OpenCV iOS 开发笔记

GITHUB:https://github.com/endpang/opencvdemo

实现了寻找边缘和自定义上色。

  • 添加opencv.framework后编译报错
Expected identifier

解决办法

把 NO 改为
NO_EXPOSURE_COMPENSATOR = 0
  • opencv 依赖的库
libc++.tbd
AVFoundation.framework
CoreImage.framework
CoreGraphics.framework
QuartzCore.framework
Accelerate.framework

//摄像头
CoreVideo.framework
CoreMedia.framework
AssetsLibrary.framework
#import "ViewController.h"
#import <opencv2/opencv.hpp>
#import <opencv2/videoio/cap_ios.h>

//@interface ViewController ()


@interface ViewController ()<CvVideoCameraDelegate>{
    UIImageView *cameraView;
    CvVideoCamera *videoCamera;
}
@end

@implementation ViewController

- (void)viewDidLoad {
    [super viewDidLoad];
    // Do any additional setup after loading the view, typically from a nib.
    cameraView = [[UIImageView alloc] initWithFrame:self.view.frame];
    [self.view addSubview:cameraView];
    
    videoCamera = [[CvVideoCamera alloc] initWithParentView:cameraView];
    videoCamera.defaultAVCaptureDevicePosition = AVCaptureDevicePositionFront;
    videoCamera.defaultAVCaptureSessionPreset = AVCaptureSessionPreset1920x1080;
    videoCamera.defaultAVCaptureVideoOrientation = AVCaptureVideoOrientationPortrait;
    videoCamera.defaultFPS = 60;
    videoCamera.grayscaleMode = NO;
    videoCamera.delegate = self;
}
- (void)viewDidAppear:(BOOL)animated {
    [super viewDidAppear:animated];
    [videoCamera start];
}

- (void)viewWillDisappear:(BOOL)animated {
    [super viewWillDisappear:animated];
    [videoCamera stop];
}

#pragma mark -  CvVideoCameraDelegate
- (void)processImage:(cv::Mat&)image {
    //在这儿我们将要添加图形处理的代码
    cv::Mat image_copy;
    //首先将图片由RGBA转成GRAY
    cv::cvtColor(image, image_copy, cv::COLOR_BGR2GRAY);
    //反转图片
    cv::bitwise_not(image_copy, image_copy);
    //将处理后的图片赋值给image,用来显示
    cv::cvtColor(image_copy, image, cv::COLOR_GRAY2BGR);
}


- (void)didReceiveMemoryWarning {
    [super didReceiveMemoryWarning];
    // Dispose of any resources that can be recreated.
}

plist 里加入  Privacy – Camera Usage Description

服务器端代码

8000 端口的服务是 https://github.com/lllyasviel/style2paints

k.png 是一张纯白色 png

<?php
/**/
//print_R($_FILES);
$imgname = $_FILES['upload1']['name'];
$tmp = $_FILES['upload1']['tmp_name'];
$filepath = 'photo/';
if(move_uploaded_file($tmp,$filepath.$imgname)){
    //echo "上传成功";
    my_post($filepath.$imgname);
}else{
    echo "上传失败";
}
//*/
//my_post("photo/20180118172008.png");
function my_post($filename){
    $url = "http://172.18.100.205:8000/paint";

    $headers[] = 'Origin: http://172.18.100.205:8000';
    $headers[] = 'Accept-Encoding: gzip, deflate';
    $headers[] = 'Accept-Language: zh-CN,zh;q=0.9,en;q=0.8';
    $headers[] = 'User-Agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_12_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/63.0.3239.132 Safari/537.36';
    $headers[] = 'Content-Type: application/x-www-form-urlencoded;';
    $headers[] = 'Accept: */*';
    $headers[] = 'Referer: http://172.18.100.205:8000/';
    $headers[] = 'Cookie: scale=2; style=photo; noise=2';
    $headers[] = 'Connection: keep-alive';
    //$post_data = array ("username" => "bob","key" => "12345");
    $ch = curl_init();
    $post_data = [];
    $post_data["sketchDenoise"] = "true";
    $post_data["resultDenoise"] = "true";
    $post_data["algrithom"] = "quality";
    $post_data["method"] = "colorize";
    $post_data["sketchID"] = "new";
    $post_data["referenceID"] = "no";
    //$b6 = "data%3Aimage%2Fpng%3Bbase64%2C";
    $b5 = "data:image/jpeg;base64,";
    $b6 = "data:image/png;base64,";
    //echo base64_encode($b6);
    $post_data["hint"] = $b6.base64_encode(file_get_contents("k.png"));
    $post_data["reference"] ="null" ;//$b6.base64_encode(file_get_contents("108_copy.png"));
    //$post_data["reference"] = null;
    $post_data["sketch"] = $b6.base64_encode(file_get_contents($filename));
    curl_setopt($ch, CURLOPT_HTTPHEADER, $headers);
    curl_setopt($ch, CURLOPT_URL, $url);
    curl_setopt($ch, CURLOPT_RETURNTRANSFER, 1);
    // post数据
    curl_setopt($ch, CURLOPT_POST, 1);
    // post的变
    //echo $post_data["sketch"];
    //print_R(http_build_query($post_data));
    curl_setopt($ch, CURLOPT_POSTFIELDS, http_build_query($post_data));

    $output = curl_exec($ch);
    $out_array = explode('*',$output);

    curl_close($ch);
    echo "http://172.18.100.205:8000/results/".$out_array[0].".jpg";
    //print_R($output);
}

No module named ‘skimage’   (python3)

apt install . python3-skimage

视频物体分割–One-Shot Video Object Segmentation

git clone git@github.com:fperazzi/davis-2017.git

./configure.sh && make -C build/release

pip install virtualenv virtualenvwrapper
source /usr/local/bin/virtualenvwrapper.sh
mkvirtualenv davis
pip install -r python/requirements.txt
export PYTHONPATH=$(pwd)/python/lib

example

cd python/experiments
python read_write_segmentation.py

报错

Traceback (most recent call last):
  File "read_write_segmentation.py", line 20, in <module>
    from   davis import cfg,io,DAVISLoader
  File "/root/game/davis-2017/python/lib/davis/__init__.py", line 13, in <module>
    from misc import log     # Logger
ImportError: No module named 'misc'

./python/lib/davis/misc/config.py

./python/lib/davis/__init__.py

有一些文件引用错了,改之。。。又报错

[WARNING][11-01-2018 17:27:26] Temporal stability not available
Traceback (most recent call last):
  File "./python/experiments/read_write_segmentation.py", line 23, in <module>
    db = DAVISLoader(year=cfg.YEAR,phase=cfg.PHASE)
  File "/root/game/davis-2017/python/lib/davis/dataset/loader.py", line 73, in __init__
    for s in self._db_sequences]
  File "/root/game/davis-2017/python/lib/davis/dataset/base.py", line 97, in __init__
    osp.join(cfg.PATH.SEQUENCES,name),regex)
  File "/root/game/davis-2017/python/lib/davis/dataset/base.py", line 78, in __init__
    self.name,len(self),cfg.SEQUENCES[self.name].num_frames))
Exception: Incorrect frames number for sequence 'bike-packing': found 0, expected 69.

原因是找不到文件

到data 目录下执行两个 sh 文件 1G 左右大小的文件。

get_davis_results.sh
get_davis.sh
python python/tools/visualize.py

按住空格或者回车键。

tensorflow 版本:https://github.com/scaelles/OSVOS-TensorFlow

OpenCV 去雾

import cv2
import numpy as np
  
def zmMinFilterGray(src, r=7):
    '''最小值滤波,r是滤波器半径'''
    '''if r <= 0:
        return src
    h, w = src.shape[:2]
    I = src
    res = np.minimum(I  , I[[0]+range(h-1)  , :])
    res = np.minimum(res, I[range(1,h)+[h-1], :])
    I = res
    res = np.minimum(I  , I[:, [0]+range(w-1)])
    res = np.minimum(res, I[:, range(1,w)+[w-1]])
    return zmMinFilterGray(res, r-1)'''
    return cv2.erode(src, np.ones((2*r+1, 2*r+1)))                      #使用opencv的erode函数更高效
def guidedfilter(I, p, r, eps):
    '''引导滤波,直接参考网上的matlab代码'''
    height, width = I.shape
    m_I = cv2.boxFilter(I, -1, (r,r))
    m_p = cv2.boxFilter(p, -1, (r,r))
    m_Ip = cv2.boxFilter(I*p, -1, (r,r))
    cov_Ip = m_Ip-m_I*m_p
  
    m_II = cv2.boxFilter(I*I, -1, (r,r))
    var_I = m_II-m_I*m_I
  
    a = cov_Ip/(var_I+eps)
    b = m_p-a*m_I
  
    m_a = cv2.boxFilter(a, -1, (r,r))
    m_b = cv2.boxFilter(b, -1, (r,r))
    return m_a*I+m_b
  
def getV1(m, r, eps, w, maxV1):  #输入rgb图像,值范围[0,1]
    '''计算大气遮罩图像V1和光照值A, V1 = 1-t/A'''
    V1 = np.min(m,2)                                         #得到暗通道图像
    V1 = guidedfilter(V1, zmMinFilterGray(V1,7), r, eps)     #使用引导滤波优化
    bins = 2000
    ht = np.histogram(V1, bins)                              #计算大气光照A
    d = np.cumsum(ht[0])/float(V1.size)
    for lmax in range(bins-1, 0, -1):
        if d[lmax]<=0.999:
            break
    A  = np.mean(m,2)[V1>=ht[1][lmax]].max()
          
    V1 = np.minimum(V1*w, maxV1)                   #对值范围进行限制
      
    return V1,A
  
def deHaze(m, r=81, eps=0.001, w=0.95, maxV1=0.80, bGamma=False):
    Y = np.zeros(m.shape)
    V1,A = getV1(m, r, eps, w, maxV1)               #得到遮罩图像和大气光照
    for k in range(3):
        Y[:,:,k] = (m[:,:,k]-V1)/(1-V1/A)           #颜色校正
    Y =  np.clip(Y, 0, 1)
    if bGamma:
        Y = Y**(np.log(0.5)/np.log(Y.mean()))       #gamma校正,默认不进行该操作
    return Y
  
if __name__ == '__main__':
    m = deHaze(cv2.imread('land.jpg')/255.0)*255
    cv2.imwrite('defog.jpg', m)

转自:https://www.cnblogs.com/zmshy2128/p/6128033.html

视频去雾

if __name__ == '__main__':
    cap = cv2.VideoCapture("1.mp4")
    while(1):
        ret, frame = cap.read()
        m = deHaze(frame/255.0)  #注意,这里不要乘 255
        cv2.imshow("yuan",frame)
        cv2.imshow("this",m)
        if cv2.waitKey(1) & 0xFF == ord('q'):
             break
cap.release()
cv2.destroyAllWindows()
安吉
感谢 @静静静姐姐 的照片

以太币私有链搭建教程

sudo apt-get update

sudo apt-get install software-properties-common

sudo add-apt-repository -y ppa:ethereum/ethereum

sudo add-apt-repository -y ppa:ethereum/ethereum-dev

sudo apt-get update

sudo apt-get install ethereum

geth #启动

创始块配置文件 piccgenesis.json

{
  "config": {
        "chainId": 10,
        "homesteadBlock": 0,
        "eip155Block": 0,
        "eip158Block": 0
    },
  "alloc"      : {},
  "coinbase"   : "0x0000000000000000000000000000000000000000",
  "difficulty" : "0x02000000",
  "extraData"  : "",
  "gasLimit"   : "0x2fefd8",
  "nonce"      : "0x0000000000000042",
  "mixhash"    : "0x0000000000000000000000000000000000000000000000000000000000000000",
  "parentHash" : "0x0000000000000000000000000000000000000000000000000000000000000000",
  "timestamp"  : "0x00"
}

mixhash

与nonce配合用于挖矿,由上一个区块的一部分生成的hash。注意他和nonce的设置需要满足以太坊的Yellow paper, 4.3.4. Block Header Validity, (44)章节所描述的条件。.
nonce nonce就是一个64位随机数,用于挖矿,注意他和mixhash的设置需要满足以太坊的Yellow paper, 4.3.4. Block Header Validity, (44)章节所描述的条件。
difficulty 设置当前区块的难度,如果难度过大,cpu挖矿就很难,这里设置较小难度
alloc 用来预置账号以及账号的以太币数量,因为私有链挖矿比较容易,所以我们不需要预置有币的账号,需要的时候自己创建即可以。
coinbase 矿工的账号,随便填
timestamp 设置创世块的时间戳
parentHash 上一个区块的hash值,因为是创世块,所以这个值是0
extraData 附加信息,随便填,可以填你的个性信息
gasLimit 该值设置对GAS的消耗总量限制,用来限制区块能包含的交易信息总和,因为我们是私有链,所以填最大。
geth  --datadir "Your/Path" init piccgenesis.json

创建数据存放地址并初始化创世块

geth --identity "YourName"  --rpc  --rpccorsdomain "*" --datadir "Your/Path" --port "30303"  --rpcapi "db,eth,net,web3" --networkid  95518  console

#如果nohup 请去掉 console

从第二个节点连接。创建目录并将piccgenesis.json拷贝进去。

geth --datadir . init ./piccgenesis.json  #初始化目录
geth --datadir . --networkid 95518 --ipcdisable --port 61911 --rpcport 8101 --bootnodes "enode://8a0127669dc890530d868aa2a08efaff12933c885da21882ed935f563b7cdb7aa3497aa24807bc348c143017dba4c4433d97e64571a1962e257726a7c0725ed8@172.18.100.205:8888" console

创建账号

personal.newAccount()

#启动挖矿
miner.start()

#查看账户余额,不为零即已经在挖矿了
eth.getBalance(eth.accounts[0])

显卡挖矿

下载二进制安装包

https://github.com/ethereum-mining/ethminer/releases

或(注意两种安装方式的命令不一样,请  -h 查看)

apt-get install ethminer
ethminer -G

解锁账户

personal.unlockAccount("0x00530bc8552639fd8479c22f403e84fe5e98896f","===pwd===")

转账3以太币

eth.sendTransaction({from:"0x00530bc8552639fd8479c22f403e84fe5e98896f",to:"0xa6993059b5a31e53f4df0e84a59ccf13abf86b86",value:web3.toWei(3,"ether")})

矿池挖矿

./ethminer --farm-recheck 2000 -G -S us2.ethpool.org:3333 -FS us1.ethpool.org:3333 -O 0x550ce8f9cacae8d5137feb704fbfa45e213bcd30

 

CBB(抄币币)的创世节点:enode://3251729f9c8622826f9a94c40c6f8566505ffd2f34771f77468797858cae8f16b7e7b923a694431f14815b7460c910349d981801a2637a30a8bc503eedee781d@13.115.164.167:30303

配置文件:

 
{
        "config": {
                "chainId": 10,
                        "homesteadBlock": 0,
                        "eip155Block": 0,
                        "eip158Block": 0
        },
                "alloc"      : {},
                "coinbase"   : "0x0000000000000000000000000000000000000000",
                "difficulty" : "0x020000",
                "extraData"  : "",
                "gasLimit"   : "0x2fefd8",
                "nonce"      : "0x0000000000000042",
                "mixhash"    : "0x0000000000000000000000000000000000000000000000000000000000000000",
                "parentHash" : "0x0000000000000000000000000000000000000000000000000000000000000000",
                "timestamp"  : "0x00"
}

OpenCV 实时景深

#coding=utf-8
import cv2
import numpy as np
import usb.core
import usb.backend.libusb1
import requests
import time
from matplotlib import pyplot as plt

cap = cv2.VideoCapture(1)
backend = usb.backend.libusb1.get_backend(find_library=lambda x: "/usr/lib/libusb-1.0.so")
 # 
dev = usb.core.find(idVendor=0x18e3, idProduct=0x5031, backend=backend)
dev.ctrl_transfer(0x21,0x01,0x0800,0x0600,[0x50,0xff])
dev.ctrl_transfer(0x21,0x01,0x0f00,0x0600,[0x00,0xf6])
dev.ctrl_transfer(0x21,0x01,0x0800,0x0600,[0x25,0x00])
dev.ctrl_transfer(0x21,0x01,0x0800,0x0600,[0x5f,0xfe])
dev.ctrl_transfer(0x21,0x01,0x0f00,0x0600,[0x00,0x03])
dev.ctrl_transfer(0x21,0x01,0x0f00,0x0600,[0x00,0x02])
dev.ctrl_transfer(0x21,0x01,0x0f00,0x0600,[0x00,0x12])
dev.ctrl_transfer(0x21,0x01,0x0f00,0x0600,[0x00,0x04])
dev.ctrl_transfer(0x21,0x01,0x0800,0x0600,[0x76,0xc3])
dev.ctrl_transfer(0x21,0x01,0x0a00,0x0600,[4,0x00])   

firstFrame = None
window_size = 0 
while(1):
        ret, frame = cap.read()
        frame = cv2.resize(frame, (1280, 480), interpolation=cv2.CV_8SC1)
        #cv2.cvtColor(frame, frame, cv2.COLOR_BGR2GRAY);
        frame_left_old = frame[0:480,0:640] 
        frame_left = cv2.cvtColor(frame_left_old,  cv2.COLOR_BGR2GRAY);
        frame_right_old = frame[0:480,640:1280]
        frame_right = cv2.cvtColor(frame_right_old,  cv2.COLOR_BGR2GRAY);
        #stereo = cv2.StereoBM_create(numDisparities=32, blockSize=15)
        stereo = cv2.StereoSGBM_create(minDisparity = 16,
            numDisparities = 64,
            blockSize = 16,
            P1 = 8*3*window_size**2,
            P2 = 32*3*window_size**2,
            disp12MaxDiff = 1,
            uniquenessRatio = 10,
            speckleWindowSize = 100,
            speckleRange = 32
        )
        disparity = stereo.compute(frame_left,frame_right)
        disp = cv2.normalize(disparity, disparity, alpha=0, beta=255, norm_type=cv2.NORM_MINMAX, dtype=cv2.CV_8U)
        cv2.imshow("h",disp)
        #plt.imshow(disparity,'gray')
        #plt.show()
        if cv2.waitKey(1) & 0xFF == ord('q'):
                break
cap.release()
cv2.destroyAllWindows()

最新文件在 : https://github.com/endpang/driverless

disparity.py   图片调参
disparity_video.py   视频取图调参

这两个文件是调节摄像头的。其实应该用严格标定,懒得麻烦的,可以用这个工具简单表定下。

left_or_right.py  测试

其中minDisparity是控制匹配搜索的第一个参数,代表了匹配搜苏从哪里开始,numberOfDisparities表示最大搜索视差数uniquenessRatio表示匹配功能函数

机器找不到 libcudnn.so.6

Traceback (most recent call last):
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/pywrap_tensorflow.py", line 58, in <module>
    from tensorflow.python.pywrap_tensorflow_internal import *
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 28, in <module>
    _pywrap_tensorflow_internal = swig_import_helper()
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 24, in swig_import_helper
    _mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)
  File "/usr/lib/python3.5/imp.py", line 242, in load_module
    return load_dynamic(name, filename, file)
  File "/usr/lib/python3.5/imp.py", line 342, in load_dynamic
    return _load(spec)
ImportError: libcudnn.so.6: cannot open shared object file: No such file or directory

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/__init__.py", line 24, in <module>
    from tensorflow.python import *
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/__init__.py", line 49, in <module>
    from tensorflow.python import pywrap_tensorflow
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/pywrap_tensorflow.py", line 72, in <module>
    raise ImportError(msg)
ImportError: Traceback (most recent call last):
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/pywrap_tensorflow.py", line 58, in <module>
    from tensorflow.python.pywrap_tensorflow_internal import *
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 28, in <module>
    _pywrap_tensorflow_internal = swig_import_helper()
  File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/pywrap_tensorflow_internal.py", line 24, in swig_import_helper
    _mod = imp.load_module('_pywrap_tensorflow_internal', fp, pathname, description)
  File "/usr/lib/python3.5/imp.py", line 242, in load_module
    return load_dynamic(name, filename, file)
  File "/usr/lib/python3.5/imp.py", line 342, in load_dynamic
    return _load(spec)
ImportError: libcudnn.so.6: cannot open shared object file: No such file or directory


Failed to load the native TensorFlow runtime.

See https://www.tensorflow.org/install/install_sources#common_installation_problems

.bashrc 中加入

export LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH

srez – super-resolution

https://github.com/david-gpu/srez

python3 srez_main.py --run demo.

报错

Traceback (most recent call last):
  File "/usr/local/lib/python3.5/dist-packages/imageio/plugins/ffmpeg.py", line 82, in get_exe
    auto=False)
  File "/usr/local/lib/python3.5/dist-packages/imageio/core/fetching.py", line 102, in get_remote_file
    raise NeedDownloadError()
imageio.core.fetching.NeedDownloadError

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "srez_main.py", line 1, in <module>
    import srez_demo
  File "/root/srez/srez_demo.py", line 1, in <module>
    import moviepy.editor as mpe
  File "/usr/local/lib/python3.5/dist-packages/moviepy/editor.py", line 22, in <module>
    from .video.io.VideoFileClip import VideoFileClip
  File "/usr/local/lib/python3.5/dist-packages/moviepy/video/io/VideoFileClip.py", line 3, in <module>
    from moviepy.video.VideoClip import VideoClip
  File "/usr/local/lib/python3.5/dist-packages/moviepy/video/VideoClip.py", line 21, in <module>
    from .io.ffmpeg_writer import ffmpeg_write_image, ffmpeg_write_video
  File "/usr/local/lib/python3.5/dist-packages/moviepy/video/io/ffmpeg_writer.py", line 11, in <module>
    from moviepy.config import get_setting
  File "/usr/local/lib/python3.5/dist-packages/moviepy/config.py", line 35, in <module>
    FFMPEG_BINARY = get_exe()
  File "/usr/local/lib/python3.5/dist-packages/imageio/plugins/ffmpeg.py", line 86, in get_exe
    raise NeedDownloadError('Need ffmpeg exe. '
imageio.core.fetching.NeedDownloadError: Need ffmpeg exe. You can download it by calling:
  imageio.plugins.ffmpeg.download()

修改

srez_demo.py

最上面加两行

import imageio
imageio.plugins.ffmpeg.download()

新建 checkpoint 文件夹,重新运行。

报错

Traceback (most recent call last):
 File "srez_main.py", line 190, in <module>
 tf.app.run()
 File "/usr/local/lib/python3.5/dist-packages/tensorflow/python/platform/app.py", line 48, in run
 _sys.exit(main(_sys.argv[:1] + flags_passthrough))
 File "srez_main.py", line 185, in main
 _demo()
 File "srez_main.py", line 113, in _demo
 sess, summary_writer = setup_tensorflow()
 File "srez_main.py", line 103, in setup_tensorflow
 summary_writer = tf.train.SummaryWriter(FLAGS.train_dir, sess.graph)
AttributeError: module 'tensorflow.python.training.training' has no attribute 'SummaryWriter'

升级 tensorflow-gpu
/usr/bin/pip3 install –upgrade tensorflow-gpu

又报错

ImportError: libcudnn.so.6: cannot open shared object file: No such file or directory

参考 这篇文章

 

OpenCV 动态检测

10000 是检测灵敏度阈值,根据需要调整灵敏度。

#coding=utf-8
import cv2
import numpy as np
import usb.core
import usb.backend.libusb1
import requests
import time

cap = cv2.VideoCapture(1)
backend = usb.backend.libusb1.get_backend(find_library=lambda x: "/usr/lib/libusb-1.0.so")
 # 
dev = usb.core.find(idVendor=0x18e3, idProduct=0x5031, backend=backend)
dev.ctrl_transfer(0x21,0x01,0x0800,0x0600,[0x50,0xff])
dev.ctrl_transfer(0x21,0x01,0x0f00,0x0600,[0x00,0xf6])
dev.ctrl_transfer(0x21,0x01,0x0800,0x0600,[0x25,0x00])
dev.ctrl_transfer(0x21,0x01,0x0800,0x0600,[0x5f,0xfe])
dev.ctrl_transfer(0x21,0x01,0x0f00,0x0600,[0x00,0x03])
dev.ctrl_transfer(0x21,0x01,0x0f00,0x0600,[0x00,0x02])
dev.ctrl_transfer(0x21,0x01,0x0f00,0x0600,[0x00,0x12])
dev.ctrl_transfer(0x21,0x01,0x0f00,0x0600,[0x00,0x04])
dev.ctrl_transfer(0x21,0x01,0x0800,0x0600,[0x76,0xc3])
dev.ctrl_transfer(0x21,0x01,0x0a00,0x0600,[4,0x00])   

firstFrame = None

while(1):
        ret, frame = cap.read()
        frame = cv2.resize(frame, (1280, 480), interpolation=cv2.INTER_CUBIC)
        frame_left = frame[0:480,0:640]
        frame_right = frame[0:480,640:1280]
        gray = cv2.cvtColor(frame_left, cv2.COLOR_BGR2GRAY)         
        gray = cv2.GaussianBlur(gray, (21, 21), 0)
        if firstFrame is None:  
            firstFrame = gray
            continue
    
        frameDelta = cv2.absdiff(firstFrame, gray)
        thresh = cv2.threshold(frameDelta, 25, 255, cv2.THRESH_BINARY)[1] 
        thresh = cv2.dilate(thresh, None, iterations=2)
        (_, cnts, _) = cv2.findContours(thresh.copy(), cv2.RETR_CCOMP, cv2.CHAIN_APPROX_SIMPLE)
       
        g = frame.copy()
        ii = 0
        for c in cnts:
            if cv2.contourArea(c) < 10000:
                continue
            ii = 1
            #(x, y, w, h) = cv2.boundingRect(c)
            #print (cv2.contourArea(c))
            #cv2.rectangle(g, (x, y), (x + w, y + h), (0, 255, 0), 2)
        if ii == 1:
            url = "http://br.bj.oupeng.com:10080"
            t = time.time()
            cv2.imwrite("./"+str(t)+".jpg", g)
            files = {'file123':(str(t)+'.png',open("./"+str(t)+".jpg",'rb'))}
            data = {'time',str(t)}
            r = requests.post(url, files=files )#, data = data)
            print(r.text)
        cv2.imshow("br",g)
        firstFrame = gray.copy() 
        ##去掉绿色通道,生成红蓝图
        #zeros = np.zeros(frame_2.shape[:2], dtype = "uint8")
        #merged = cv2.merge([b,zeros,r2])  
        #cv2.imshow("br",merged)  
        
        if cv2.waitKey(1) & 0xFF == ord('q'):
                break
cap.release()
cv2.destroyAllWindows()

TOF python 实现

看了下  lighthouse ,图漾景深摄像头的原理。似乎是用 tof(time of fly) 和 光流实现的。

模拟一下

import cv2
import numpy as np
cap = cv2.VideoCapture(0)

ret, frame1 = cap.read()
prvs = cv2.cvtColor(frame1,cv2.COLOR_BGR2GRAY)
hsv = np.zeros_like(frame1)
hsv[...,1] = 255

while(1):
    ret, frame2 = cap.read()
    next = cv2.cvtColor(frame2,cv2.COLOR_BGR2GRAY)

    flow = cv2.calcOpticalFlowFarneback(prvs,next, None, 0.5, 3, 15, 3, 5, 1.2, 0)

    mag, ang = cv2.cartToPolar(flow[...,0], flow[...,1])
    hsv[...,0] = ang*180/np.pi/2
    hsv[...,2] = cv2.normalize(mag,None,0,255,cv2.NORM_MINMAX)
    rgb = cv2.cvtColor(hsv,cv2.COLOR_HSV2BGR)

    cv2.imshow('frame2',rgb)
    k = cv2.waitKey(30) & 0xff
    if k == 27:
        break
    elif k == ord('s'):
        cv2.imwrite('opticalfb.png',frame2)
        cv2.imwrite('opticalhsv.png',rgb)
    prvs = next

cap.release()
cv2.destroyAllWindows()

效果:

视频地址:https://m.youtube.com/watch?v=5jur04bJDkM&feature=youtu.be