USB 3.0 solved the capture problem on Windows.

Yes, I know it sounds quite stupid but the reason why I was getting this strange image is that the USB cable was a 2.0 and not a 3.0. As the cable was already plugged in the camera I didn't bother verifying it but changing it to a 3.0 made it worked instantly on the camera Windows app. The company also confirmed that the EVO Cam II generates a signal using the DirectShow format.

However, when comparing the images that are saved on the USB drive by the camera and the one capture using the USB cable I realized that the quality is not similar. And especially in my case the quality of the images captured using the USB cable are not good enough. I will therefore not pursue in this direction anymore.

However, for those who would like to continue where I left it, here are some links the Vision Engineering support gave me to capture the images using OpenCV on Linux:

1. Webcam DirectShow Properties Page in Python


2. http://videocapture.sourceforge.net/

For the moment they don't have a straightforward solution for it.

Different kinds of USB transfer

The page you referenced does not say that the device can be "plugged into a computer using a USB 3.0 cable and then used as a normal webcam". The page says only that it has a usb 3.0 interface. The only resource available from the page you referenced, is the brochure, where it does not say its plug-and-play either.

In the area of vision devices and imaging devices, a common interface on top of usb, is the "usb vision" standard. Vendors that make such devices provide specialized drivers, and commonly provide example code on how to interface with popular libraries, such as openCV. Using devices with this standard provides increased transfer rates, lower lag times, and lower cpu utilization compared to plug-and-play. Often, a plug-and-play driver is provided also, but you have no guarantee. If such a plug-and-play driver would be available in addition to usb vision, you would want to use the usb vision driver instead, as it would be superior most likely.

The fact that the vendor says nothing about what driver it is, makes me immediately suspicious. I would contact them before any purchase, and have them explain why this is not mentioned (or maybe its hidden somewhere on their web-page?)

On linux (in comments you say you run ubuntu 18.04), this plug-and-play functionality comes through video-for-linux "v4l". If you want to use your device as you have shown above, you need to make sure that the vendor supplies a v4l driver, that works for your version of Linux.

Ubuntu version

As of writing this (19 November 2018), Ubuntu 18.04 has not been around long enough to expect stability of un-common use-cases. If the vendor of this imaging device provides v4l interface drivers, there is a reasonable probability it is unstable. Try using Ubuntu 16 if that is possible. If you find it to work with Ubuntu 16, even though your drivers is supposed to work for ubuntu 18, make sure to inform the developers you have found a bug.