$ python

Python 2.7.12 (default, Nov 19 2016, 06:48:10)
[GCC 5.4.0 20160609] on linux2
Type "help", "copyright", "credits" or "license" for more information.
> import cv2
> cap = cv2.VideoCapture(0)
> print cap.isOpened()
True
>

> import cv2
> cv2.namedWindow('test',cv2.WINDOW_AUTOSIZE)
> 

OpenCV Error: Unspecified error (The function is not implemented. Rebuild the library with Windows,
 GTK+ 2.x or Carbon support. If you are on Ubuntu or Debian, install libgtk2.0-dev and pkg-config, 
then re-run cmake or configure script) in cvNamedWindow,

$ pip list |grep opencv

$ sudo apt-get remove python-opencv

$ cd build
$ make uninstall

$ ln -s /usr/include/libv4l1-videodev.h /usr/include/linux/videodev.h

$ sudo apt-get install libgphoto2-dev v4l2ucp libv4l-dev dv4l libwebcam0-dev libgtkglext1-dev libunicap2-dev 

$ cmake -D CMAKE_BUILD_TYPE=Release -D CMAKE_INSTALL_PREFIX=/usr/local -D WITH_TBB=ON -D WITH_V4L=ON -D WITH_GTK=ON -D WITH_GTK_2_X -D WITH_OPENGL=ON -D WITH_CUDA=ON -D WITH_CUBLAS=ON -D BUILD_PYTHON_SUPPORT=ON -D OPENCV_EXTRA_MODULES_PATH=../opencv_contrib-3.2.0/modules/ ../opencv-3.2.0

-D WITH_LIBV4L=ON

Detected version of GNU GCC: 54 (504)
FP16: Feature disabled
Found OpenEXR: /usr/lib/x86_64-linux-gnu/libIlmImf.so
Checking for module 'libucil'
 No package 'libucil' found
Looking for linux/videodev.h
Looking for linux/videodev.h - found
Looking for linux/videodev2.h
Looking for linux/videodev2.h - found
Looking for sys/videoio.h
Looking for sys/videoio.h - not found
Checking for module 'libavresample'
 No package 'libavresample' found
Found TBB: build
found IPP (ICV version): 9.0.1 [9.0.1]
at: /mnt/sdb/ubuntu/install/opencv/build/3rdparty/ippicv/ippicv_lnx
CUDA detected: 8.0
CUDA NVCC target flags: -gencode;arch=compute_20,code=sm_20;-gencode;arch=compute_30,code=sm_30;-gencode;arch=compute_35,code=sm_35;-gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_52,code=sm_52;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_61,code=sm_61;-D_FORCE_INLINES
LAPACK_IMPL: Atlas, LAPACK_LIBRARIES: /usr/lib/liblapack.so;/usr/lib/libcblas.so;/usr/lib/libatlas.so
Could NOT find JNI (missing: JAVA_AWT_LIBRARY JAVA_JVM_LIBRARY JAVA_INCLUDE_PATH JAVA_INCLUDE_PATH2 JAVA_AWT_INCLUDE_PATH) 
Could NOT find Matlab (missing: MATLAB_MEX_SCRIPT MATLAB_INCLUDE_DIRS MATLAB_ROOT_DIR MATLAB_LIBRARIES MATLAB_LIBRARY_DIRS MATLAB_MEXEXT MATLAB_ARCH MATLAB_BIN) 
VTK is not found. Please set -DVTK_DIR in CMake to VTK build directory, or to VTK install subdirectory with VTKConfig.cmake file
 
General configuration for OpenCV 3.2.0 =====================================
 Version control:    unknown
 
 Platform:
 Timestamp:     2017-08-14T00:31:55Z
 Host:      Linux 4.10.0-30-generic x86_64
 CMake:      3.5.1
 CMake generator:    Unix Makefiles
 CMake build tool:   /usr/bin/make
 Configuration:    Release
 
 C/C++:
 Built as dynamic libs"htmlcode">

Checking for module 'libucil'
 No package 'libucil' found


这个我还真没找到怎么解决，不过反正问题不大
再来下面的部份一定要注意几个部分一定要有


 GUI: 
 GTK+ 2.x:     YES (ver 2.24.30)




Video I/O:
 V4L/V4L2:     YES/YES
 FFMPEG:      YES
 Python 2:
 Interpreter:     /usr/bin/python2.7 (ver 2.7.12)
 Libraries:     /usr/lib/x86_64-linux-gnu/libpython2.7.so (ver 2.7.12)
 numpy:      /usr/local/lib/python2.7/dist-packages/numpy/core/include (ver 1.13.1)
 packages path:    lib/python2.7/dist-packages


主要就是上面几个个非常重要，必須要装上
再来就正常 make


$ make -j8
$ make install


设置nccl的ld环境


$ vi /etc/ld.so.conf.d/nccl.conf


加上下面目录


/usr/local/nccl/lib/


然后执行


$ sudo ldconfig


安装完后回python按步骤一再次检查是否环境都好使了
二、撰写Python测试程序


# -*- coding:utf-8 -*-
# 用于模型的单张图像分类操作
import os
os.environ['GLOG_minloglevel'] = '2' # 将caffe的输出log信息不显示，必须放到import caffe前
import caffe # caffe 模块
from caffe.proto import caffe_pb2
from google.protobuf import text_format
import numpy as np
import cv2
import matplotlib.pyplot as plt
import time
import skimage.io
 
global num
num = 0
 
 
 
def detect(image1,net):
 # 传进来的image1的dtype为uint8
 # print image1.shape
 # print image1.dtype
 # print image1.size
 
 # image = np.array(image1, dtype=np.float32)
 # image = caffe.io.resize_image(image1, (480, 640))
 image = skimage.img_as_float(image1).astype(np.float32)
 # image = caffe.io.resize_image(image2, (300, 300))
 
 # skimage.io.imsave("photo.png", image)
 # cv2.imwrite("photo.png", image)
 # image = caffe.io.load_image(caffe_root + 'examples/images/bird.jpg')
 # 以下方式读取的imaged的dtype为float32
 # image = caffe.io.load_image(caffe_root + 'photo.png')
 # image = caffe.io.load_image(image1)
 
 # 改变dtype
 # image.dtype = 'float32'
 # print 'mode:'+image.mode
 # print image.shape
 # print image.dtype
 # print image.size
 
 # plt.imshow(image)
 
 # * Run the net and examine the top_k results
 # In[5]:
 global num
 num += 1
 print 'image num:' + str(num)
 
 transformed_image = transformer.preprocess('data', image)
 net.blobs['data'].data[...] = transformed_image
 
 time_start=time.time()
 # Forward pass.
 net.forward()
	
 time_end=time.time() 
 print 'time:' + str(time_end-time_start) + ' s'
 
 
 
 loc = net.blobs['bbox-list'].data[0]
 print(loc)
 #查看了结构文件发现在CAFFE一开始图像输入的时候就已经将图片缩小了，宽度1248高度384
 #然后我们在net.blobs['bbox-list'].data得到的是侦测到的目标座标，但是是相对于1248*384的
 #所以我们要把座标转换回相对原大小的位置，下面im.shape是保存在原尺寸的宽高，
 for l in range(len(loc)):
		xmin = int(loc[l][0] * image.shape[1] / 1248)
		ymin = int(loc[l][1] * image.shape[0] / 384)
		xmax = int(loc[l][2] * image.shape[1] /1248)
		ymax = int(loc[l][3] * image.shape[0] / 384)
		#在该座标位置画一个方框
		cv2.rectangle(image, (xmin, ymin), (xmax, ymax), (55 / 255.0, 255 / 255.0, 155 / 255.0), 2)
 # 显示结果
 
 #plt.imshow(image, 'brg')
 #plt.show()
 cv2.imshow('img', image)
 
 
 
def show_info(cam):
 print 'POS_FRAMES:'+str(cam.get(1))
 print 'FRAME_COUNT:'+str(cam.get(7))
 print 'FORMAT:'+str(cam.get(8))
 print 'MODE:'+str(cam.get(9))
 print 'SATURATION:'+str(cam.get(12))
 print 'FPS:'+str(cam.get(5))
 
#CPU或GPU模型转换
caffe.set_mode_gpu()
#caffe.set_mode_cpu()
#caffe.set_device(0)
 
caffe_root = '/var/smb/work/mycode/'
# 网络参数（权重）文件
caffemodel = caffe_root + 'module/detectnet/snapshot_iter_2391.caffemodel'
# 网络实施结构配置文件
deploy = caffe_root + 'module/detectnet/deploy.prototxt'
 
 
img_root = caffe_root + 'data/'
 
# 网络实施分类
net = caffe.Net(deploy, # 定义模型结构
    caffemodel, # 包含了模型的训练权值
    caffe.TEST) # 使用测试模式(不执行dropout)
 
# 加载ImageNet图像均值 (随着Caffe一起发布的)
print(os.environ['PYTHONPATH'])
#mu = np.load(os.environ['PYTHONPATH'] + '/caffe/imagenet/ilsvrc_2012_mean.npy')
#mu = mu.mean(1).mean(1) # 对所有像素值取平均以此获取BGR的均值像素值
 
# 图像预处理
transformer = caffe.io.Transformer({'data': net.blobs['data'].data.shape})
transformer.set_transpose('data', (2,0,1))
#transformer.set_mean('data', mu)
transformer.set_raw_scale('data', 255)
transformer.set_channel_swap('data', (2,1,0))
 
# 处理图像
cam = cv2.VideoCapture(0) 
if cam.isOpened():
 cam.set(3, 400)
 cam.set(4, 300)
 cam.set(5, 3)
 time.sleep(6)
 cam.set(15, -8.0)
 size = (int(cam.get(3)), int(cam.get(4)))
 print 'size:'
 print size
 
cv2.namedWindow('img', cv2.WINDOW_NORMAL)
 
# cnt=2
# while cnt:
#  cnt -= 1
while cam.isOpened():
 ret, img = cam.read()
 if ret:
  #show_info(cam)
  detect(img,net)
 
 if 0xFF == ord('q') & cv2.waitKey(5) == 27:
  break
 # time.sleep(0.033)
cam.release()
cv2.destroyAllWindows()



介面上会打印bbox也就是侦测到的目标在图像的座标，另外请自行修改python代码里的相关目录，

我用自己训练的KITTI数据集，用于侦测车辆，因为拍不到车子拿手机欺骗一下，好使
以上这篇python+opencv+caffe+摄像头做目标检测的实例代码就是小编分享给大家的全部内容了，希望能给大家一个参考，也希望大家多多支持。