visionlib 1.2.0

A simple, easy to use and customizeble cv library

Visionlib

A simple high level api made for assisting in cv-related projects.

Features

• Track faces using
  • MTCNN module
  • Dlib hog Based detector
  • Opencv Haar casscades
  • Dnn based model
• Predict Gender
• Detect Objects
  • Yolo v3
  • tiny-yolo

Installation

Dependencies

sudo apt-get install build-essential cmake pkg-config

sudo apt-get install libx11-dev libatlas-base-dev

sudo apt-get install libgtk-3-dev libboost-python-dev

This should install Dependencies required by dlib.

pip install visionlib

This will install visionlib.

Optional

If You want to install from source git clone https://github.com/ashwinvin/Visionlib.git cd visionlib pip install .

Face Detection

Detecting face in an image is easy . This will return the image with bounding box and box coordinates from visionlib.face.detection import FDetector detector = FDetector() detector.detect_face(img, show=True)

This would detect face and display it automatically.

detector.set_detector("mtcnn") Dont like the default detector?, change it like this.

Examples

Gender Detection

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.Like this from visionlib.gender.detection import GDetector Gdetector = GDetector() pred, confidence = Gdetector.detect_gender(c_img)

Example

Object Detection

Detecting common objects in the scene is enabled through a single function call detect_objects(). It will return the labeled image for the detected objects in the image. By default it uses yolov3-tiny model. from visionlib.object.detection import Detection import cv2 detector = Detection() d_img = detector.detect_objects(img)

You can enable gpu usage by detector.detect_objects(img, enable_gpu=True)

Example

For more examples look in examples directory