Oct 26, 2020
2 mins read
Hello to all AI Enthusiasts out there, Hope you are doing good in this pandemic era and improving your skills.
DarkNeurons is an Open-Source implementation of Automatic Deep Learning Library which can reduce the time and Complexity for non-technical users to train their own networks without Compromising Accuracies for Classification of Images and Object Detection, the most demanding techniques for Autonomous Systems and Medical Fields.
" By augmenting human performance, AI has the potential to markedly improve productivity, efficiency, workflow, accuracy and speed, both for physicians and for patients … What I’m most excited about is using the future to bring back the past: to restore the care in healthcare. " - Eric Topol
Two ways to install Library:
$ pip install DarkNeurons
git clone https://github.com/Tushar-ml/DarkNeuron.git
python setup.py install
Providing the Summary of Methods in DarkNeurons below, Detailed Instructions can be seen over here: Show Your Support by Forking the Repository and by Providing contribution to it.
DarkNeuron Classification has the feature of implementing Pretrained Models on ImageNet Data. Users can directly train pre-trained models or can retrain their own models. Models provided are:
VGG19 Further will be added on upcoming releases.
from DarkNeurons import Classify_Images
classify = Classify_Images( working directory )
Preparation and Preprocessing of Data:
Train , Valid , Test = classify.Preprocess_the_Image( )
model = classify.Create_the_Model( )
model = classify.Train_the_Model( )
Visualization of Metrics and Prediction
Object Detection Model uses the YOLOv4 version for Detection. It is the fastest algorithm known for Detection
from DarkNeurons import YOLOv4
yolo = YOLOv4( working directory )
Preparation of Data:
In the Detection part, you can detect from Image, Video or even Live Capturing from Screen Detection.
Visualization of Artificial Neural Networks
Hybridization or Fusion of Two Different Models
Object Tracking using DeepSORT
Improve your Deep Learning Skills by Contributing to the Open-Source Libraries.
Keep Coding, Keep Growing with AI
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