Objective and problem
I'm trying to process a video file on the fly using OpenCV 3.4.1 by grabbing each frame, converting to grayscale, then doing Canny edge detection on it. In order to display the images (on the fly as well), I created a Mat class with 3 additional headers that is three times as wide as the original frame. The 3 extra headers represent the images I would like to display in the composite, and are positioned to the 1st, 2nd and 3rd horizontal segment of the composite.
After image processing however, the display of the composite image is not as expected: the first segment (where the original frame should be) is completely black, while the other segments (of processed images) are displayed fine. If, on the other hand, I display the ROIs one by one in separate windows, all the images look fine.
These are the things I tried to overcome this issue:
use .copyTo to actually copy the data into the appropriate image segments. The result was the same.
I put the Canny image to the compOrigPart ROI, and it did display in the first segment, so it is not a problem with the definition of the ROIs.
Define the composite as three channel image
In the loop convert it to grayscale
put processed images into it
convert back to BGR
put the original in.
This time around the whole composite was black, nothing showed.
As per gameon67's suggestion, I tried to create a namedWindow as well, but that doesn't help either.
Code:
int main() {
cv::VideoCapture vid("./Vid.avi");
if (!vid.isOpened()) return -1;
int frameWidth = vid.get(cv::CAP_PROP_FRAME_WIDTH);
int frameHeight = vid.get(cv::CAP_PROP_FRAME_HEIGHT);
int frameFormat = vid.get(cv::CAP_PROP_FORMAT);
cv::Scalar fontColor(250, 250, 250);
cv::Point textPos(20, 20);
cv::Mat frame;
cv::Mat compositeFrame(frameHeight, frameWidth*3, frameFormat);
cv::Mat compOrigPart(compositeFrame, cv::Range(0, frameHeight), cv::Range(0, frameWidth));
cv::Mat compBwPart(compositeFrame, cv::Range(0, frameHeight), cv::Range(frameWidth, frameWidth*2));
cv::Mat compEdgePart(compositeFrame, cv::Range(0, frameHeight), cv::Range(frameWidth*2, frameWidth*3));
while (vid.read(frame)) {
if (frame.empty()) break;
cv::cvtColor(frame, compBwPart, cv::COLOR_BGR2GRAY);
cv::Canny(compBwPart, compEdgePart, 100, 150);
compOrigPart = frame;
cv::putText(compOrigPart, "Original", textPos, cv::FONT_HERSHEY_PLAIN, 1, fontColor);
cv::putText(compBwPart, "GrayScale", textPos, cv::FONT_HERSHEY_PLAIN, 1, fontColor);
cv::putText(compEdgePart, "Canny edge detection", textPos, cv::FONT_HERSHEY_PLAIN, 1, fontColor);
cv::imshow("Composite of Original, BW and Canny frames", compositeFrame);
cv::imshow("Original", compOrigPart);
cv::imshow("BW", compBwPart);
cv::imshow("Canny", compEdgePart);
cv::waitKey(33);
}
}
Questions
Why can't I display the entirety of the composite image in a single window, while displaying them separately is OK?
What is the difference between these displays? The data is obviously there, as evidenced by the separate windows.
Why only the original frame is misbehaving?
Your compBwPart and compEdgePart are grayscale images so the Mat type is CV8UC1 - single channel and therefore your compositeFrame is in grayscale too. If you want to combine these two images with a color image you have to convert it to BGR first and then fill the compOrigPart.
while (vid.read(frame)) {
if (frame.empty()) break;
cv::cvtColor(frame, compBwPart, cv::COLOR_BGR2GRAY);
cv::Canny(compBwPart, compEdgePart, 100, 150);
cv::cvtColor(compositeFrame, compositeFrame, cv::COLOR_GRAY2BGR);
frame.copyTo(compositeFrame(cv::Rect(0, 0, frameWidth, frameHeight)));
cv::putText(compOrigPart, "Original", textPos, cv::FONT_HERSHEY_PLAIN, 1, fontColor); //the rest of your code
This is a combination of several issues.
The first problem is that you set the type of compositeFrame to the value returned by vid.get(cv::CAP_PROP_FORMAT). Unfortunately that property doesn't seem entirely reliable -- I've just had it return 0 (meaning CV_8UC1) after opening a color video, and then getting 3 channel (CV_8UC3) frames. Since you want to have the compositeFrame the same type as the input frame, this won't work.
To work around it, instead of using those properties, I'd lazy initialize compositeFrame and the 3 ROIs after receiving the first frame (based on it's dimensions and type).
The next set of problems lies in those two statements:
cv::cvtColor(frame, compBwPart, cv::COLOR_BGR2GRAY);
cv::Canny(compBwPart, compEdgePart, 100, 150);
In this case assumption is made that frame is BGR (since you're trying to convert), meaning compositeFrame and its ROIs are also BGR. Unfortunately, in both cases you're writing a grayscale image into the ROI. This will cause a reallocation, and the target Mat will cease to be a ROI.
To correct this, use temporary Mats for the grayscale data, and use cvtColor to turn it back to BGR to write into the ROIs.
Similar problem lies in the following statement:
compOrigPart = frame;
That's a shallow copy, meaning it will just make compOrigPart another reference to frame (and therefore it will cease to be a ROI of compositeFrame).
What you need is a deep copy, using copyTo (note that the data types still need to match, but that was fixed earlier).
Finally, even though you try to be flexible regarding the type of the input video (judging by the vid.get(cv::CAP_PROP_FORMAT)), the rest of the code really assumes that the input is 3 channel, and will break if it isn't.
At the least, there should be some assertion to cover this expectation.
Putting this all together:
#include <opencv2/opencv.hpp>
int main()
{
cv::VideoCapture vid("./Vid.avi");
if (!vid.isOpened()) return -1;
cv::Scalar fontColor(250, 250, 250);
cv::Point textPos(20, 20);
cv::Mat frame, frame_gray, edges_gray;
cv::Mat compositeFrame;
cv::Mat compOrigPart, compBwPart, compEdgePart; // ROIs
while (vid.read(frame)) {
if (frame.empty()) break;
if (compositeFrame.empty()) {
// The rest of code assumes video to be BGR (i.e. 3 channel)
CV_Assert(frame.type() == CV_8UC3);
// Lazy initialize once we have the first frame
compositeFrame = cv::Mat(frame.rows, frame.cols * 3, frame.type());
compOrigPart = compositeFrame(cv::Range::all(), cv::Range(0, frame.cols));
compBwPart = compositeFrame(cv::Range::all(), cv::Range(frame.cols, frame.cols * 2));
compEdgePart = compositeFrame(cv::Range::all(), cv::Range(frame.cols * 2, frame.cols * 3));
}
cv::cvtColor(frame, frame_gray, cv::COLOR_BGR2GRAY);
cv::Canny(frame_gray, edges_gray, 100, 150);
// Deep copy data to the ROI
frame.copyTo(compOrigPart);
// The ROI is BGR, so we need to convert back
cv::cvtColor(frame_gray, compBwPart, cv::COLOR_GRAY2BGR);
cv::cvtColor(edges_gray, compEdgePart, cv::COLOR_GRAY2BGR);
cv::putText(compOrigPart, "Original", textPos, cv::FONT_HERSHEY_PLAIN, 1, fontColor);
cv::putText(compBwPart, "GrayScale", textPos, cv::FONT_HERSHEY_PLAIN, 1, fontColor);
cv::putText(compEdgePart, "Canny edge detection", textPos, cv::FONT_HERSHEY_PLAIN, 1, fontColor);
cv::imshow("Composite of Original, BW and Canny frames", compositeFrame);
cv::imshow("Original", compOrigPart);
cv::imshow("BW", compBwPart);
cv::imshow("Canny", compEdgePart);
cv::waitKey(33);
}
}
Screenshot of the composite window (using some random test video off the web):
I'm new in opencv and I had this problem...
Given the following Mat type (globally declarated)
Mat src_gray;
Mat dst;
I have dst being a zero grayscale Mat with this initialization
dst=Mat::zeros(src_gray.size(), CV_BGR2GRAY);
It seems I can't edit the pixels on the dst image (when I use imwrite, it gives me a black image as if I hadn't done anything).
This is the code I currently have:
for(int i=0;i<=dst.cols;i++)
for(int j=0;j<=dst.rows;j++)
{
dst.at<uchar>(j,i)=255;
}
imwrite( "img_res.png", dst );
The result Image has the dimensions it's supposed to have, but it is a black pixeled picture, shouldn't it be a white pixeled Image?
I don't know if it is relevant if I mention that I have 3 global Mats
Mat image;
Mat src_gray;
Mat dst;
Which are initialized this way:
image = imread( argv[1], 1 );
cvtColor( image, src_gray, CV_BGR2GRAY );
Then, I release them as:
image.release();
dst.release();
src_gray.release();
The other problem I get is that when I release the Mats (during execution), I get the "Segmentation fault (core dumped)" error. (I code from Linux Ubuntu distri)
Try:
dst=Mat::zeros(src_gray.size(), CV_8UC1);
When you use CV_BGR2GRAY, you are creating a Mat with 3 color channels, then, it's not possible to assign a number when you have an array of numbers (B,G,R).
With CV_8UC1, you create a Mat with 1 color channel of uchar then it should works with:
dst.at<uchar>(j,i)=255;
I'm working on my school project. I use grid-eye to access the environment temperature. The data form is a 64 pixels array (8x8 2D-array). Now I want to use this array to generate a thermal picture. I can simply copy the value to Matlab, scale it, and use image (temperature) to output a picture like this
The more red and dark represent hotter.
But I build all program in C++. So I have to find a way to do the same thing in C++. The first thing I though is OpenCV. After some searching, I wrote a simple code for only gray-scale mat. But this image looks weird.
Here is my code:
void GridEye::showCV() {
// > threshold means this pixel contain heat object.
for (int i = 0; i < 64; ++i) {
if (temperature[i] > threshold) forimage[i] = 255;
else forimage[i] = 0;
}
Mat image(8, 8, CV_8UC1, forimage);
resize(image, image, Size(640, 640)); // to make picture larger
namedWindow("Display window", WINDOW_AUTOSIZE);
imshow("Display window", image);
waitKey(100);
}
Is there something wrong with my code? Or some suggestion for using other library because I am really not familiar to OpenCV.
Try something like:
Mat1f image(8, 8, temperature);
//threshold(image, image, your_threshold_value, 0, THRESH_TOZERO); // << Uncomment this line to apply a threshold
normalize(image, image, 0, 1, NORM_MINMAX);
imshow("original size", image);
Mat resized;
//resize(image, resized, Size(640, 640)); // << Apply bilinear interpolation
resize(image, resized, Size(640, 640), 0, 0, INTER_NEAREST);
imshow("resized", resized);
waitKey();
The implementation of this functionality seems pretty straightforward in Python, as shown here: http://docs.opencv.org/trunk/doc/py_tutorials/py_imgproc/py_grabcut/py_grabcut.html
Yet, when I tried to do exactly the same in C++, I get bad arguments error (for the grabcut function). How to put the mask image in the right format?
I am a newbie at this, so I'd be very thankful if someone could help me understand better. Thank you!
Here's what I have so far:
Mat image;
image= imread(file);
Mat mask;
mask.setTo( GC_BGD );
mask = imread("messi5.png");
Mat image2 = image.clone();
// define bounding rectangle
cv::Rect rectangle(startX, startY, width, height);
cv::Mat result; // segmentation result (4 possible values)
cv::Mat bgModel,fgModel; // the models (internally used)
//// GrabCut segmentation that works, but with a rectangle, not with the mask I need
//cv::grabCut(image, // input image
// result, // segmentation result
// rectangle,// rectangle containing foreground
// bgModel,fgModel, // models
// 1, // number of iterations
// cv::GC_INIT_WITH_RECT); // use rectangle
grabCut( image, mask, rectangle, bgModel, fgModel, 1, GC_INIT_WITH_MASK);
cv::compare(mask,cv::GC_PR_FGD,mask,cv::CMP_EQ);
cv::Mat foreground(image.size(),CV_8UC3,cv::Scalar(255,255,255));
image.copyTo(foreground,mask); // bg pixels not copied
namedWindow( "Display window", WINDOW_AUTOSIZE );
imshow( "Display window", foreground );
waitKey(0);
return 0;
}
It looks like you have misunderstood the guide, repeated here from the linked guide in the question:
# newmask is the mask image I manually labelled
newmask = cv2.imread('newmask.png',0)
# whereever it is marked white (sure foreground), change mask=1
# whereever it is marked black (sure background), change mask=0
mask[newmask == 0] = 0
mask[newmask == 255] = 1
mask, bgdModel, fgdModel = cv2.grabCut(img,mask,None,bgdModel,fgdModel,5,cv2.GC_INIT_WITH_MASK)
mask = np.where((mask==2)|(mask==0),0,1).astype('uint8')
img = img*mask[:,:,np.newaxis]
plt.imshow(img),plt.colorbar(),plt.show()
this is not what you have done i'm afraid. For a start you seem to have set the mask to the rgb image:
mask = imread("messi5.png");
whereas is should be set to the mask image:
mask = imread("newmask.png",CV_LOAD_IMAGE_GRAYSCALE);
EDIT from comments:
from a pure red mask painted over the image (an actual mask would be better).
maskTmp = imread("messi5.png");
std::vector<cv::Mat> channels(3)
split( messi5, channels);
cv::Mat maskRed = channels[2];
now threshold on the red channel to get your binary mask.
Is there an easy non costly method to flip an IplImage along the y-axis ?
I'm working with high framerates.
There is cvFlip (see Operation On Arrays) that can do in place flipping. Horizontal, vertical and combined flipping is supported.
Example: Flipping y-axis:
cvFlip(Image, NULL, 1);
Why not use C++ API Mat? Try this out and see if it works with your requirement. Just replace IplImage* img with your frame.
IplImage* img = cvLoadImage("c:\\test.jpg");
cvFlip(img, img, 0);
cvNamedWindow("result", CV_WINDOW_AUTOSIZE);
cvShowImage("result", img);
cvWaitKey(0);
cvDestroyWindow("result");