How to extract a specific section of an image using OpenCV in Python?
Extract a particular object from images using OpenCV in Python?
- Task. Draw shape on any image.
- Code. Get the code from here or just follow the code provided below:
- Run. Save the file as capture_events.py and for testing we select a demo image located in the same directory.
- Expected performance.
Table of Contents
How do I identify a specific object in an image?
What is object detection? Object detection is a computer vision technique that works to identify and locate objects within an image or video. Specifically, object detection draws bounding boxes around these detected objects, allowing us to pinpoint where those objects are (or how they are moving through) a given scene.
How can object detection be done in OpenCV?
Steps to download requirements below:
- Run the following command in terminal to install opencv. pip install opencv-python.
- Run the following command to install matplotlib in terminal. pip install matplotlib.
- To download the haar waterfall file and the image used in the following code as a zip file, click here.
How does Python detect edges in an image?
Edge detection function
- def simple_edge_detection(image): edges_detected = cv2.Canny(image, 100, 200) images = [imagen, bordes_detectados]
- location = [121, 122] for loc, zipped edge_image(location, images): plt.subplot(location)
- cv2.imwrite(‘edge_detected.png’, edge_detected) plt.savefig(‘edge_plot.png’) plt.show()
How to detect an object in Python using OpenCV?
Detect an object with OpenCV-Python. OpenCV is the huge open source library for computer vision, machine learning and image processing and now it plays an important role in real-time operation which is very important in today’s systems. Using it, one can process images and videos to identify objects, faces, or even the handwriting of a human being.
How to detect color patches in an image using OpenCV?
Processing the colorful image in the HSV color space is a good direction. And I split the channels and found the S channel to be great. Because S is Saturation (饱和度) of color. Then threshold the S with a threshold of 100, you get this. It will be easy to separate the colored region in the trite binary image.
What can OpenCV be used for in real time?
OpenCV is the huge open source library for computer vision, machine learning and image processing and now it plays an important role in real-time operation which is very important in today’s systems. Using it, one can process images and videos to identify objects, faces, or even the handwriting of a human being.
How to make face detection work in Python?
use the image [y:y+profundidad, x:x+ancho], where x and y are the left-hand axes to start trimming. width and depth are the x and y (length) dimensions of the cropped image respectively. Line 15 converts the image to grayscale, note that the face detection algorithm used here works best on grayscale images.
How do I translate an image in OpenCV?
To translate an image using OpenCV, we must:
- Load an image from disk.
- Define an affine transformation matrix.
- Apply the. cv2.warp Affine. function to perform the translation.
How do you translate an image in Python?
Translation refers to the rectilinear displacement of an object, that is, an image from one place to another. If we know the amount of change in the horizontal and vertical direction, say (tx, ty), then we can make a transformation matrix, for example
How to scale an image in OpenCV Python?
Examples of use of cv2. resize() function
- Preserve aspect ratio (retain the ratio of the image’s height to width) Scale it down (decrease the image size)
- Do not preserve aspect ratio. Resize width only (increase or decrease the width of the image while keeping the height unchanged)
- Resize to a specific width and height.
Explanation:
- Import all required libraries (opencv, tkinter, tesseract)
- Provide the location of the tesseract.exe file.
- Tkinter provides GUI functionality: open an image dialog so the user can upload an image.
- Let’s move on to the extract function which takes the image path as a parameter.
How do I convert a color to grayscale using OpenCV?
Converting video from color to grayscale using OpenCV in Python
- Import the cv2 module.
- Read the video file to be converted using cv2. VideoCapture() method.
- Run an infinite loop.
- Inside the loop, extract frames from the video using the read() method.
- Pass the frame to cv2.
- Show the framework using the file cv2.
How do you rotate an image 90 degrees in Python?
You can rotate an image 90 degrees counterclockwise by providing angle = 90. We also give expand=True, so that the rotated image fits the output size.
How do you rotate an image in Python?
Example:
- # imports the Python image processing library.
- of the PIL import image.
- # Create an Image object from an Image.
- colorImage = Image.open(“./effil.jpg”)
- # Rotate it 45 degrees.
- rotated = ImageColor.rotate(45)
- # Rotate it 90 degrees.
- transpose = colorImage.transpose(Image.ROTATE_90)
How do we draw a line with open CV?
Draw a line using the OpenCV function line() Draw an ellipse using the OpenCV function ellipse() Draw a rectangle using the OpenCV function rectangle() Draw a circle using the OpenCV function circle()