A simple, high level, easy-to-use open source Computer Vision library for Python.
It was developed with a focus on enabling easy and fast experimentation. Being able to go from an idea to prototype with least amount of delay is key to doing good research.
Guiding principles of cvlib are heavily inspired from Keras (deep learning library).
Provided the below python packages are installed, cvlib is completely pip installable.
If you don’t have them already installed, you can install through pip
pip install opencv-python tensorflow
pip install cvlib
To upgrade to the newest version
pip install --upgrade cvlib
Checkout the github page for complete instructions.
Detecting faces in an image is as simple as just calling the function
detect_face(). It will return the bounding box corners and corresponding confidence for all the faces detected.
import cvlib as cv faces, confidences = cv.detect_face(image)
Seriously, that’s all it takes to do face detection with
cvlib. Underneath it is using OpenCV’s
dnn module with a pre-trained caffemodel to detect faces.
Checkout the github repo to learn more.
Once face is detected, it can be passed on to
detect_gender() function to recognize gender. It will return the labels (man, woman) and associated probabilities.
label, confidence = cv.detect_gender(face)
examples directory for the complete code.
Detecting common objects in the scene is enabled through a single function call
detect_common_objects(). It will return the bounding box co-ordinates, corrensponding labels and confidence scores for the detected objects in the image.
import cvlib as cv from cvlib.object_detection import draw_bbox bbox, label, conf = cv.detect_common_objects(img) output_image = draw_bbox(img, bbox, label, conf)
Checkout the github repo to learn more about all the functionalities available in cvlib.
cvlib is released under MIT License.
For bugs and feature requests, feel free to file a GitHub issue. (Make sure to check whether the issue has been filed already)
For usage related how-to questions, please create a new question on StackOverflow with the tag