Difference between revisions of "OpenCV4"
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* Note: Scroll down to the Explanation. | * Note: Scroll down to the Explanation. | ||
− | In order to use build-in function in Open CV: remember to <code>import</code> cv2. In the instruction, the <code>import</code> cv2 <code>as</code>cv means that you can now type in cv instead of cv2 when using build function. | + | In order to use build-in function in Open CV: remember to <code>import</code> cv2. In the instruction, the <code>import</code> cv2 <code>as</code>cv means that you can now type in cv instead of cv2 when using build-in function. |
Revision as of 01:14, 12 December 2018
Contents
Overview
This is a tutorial on how to install OpenCV4 and use camera module.
Materials/Prerequisites
- Raspberry Pi
- Raspberry Pi Camera
Process
Install OpenCV
Follow these instruction[1] to install OpenCV onto your Raspberry Pi using the terminal.
- Important note: don't do
make-j4
. It may freeze so it best to just domake
ormake-j1
.
After you have successfully installed OpenCV, you will be able to use import cv2
. If you do it on the terminal, you want to put in these code source ~/.profile
and then workon cv
.
Capturing image
Following these step to set up your camera[2]
- Note: Ignoring GoPiGo installation.
Once the camera is set up, it is ready to take pictures. In order to capture image, follow these instruction [3]
Note:
- Use
sleep
(measured in seconds) to create a delay between the preview:time.sleep(seconds)
- Another way to enable your camera is: go to the terminal → type in
sudo raspi-config
→ selectEnable Camera
→ press Enter → selectFinish
→ reboot and log back on to the Raspberry Pi.
Edge Detector
Once you have a picture, you may want to use edge detection to detect the chessboard region of interest.
Follow these instruction for Canny edge detection[4]
- Note: Scroll down to the Explanation.
In order to use build-in function in Open CV: remember to import
cv2. In the instruction, the import
cv2 as
cv means that you can now type in cv instead of cv2 when using build-in function.
Use the following build-in code for Canny Detection:
Canny( detected_edges, detected_edges, lowThreshold, lowThreshold*ratio, kernel_size )
Ex: To load image:
- src =
cv.imread
(filename, cv.IMREAD_GRAYSCALE)
Then use:
- dst =
cv.Canny
(src, 50, 200, None, 3)
Hougline Transformation
Authors
- Nhut Dang
- Robert Goodloe
- Ethan Shry(TA)
Fall 2018