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
CONTENTS:
Installation
Classification
Object Detection
INSTALLATION:
Two ways to install Library:
$ pip install DarkNeurons
or
git clone https://github.com/Tushar-ml/DarkNeuron.git
cd DarkNeuron
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.
https://github.com/Tushar-ml/DarkNeuron
CLASSIFICATION:
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:
InceptionV3
Xception
ResNet50
VGG16
VGG19 Further will be added on upcoming releases.
Initialization:
from DarkNeurons import Classify_Images
classify = Classify_Images( working directory )
Preparation and Preprocessing of Data:
Train , Valid , Test = classify.Preprocess_the_Image( )
Model Creation
model = classify.Create_the_Model( )
Model Training
model = classify.Train_the_Model( )
Prediction
classify.Predict_from_the_Model( )
Visualization of Metrics and Prediction
classify.Visualize_the_Metrics( )
classify.Visualize_the_Predictions( )
OBJECT DETECTION
Object Detection Model uses the YOLOv4 version for Detection. It is the fastest algorithm known for Detection
Initialization:
from DarkNeurons import YOLOv4
yolo = YOLOv4( working directory )
Preparation of Data:
yolo.Prepare_the_Data( )
Model Training
yolo.Train_the_Yolo( )
Detection
yolo.Detect( )
In the Detection part, you can detect from Image, Video or even Live Capturing from Screen Detection.
Further Releases:
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
For Further Open-Source Libraries and Tutorials, Follow me for the newsletters directly to your emails. For Contributing topics for this post, connect with me on:
Gmail: [email protected]
LinkedIn: https://www.linkedin.com/in/tushar-goel-563153184/
GitHub: https://github.com/Tushar-ml
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Thank You!!!!
