xtreme-vision 1.3

A Python Library for Computer-Vision related Tasks

Xtreme-Vision

This is the Official Repository of Xtreme-Vision. Xtreme-Vision is a Python Library which is built with simplicity in mind for Computer Vision Tasks, such as Object-Detection, Human-Pose-Estimation, Image-Segmentation Tasks, it provides the support of a list of state-of-the-art algorithms, You can Start Detecting with Pretrained Weights as well as You can train the Models On Custom Dataset.

Currently, It Provides the Solution for the following Tasks:

• Object-Detection
• Pose-Estimation
• Image-Segmentation

For Detection with pre-trained models it provides:

• RetinaNet
• CenterNet
• YOLOv4
• TinyYOLOv4
• Mask-RCNN

For Custom Training It Provides:

• YOLOv4
• TinyYOLOv4

In Future it will provide solution for a wide variety of Computer-Vision Tasks such as Object-Detection, Pose-Estimation, Image-Segmentation, Image-Prediction, Auto-Encoders and GANs.

If You Like this Project Please do support it by donating here

Dependencies:

• Tensorflow >= 2.3.0
• Keras
• Opencv-python
• Numpy
• Pillow
• Matplotlib
• Pandas
• Scikit-learn
• Progressbar2
• Scipy
• H5Py

Get Started:

!pip install xtreme-vision

For More Tutorials of Xtreme-Vision, Click Here

RetinaNet Example

Image Object_Detection Using RetinaNet

from xtreme_vision.Detection import Object_Detection

model = Object_Detection()
model.Use_RetinaNet()
model.Detect_From_Image(input_path='kite.jpg',
                        output_path='./retinanet.jpg', 
                        extract_objects=True)

from PIL import Image
Image.open('retinanet.jpg')