我正在尝试使用OpenCV从EVOCAM II Microscope from Vision Engineering捕获图像。它在其手册中说,可以使用USB 3.0电缆将其插入计算机,然后用作普通的网络摄像头。
因此,我使用这个非常简单的代码片段从相机中捕获图像:
import cv2
camera = cv2.VideoCapture(0)
ret, frame = camera.read()
if ret:
cv2.imwrite('./test.png', frame)
但是,当我应该获得1920px x 1080px
张RGB图片时,我会得到640px x 480px
张带有怪异伪像的图像:
我试图在其他软件(例如 VLC 或 AMCap )上测试相机,但是我得到了640px x 480px
黑色图像,或者该软件甚至无法启动捕获。
我想知道这是否是编码问题,还是有关相机如何向计算机声明本身。
我可以通过在OpenCV中修改某些参数来解决此问题吗?
非常感谢您的时间,
编辑1 :
在我的conda环境中opencv_version -v
的输出:
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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答案 0 :(得分:1)
TL; DR所使用的电缆为USB 2.0,用USB 3.0代替它可以解决Windows上的捕获问题。
是的,我知道这听起来很愚蠢,但是我得到这张奇怪图像的原因是USB电缆是2.0而不是3.0。由于电缆已经插入相机中,因此我无需费心进行验证,但是将其更改为3.0使其可以在相机Windows应用程序上立即工作。该公司还确认EVO Cam II使用 DirectShow格式生成信号。
但是,当比较相机保存在USB驱动器上的图像和使用USB电缆捕获的图像时,我意识到质量并不相同。特别是在我的情况下,使用USB电缆捕获的图像质量不够好。因此,我将不再朝这个方向前进。
但是,对于那些想要继续我离开的人来说,以下是Vision Engineering支持人员提供的一些链接,这些链接使我可以在Linux上使用OpenCV捕获图像:
目前,他们还没有直接的解决方案。
答案 1 :(得分:0)
各种USB传输
您引用的页面并不表示可以将该设备“使用USB 3.0电缆插入计算机,然后用作普通网络摄像头”。该页面仅说它具有USB 3.0界面。您所引用的页面上唯一可用的资源是小册子,在小册子中也没有说明即插即用。
在视觉设备和成像设备领域,"usb vision" standard是USB上的通用接口。制造此类设备的供应商提供专门的驱动程序,并通常提供有关如何与流行的库(例如openCV)接口的示例代码。与即插即用相比,使用具有此标准的设备可提供更高的传输速率,更短的延迟时间和更低的CPU使用率。通常,也提供即插即用驱动程序,但是您不能保证。如果除了USB视觉之外还提供了这样的即插即用驱动程序,您可能会希望使用USB视觉驱动程序,因为它很有可能会更好。
供应商对驱动程序一无所知的事实使我立即感到怀疑。我会在购买任何产品之前与他们联系,并请他们解释为什么未提及(或隐藏在其网页上的某个地方?)
在linux上(用注释表示您运行ubuntu 18.04),此即插即用功能是通过基于Linux的视频“ v4l”实现的。如果要使用上面显示的设备,则需要确保供应商提供适用于您的Linux版本的v4l驱动程序。
Ubuntu版本
截至撰写本文时(2018年11月19日),Ubuntu 18.04尚不足以期待罕见的用例的稳定性。如果此成像设备的供应商提供v41接口驱动程序,则很有可能不稳定。如果可能,请尝试使用Ubuntu 16。如果您发现它可以与Ubuntu 16一起使用,即使您的驱动程序应该可以在ubuntu 18上使用,请确保通知开发人员您已发现错误。