blur image python opencv

1. An image with a face looks clear when we are able to identify eyes, ears, nose, lips, forehead e.t.c very clear. High Level Steps: There are two steps to this process: The OpenCV python module use kernel to blur the image. img = cv2.imread ('bat.jpg') blurImg = cv2.blur (img, (10,10)) cv2.imshow ('blurred image',blurImg) cv2.waitKey (0) cv2.destroyAllWindows () Output: Now, this program above is using image blurring … e.g., I found that with an 255 x 512 array, cv2.blur was on average 0.008 seconds faster than ndimage.convolve as used above (tested on n = 50 different arrays)---and of course that scales for your larger images. What you basically have to do is isolate only specific color ranges from your image. Although images are saved as files here, if you want to display them in another window, you can use cv2.imshow() (eg: cv2.imshow('window_name', dst) ). There are many functions in OpenCV that allow you to manipulate your input image. cv2.Gaussianblur () is one of them. It allows you to blur images that are very helpful while processing your images. python blur_detection.py -i images -t 100. Figure 8: Basic blur detection with OpenCV and Python. The Sobel derivative filter. In this article, you will learn how to simply segment an object from an image based on color in Python using OpenCV. And kernel tells how much the given pixel value should be changed to blur the image. One of the common technique is using Gaussian filter (Gf) for image blurring. cv2.blur () method is used to blur an image using the normalized box filter. To get started, installed required dependencies: pip3 install opencv-python numpy. This operation processes the edges while removing the noise. This is done by convolving an image with a normalized box filter. Visualizing image derivatives with OpenCV. To read an image in Python using OpenCV, use cv2.imread() function. It is one of the most widely used tools for computer vision and image processing tasks. Output result. Invert the grayscale image to get a negative. In this article, you will learn how to simply segment an object from an image based on color in Python using OpenCV. Weight superposition. In OpenCV, image smoothing (also called blurring) could be done in many ways. OpenCV-Python is a library of Python bindings designed to solve computer vision problems. Image f iltering functions are often used to pre-process or adjust an image before performing more complex operations. If the result is below the threshold value, we perceive it as “blurry”. Create a blurred image frame. Code for How to Blur Faces in Images using OpenCV in Python Tutorial. In general, the threshold value gives very good results at 100. https://docs.opencv.org/3.4/d1/dfd/tutorial_motion_deblur_filter.html Also, you can blur an image using cv2.filter2D (). You can perform this operation on an image using the medianBlur() method of the imgproc class. The function smooths an image using the kernel which is represented as: src: It is the image whose is to be blurred. ksize: A tuple representing the blurring kernel size. dst: It is the output image of the same size and type as src. The USM sharpening formula is expressed as follows: (source image - w* Gauss blur) / (1-w); where w indicates weight (0.1 to 0.9), default is 0.6. It has the result of smoothing out image noise and reducing detail. Resizing does only change the width and height of the image. OpenCV allows us to perform multiple operations on the image, but to do that it is necessary to read an image file as input, and then we can perform the various operations on it. OpenCV is a Python open-source library, which is used for computer vision in Artificial intelligence, Machine Learning, face recognition, etc. Summary. Combine the blurred with original frame based on … So edges are blurred a little bit in this operation (there are also blurring techniques which don't blur the edges). This is done by convolving the image with a normalized box filter. If you start playing around with computer vision there are a couple of surprises waiting. The Gaussian Blur filter smooths an image by averaging pixel values with its neighbors. Digital Image Processing using OpenCV (Python & C++) Highlights: In this post, we will learn how to apply and use an Averaging and a Gaussian filter.We will also explain the main differences between these filters and how they affect the output image. In this opencv project, we’ve developed an image cartoonizer application using python. Image Smoothing using OpenCV Gaussian Blur. You can read image as a grey scale, color image or image with transparency. Image Smoothing techniques help in reducing the noise. Importing libraries. import cv2 Now to read the image, use the imread() method of the cv2 module, specify the path to the image in the arguments and store the image in a variable as below: blur detection using opencv. 1.Read an image. OpenCV Python – Rotate Image We can rotate an image using OpenCV to any degree. In blurring, we simple blur an image. March 23, 2021 cocyer. And with Python and OpenCV we can detect faces and blur them within few lines of code. Laplacian - yet another edge detection technique. Rotate an Image. We did a little project for blur detection using OpenCV … The Gaussian filter is a low-pass filter that removes the h Let’s have some fun with some images! We specify 4 arguments (more details, check the Reference): src: Source image. OpenCV 3 Python blur detection. Image processing finds a crucial place in the deep learning domain with the growing size of image and video data and the increase in digital solution needs. OpenCV is one of the famously used open-source Python libraries meant exclusively for Computer Vision. As Lines 22-24 show, we blur our image with increasing sizes kernels. We’re going to learn in this video how to detect when an Image is blurry using Opencv with Python. But how to determine if captured picture is in focus after it has been taken. OpenCV – Open Source Computer Vision. Although images are saved as files here, if you want to display them in another window, you can use cv2.imshow() (eg: cv2.imshow('window_name', dst) ). Installing Sample App / OpenCV Manager. 12 min read. So, currently, I am working on a large project for ASL (American Sign Language) recognitionusing deep learning for computer vision. Best Practice to Implement Image Median Blur in Python OpenCV. Creating a pixelated face blur with OpenCV Figure 8: Creating a pixelated face effect on an image with OpenCV and Python (image source). This degradation is caused by external sources. An NCSU Libraries Workshop. You will find many algorithms using it before actually processing the image. Python Program to Blend Two Images - Using OpenCV library, you can add or blend two images with the help of cv2.addWeighted() method. How do you blur an image in Python? Why do we blur image? In blurring, we simple blur an image. That said, cv2.blur is marginally faster (it's written C++). I did a bit of research and found out that edge detection might … Python Tutorials: In this article, we will learn image filtering techniques using OpenCV in python. The only amount of blur in this image comes from Jemma wagging her tail. pip install opencv-python Now OpenCV is installed successfully and we are ready. Drawing and Writing on Image OpenCV Python Tutorial. // Import the core header file #include // core - a compact module defining basic data structures, // including the dense multi-dimensional array Mat and // basic functions used by all other modules. For example. OpenCV is one of the famously used open-source Python libraries meant exclusively for Computer Vision. The reported focus measure is lower than Figure 7, but we are still able to correctly classify the image … Today we will be Applying Gaussian Smoothing to an image using Python from scratch and not using library like OpenCV. Posted on 2015-04-06 by admin. The height and width of the kernel should be a positive and an odd number. With this, any sharp edges in images are smoothed while minimizing too much blurring. It's called a Gaussian Blur because the average has a Gaussian falloff effect. Hello, i want to blur specific regions (ellipses) of an image with smooth edges. To average blur an image, we use the cv2.blur function. The image is read as a numpy array, in which cell values depict R, G, and B values of a pixel. Let’s look at the code that we add in this function # Load the foreground input image foreground = cv2.imread(source) # Change the color of foreground image to RGB # and resize image to match shape of R-band in RGB output map foreground = … ... A Gaussian blur is an image filter that uses a kind of function called a Gaussian to transform each pixel in the image. The kernel size should be a positive odd integer. With a few changes, we can Blur Faces in real-time with Opencv, Mediapipe and Python. You can blur an image in Python using OpenCV cv2.blur () function. Median Filtering. Code implementation steps in OpenCV. But, cv2.blur () is a quick high level function for filtering action and performing an averaging. How can we apply gaussian blur to our images in Python using OpenCV? Image processing is extensively used in video datasets compared to image datasets. Today in this tutorial, we will be applying few of the filters to images. Our OpenCV tutorial includes all topics of Read and Save Image, Canny Edge Detection, Template matching, Blob Detection, Contour, Mouse Event, Gaussian blur and so on. Displaying the coordinates of the points clicked on the image using Python-OpenCV. To rotate an image using OpenCV Python, first calculate the affine matrix that does the affine transformation (linear mapping of pixels), then warp the input image with the affine matrix. Here, we crop out a smaller section of an image to better notice the image blurring operation. Image blurring is achieved by convolving the image with a low-pass filter kernel. Unresolved inclusions in OpenCV android tutorial 4. build openCV for android, without CUDA. In Python OpenCV Tutorial, Explained How to Blur image using cv2.GaussianBlur() opencv function. Open up a new file and import: import cv2 … on 2016-07-27. But how to determine if captured picture is in focus after it has been taken. OpenCV Read and Save Image OpenCV Reading Images. [Blend: How to Combine 2 Images?] All the previous procedure works on the single image, but as we know, on OpenCV, the video is a sequence of images. Let’s take two images a not blurry one and a blurry one: NOT BLURRY; BLURRY; What is a blurry image? dst: Destination image. Gaussian Blur is a smoothening technique which is used to reduce noise in an image. The cv2.blur () function takes in 2 parameters. OpenCV 3 Python blur detection. Go Image Operations OpenCV Python Tutorial. Image derivatives in two dimensions. Blur detection using OpenCV. These operations help reduce noise or unwanted variances of an image or threshold. Blurred. The larger our kernel becomes, the more blurred our image will appear. It simply takes the average of all the pixels under kernel area and replaces the central element with this average. Posted on 2015-04-06 by admin. (Nah, ada teknik blur yang tidak mengaburkan ujung). You can read more about it on Blur Documentation. How To. Image Smoothing using OpenCV Gaussian Blur As in any other signals, images also can contain different types of noise, especially because of the source (camera sensor). Ini akan benar-benar menghapus konten frekuensi tinggi (misalnya: noise, edge) dari gambar yang mengakibatkan tepi menjadi buram saat filter ini diterapkan. import cv2 img = cv2.imread("pyimg.jpg") 2.Create image gaussian blur For today’s tutorial, we will see how to blur someone’s face on video using OpenCV and Python (you can use the same technique on still images, but since there are a … Taking a look at the two images above we can easily affirm that the second image is blurry while the first is not. OpenCV - Gaussian Blur - In Gaussian Blur operation, the image is convolved with a Gaussian filter instead of the box filter. I wanted to anonymize the people’s identity by blurring their faces so for that I used the deadly combination of the old but highly esteemed technology, which are OpenCV with Python 3.Hence I used the Haar Cascade file to detect the faces and then implemented the preexisting blurring method of OpenCV to blur those detected faces. We blur images with OpenCV using the cv2.blur () function. How do you blur part of a picture? imutils also check to find functions if you already have NumPy, SciPy, Matplotlib, and OpenCV installed. import cv2 img = cv2.imread("pynoise.png") For example, I am using the width of 5 and a height of 55 to generate the blurred image. Using Gaussian filter/kernel to smooth/blur an image is a very important tool in Computer Vision. In this tutorial, we will use cv2.medianBlur() to implement image media blur. Following is the link to its documentation, which is fairly Browse other questions tagged python opencv image-processing motion-blur or ask your own question. It is a widely used effect in graphics software, typically to reduce image noise and reduce detail. We have chosen three different sizes for the filter to demonstrate that the output image will become more blurred as the filter size increases. The aspect ratio can be … It is extremely effective for the salt-and-paper noise in the image. # 100*100 one_mat_100_100 = np.ones((100,100), dtype=np.float32)/10000 blur_img_100_100 = cv2.filter2D(img, -1, one_mat_100_100) cv2.imshow("Original Image", img) cv2.imshow("Blure Image using", blur_img_100_100) cv2.waitKey(0) cv2.destroyAllWindows() Python OpenCV package provides ways for image smoothing also called blurring. feature to determine image too dark opencv. $ python blur_detector_image.py --image images/adrian_01.png [INFO] Not Blurry (42.4630) Figure 3: Using Python and OpenCV to determine if a photo is blurry in conjunction with the Fast Fourier Transform (FFT) algorithm. You can learn how to do from this tutorial. ksize: Gaussian kernel size. One of the common technique is using Gaussian filter (Gf) for image blurring. We’ll be using the following libraries of python. Examples provide situations where we use kernels of different shapes and its effect on the blur in the output. Following is a quick code snippet that blurs an image img_src with the kernel of shape (5, 5) and returns the blurred image. In the above statement, we store the blurred image in img_rst. OpenCV imread function Using the --test routine of our Python blurriness detector script, we’ve applied a series of intentional … This degradation is caused by external sources. // Title: OpenCV C++ Program to blur an image. You can find the ratio of a specific color in an image using image processing. Deblur image opencv python. Luckily for us, I already wrote a tutorial on face detection, we'll only be using its source code, feel free to check it out for further detail on how the face detection code works. OpenCV-Python is a library of Python bindings designed to solve computer vision problems. cv2.blur () method is used to blur an image using the normalized box filter. The function smooths an image using the kernel which is represented as: src: It is the image whose is to be blurred. ksize: A tuple representing the blurring kernel size. And it finished. In order to blur faces shown in images, you need to first detect these faces and their position in the image. This is what we are going to do in this section. Blur-and-anonymize-faces-with-OpenCV-and-Python import the necessary packages import the necessary packages construct the argument parse and parse the arguments load our serialized face detector model from disk load the input image from disk, clone it, and grab the image spatial dimensions construct a blob from the image pass the blob through the network and obtain the … Then you have to specify the X and Y direction that is sigmaX and sigmaY respectively. OpenCV Image Cartooning Output. If you start playing around with computer vision there are a couple of surprises waiting. While working on the project, I found that training the neural network on the direct RGB images of sign language did not produce the best results. You can perform this operation on an image using the medianBlur () method of the imgproc class. In this tutorial, we shall learn how to rotate an image to 90, 180 and 270 degrees in OpenCV Python with an example. OpenCV has a vast number of functions for working with images and videos with the ultimate object of using it to build and train image recognition models, however on my first foray into the world of OpenCV and particularly working with images it gives Python another great option for manipulating and processing images. Projects. The Median blur operation is similar to the other averaging methods. It actually removes high frequency content (eg: noise, edges) from the image. Let’s first change the source of data acquisition There are only two arguments required: an image that we want to blur and the size of the filter. To make an image blurry, you can use the GaussianBlur() method of OpenCV. Blurring an Image Using OpenCV’s Built-In Function. So, here is a very simple program with basically the same result. Blurring or S moothing Out Images — OpenCV OpenCV python code for blurring an image using kernel or filter with the basic concepts of convolution, low pass filter, frequency of image, etc. Taking img_RGB, we copy its bottom right part as img_small using NumPy array slicing: img_small = img_RGB[4000:, 2000:] That will create a smaller image of size (1563, 1709, 3). ... A Gaussian blur is an image filter that uses a kind of function called a Gaussian to transform each pixel in the image. Why you should blur an image before processing it using OpenCV and Python. OpenCV provides the medianblur () function to perform the blur operation. This is what we are going to do in this section. Essentially a convenience function, use it to blur images, where you need not specifically define a kernel. Blend the grayscale image from step 1 with the blurred negative from step 3 using a color dodge. There are three filters available in the OpenCV-Python library. With this, any sharp edges in images are smoothed while minimizing too much blurring. $ python detect_blur.py --images images Figure 4: Correctly marking the image as “blurry”. Image noise and edge detection. Image Smoothing techniques help in reducing the noise. The Canny edge detector. Here we will use OpenCV to perform our task efficiently. In this tutorial, we will use an example to show you how to do. In this tutorial, we will learn how to blur an image using cv2.blur () function with examples. dst: output image of the same size and type as src. You will find many algorithms using it before actually processing the image. Learn Image Blurring techniques, Gaussian Blur, Bilateral Blurring Technique. Opencv python , Blurry object detection in messy background. Image processing finds a crucial place in the deep learning domain with the growing size of image and video data and the increase in digital solution needs. The above code can be modified for Gaussian blurring: blur = cv2.GaussianBlur OpenCV Python Image Smoothing – Gaussian Blur Image Smoothing using OpenCV Gaussian Blur As in any other signals, images also can contain different types of noise, especially because of the source (camera sensor). Image Smoothing techniques help in reducing the noise. I'm using OpenCV to preprocess the image for better recognition, applying a Gaussian blur and a Threshold method for binarization, but the result is pretty bad. OpenCV Paths Headaches in Eclipse. Cartooning an Image using OpenCV – Python; OpenCV C++ Program for Face Detection; Opencv Python program for Face Detection; Face Detection using Python and OpenCV with webcam; ... scale and then we apply the media blur filter. dst - destination array of the same size and type as src. Metode Median Filtering Menggunakan OpenCV Python. Blurring an image. This shape of an object is due to its edges. # read image from the PC initial_img=Image.open('my_image.jpg') img = cv.imread('my_image.jpg') gray = cv.cvtColor(img, cv.COLOR_BGR2GRAY) Face Detection Videos In OpenCV This post is a practical example of how we can use OpenCV with Python for detecting faces in a … This function requires two arguments: the image we want to blur and the size of the kernel. Noise in digital images is a random variation of brightness or colour information. Blend: How to Combine 2 Images? An image looks sharper or more detailed if we are able to perceive all the objects and their shapes correctly in it. Apply a Gaussian blur to the negative from step 2. Blending in OpenCV is joining two images of same size into each other. We can use cv2.GaussianBlur() to make image gaussian blur in python opencv. OpenCV provides following functions which are used to read and write the images. Make an image blurry Gaussian Blur. The code to get the blur filter on the image is shown below. This shape of an object is due to its edges. [Draw Shapes & Text on Image] [Draw a Polygon] [Blur an image] Pre Requesites: Jupyter or any python editor. In this Python tutorial, I will walk you through the Python code on How to blur Faces in an Image using Python OpenCV. Metode Gaussian Filtering dengan OpenCv Python. Syntax: cv2.GaussianBlur(src, ksize, sigmaX[, dst[, sigmaY[, borderType]]]) -> […] Python OpenCV package provides ways for image smoothing also called blurring. In order to detect if picture is in focus modern consumer cameras use complicated phase detection circuitry and specialized sensors. Using OpenCV, we can easily blur images so that the distinct image cannot be seen but merely a blurred version of the image. How To. Image blur detection in Python using imutils package. The Sobel detector - a basic framework for edge detection. import cv2. Detecting Faces in an image and blurring it is one of the most common applications of image and video processing with Machine Learning. In OpenCV, image smoothing (also called blurring) could be done in many ways. 1. The function smooths an image using the kernel which is represented as: Syntax: cv2.blur (src, ksize [, dst [, anchor [, borderType]]]) Parameters: src: It is the image whose is to be blurred. OpenCV DescriptorMatcher matches. In the middle of the picture, there is a blurry area on the region of the Black and white strip and I want to detect the area of it by using OpenCV python. Tutorial. In order to detect if picture is in focus modern consumer cameras use complicated phase detection circuitry and specialized sensors. Hello Everyone, Hope all you are well, Earlier in previous blog we have started with the basic of OpenCV… Simply specify the kernel size, using the ksize input argument, as shown in the code below. It is used in various applications such as face detection, video capturing, tracking moving objects, object disclosure, nowadays in Covid applications such as face mask detection, social distancing, and many more. Code: Python. Make a mask to get pixels of medium to high saturation and value (it seems to capture the foreground, as the background has lower saturation and value in the HSV color space. Before Blur and After Blur. blur_faces.py. Here is the the image I'm using for tests: And here the preprocessed image: What others filter can I use to make the image … Recently, I am looking for an object detection program to detect the area of the object in very similar color background. Using Gaussian filter/kernel to smooth/blur an image is a very important tool in Computer Vision. How do you blur an image in OpenCV Python? Blurring an image. Noise in digital images is a random variation of brightness or colour information. There are various image blurring functions in the OpenCV module. OpenCV 3 image and video processing with Python OpenCV 3 with Python Image - OpenCV BGR : Matplotlib RGB Basic image operations - pixel access iPython - Signal Processing with NumPy Signal Processing with NumPy I - FFT and DFT for sine, square waves, unitpulse, and random signal Signal Processing with NumPy II - Image Fourier Transform : FFT & DFT 14, Jul 20. It has the result of smoothing out image noise and reducing detail. Beginning with image transformations: To convert an image to a cartoon, multiple transformations are done. Reaching the end of this tutorial, we learned image smoothing techniques of Averaging, Gaussian Blur, and Median Filter and their python OpenCV implementation using cv2.blur() , cv2.GaussianBlur() and cv2.medianBlur(). To perform averaging in OpenCV we use both cv2.blur()and cv2.boxFilter() functions. What is OpenCV? Smoothing Images, getGaussianKernel(). This image is marked as “blurry”. RBarryYoung. Averaging ¶. So you might consider writing your code with both options -- e.g., in your import statements have something like: Here, the central element of the image is replaced by the median of all the pixels in the kernel area. OpenCV-2.4.2-android-sdk missing build.xml? Figure 7: Applying blur detection with OpenCV and Python. We can also expand the study with adding some additional features. Get the answers of below questions: How do I blur an image in OpenCV? Why you should blur an image before processing it using OpenCV and Python. The focus measure of this image is 83.17, falling below our threshold of 100; thus, we correctly mark this image as blurry. Figure 5: Performing blur detection with OpenCV. Go Image arithmetics and Logic OpenCV Python Tutorial. Now we’ve successfully converted an image to cartoon version using opencv and python. Python and OpenCV: Apply Filters to Images. “cv2” for video capturing, frame reading, pixel management, color management of the video, How can we apply gaussian blur to our images in Python using OpenCV? The GaussianBlur() uses the Gaussian kernel. Also Read – OpenCV Tutorial – Reading, Displaying and Writing Image using imread() , imshow() and imwrite() Using OpenCV and Python, an RGB color image can be converted into a pencil sketch in four simple steps: Convert the RGB color image to grayscale. Speaker: Nian Xiong. Gaussian Blurring:Gaussian blur is the result of blurring an image by a Gaussian function. We just need basically face detection feature and Gaussian Blur to handle those tasks. The Median blur operation is similar to the other averaging methods. OpenCV - Median Blur. Conversion between IplImage and MxArray. The first parameter is the image that we want to blur. Hello Everyone, Hope all you are well, Earlier in previous blog we have started with the basic of OpenCV… This operation processes the edges while removing the noise. Opencv gaussian blur python. OpenCV provides mainly four types of blurring techniques. I'm writing a script to detect blur images using OpenCV by applying Laplacian filter and calculate the std but there is a problem the std for images that contain motion blur is very close to those images which contain any other type of blur. High Level Steps: There are two steps to this process: Because of this, there is a loss of important information of images. Projects. OpenCV offers the function blur () to perform smoothing with this filter. As in any other signals, images also can contain different types of noise, especially because of the source (camera sensor). Averaging. In this video on OpenCV Python Tutorial For Beginners, I am going to show How to do Smoothing Images or Blurring Images OpenCV with OpenCV. Out-of-focus Deblur Filter, You can use the Motion Deblur Filter of opencv, if you specifically want to use opencv. From derivatives to edges. 1.Read an image. The technique to blur the image is simple, it averages out the pixels surrounding the pixel using a kernel. NOTE: We resize the image after each transformation to display all the images on a similar scale at last. ... 2.4 Blur Filter. This source parameter is a path to the input image which we’ll be working with this time instead of the RGB output like before. on 2016-07-27. Notice that we can already analyze the age with deep learning. imread() returns a numpy array containing values that represents pixel level data. Get image size (width, height) with Python, OpenCV, Pillow (PIL) The image is alpha blended according to the values of the second parameter alpha and the fourth parameter beta . This is done by the function cv2.blur () or cv2.boxFilter (). It takes the median of all the pixels under the kernel area, and the central element is replaced with this median value. Gaussian Blur Filter; Erosion Blur Filter; Dilation Blur Filter; Image Smoothing techniques help us in reducing the noise in an image. Take out the face, blur it, and put the face back in the video. Blur Image. To resize an image in Python, you can use cv2.resize() function of OpenCV library cv2. Today we will be Applying Gaussian Smoothing to an image using Python from scratch and not using library like OpenCV. imutils is Python basic image processing functional package to do image translation, rotation, resizing, skeletonization, or blur amount detection. Bitwise_and combine two frames according to the mask. I am pretty sure you have tried out various filters available on the social platforms and your camera as well. OpenCV libs on Real Android Device. input image; the image can have any number of channels, which are processed independently, but the depth should be CV_8U, CV_16U, CV_16S, CV_32F or CV_64F. OpenCV Python Image Smoothing – Gaussian Blur Image Smoothing using OpenCV Gaussian Blur As in any other signals, images also can contain different types of noise, especially because of the source (camera sensor). OpenCV provides four main types of blurring techniques. This workshop provides an introduction to basic image processing techniques using the OpenCV computer vision library and some standard data analysis libraries in Python. Introduction to Image Processing in Python. Examples for all these scenarios have been provided in this tutorial. Type the following on the console screen for it to run. Python OpenCV – Image Smoothing using Averaging, Gaussian Blur, and Median Filter These methods sometimes blur or smooth out everything irrespective of it being noise or edges. Process Capture original image Capture background model & Background subtraction Gaussian blur & Threshold Contour & Hull & Convexity References & Tutorials README.md for people using python2 and opencv2, please check out the lzane:py2_opencv2 branch.

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