The Link of the Image is here I am having an image and I want to remove all bounding boxes using OpenCV the color code of the bounding boxes is different. How can we do that?
I have tried many codes of OpenCV but I am not able to get the result. So I want the full code.
Thanks
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I'm new to cognex world, so if anyone can help I will be thankful.
I have a image, how can I remove a Region of a Image?
So my ROI is a box, but there is a smaller box inside of that bigger box that is not important. So my ROI will be the bigger box less the smaller box.
I tried filters, but filter a new image with the size of the region (ROI filter).
How can I do this?
You can use the mask to ignore a part of the image. Some tools allow different "uses" of the mask so make sure it fits what you need.
For example, segmentation tools (red tools) can use the masked region as an extra channel of the image.
How to get do change to text perspective for OCR to detect?
Ori image:
After some pre processing, i got the below image.
I have this picture, and try to correct the perspective by using Bounding Box technical, i reference from others post, i tried to use morphnology to connect the text and use minAreaRect to get the area
Then draw the line, but the perspective is incorrect.
How can i get the persective as below?
After this, i will use getPerspectiveTransform and warpPerspective to correct it. Thanks
I am a beginner in OpenCV, and am trying to extract numbers from a dataset of images and use the extracted numbers as a dataset for NN. For this, I'm using mser's bounding boxes and then cropping the image in size of the bounding box. but mser is not detecting the text area correctly. Please help me on how to do it more precisely. here is my code:
mser = cv2.MSER_create(_delta = 1)
msers, bbs = mser.detectRegions(gray)
Here bbs are the list of bounding boxes, they are not on the text area, not even one.
Image of the ground truth, where the bounding box should be:
Bounding box by mser:
Another example of the bounding box by mser:
If you want to detect text on an image, I use Tesseract to accomplish this. You just link it a tessdata file to the language you are using, and it should detect the text in the image and output it as a string. However, if you want to crop the original image further before you detect text on an image, you could use blob detection. Blob detection is where an image is passed through a variety of different image thresholds, and it looks for consistency, and if consistency is found, a blob is created at that region. You could use blob detection in this situation, then create your bounding rectangles off of those blobs.
Need some guidance here, I'm trying to identify different objects in an image and get their bounding box.
The image is always clean with transparent background and well separated objects.
for example in the above image there are 3 objects. Any idea or any tool would be helpful.
As the objects are on such background, a simple connected components labeling will give you a first basic answer. However, it will be more complicated to find out which objects are overlapping.
Do you have any information about the objects to detect?
You can just use the template matching to find the flowers and the top-right object (assuming here that they are similar) given the image of the flower (as a template) and the whole picture.
There is an example of the template detection here: (where reference.png is the original image, and the template.png is the object you want to detect, like the flower)
Here is an image of the flower (renamed to template.png):
Running the template matching code with the whole image as reference.png, we can find the flowers (highlighted in green rectangles):
Although the code did not implement the bounding boxes, you can use boundingRect() to draw a minimum bounding rectangle (given a single contour).
The outline may be something like:
Set a ROI (Region of Interest) inside each of the green boxes.
Find the contours of pink objects.
Use boundingRect on the contours found, and draw the minimum rectangle around the flower.
I'm having the user capture an image of a barcode that they are asked to place inside a bounding box drawn on the camera overlay. I'd like to detect whether that barcode was properly placed in the box. What would be the best way to detect this? OpenCV's houghLines? And how would I figure out if the lines detected from houghLines are the barcode's corner and that they match up with the camera overlay's bounding box?
Thanks in advance for any help
The post How to find corners on a Image using OpenCv has the solution for your problem. I did the same for my project and it worked like a charm :) If need help in understanding or tuning the algorithm, don't hesitate.
Cheers