Deep Learning ToolboxTM Model for DarkNet-53 Network
                  Pretrained DarkNet-53 network model for image classification
                
                  
              
                    1,6K téléchargements
                    
                    
                  
                
                  Mise à jour
                    15 oct. 2025
                  
                
              DarkNet-53 is a pretrained model that has been trained on a subset of the ImageNet database. The model is trained on more than a million images and can classify images into 1000 object categories (e.g. keyboard, mouse, pencil, and many animals). 
Opening the darknet53.mlpkginstall file from your operating system or from within MATLAB will initiate the installation process for the release you have. 
This mlpkginstall file is functional for R2020a and beyond. Use darknet53 instead of imagePretrainedNetwork if using a release prior to R2024a.
Usage Example: 
% Access the trained model
[net, classes] = imagePretrainedNetwork("darknet53");
% See details of the architecture
net.Layers
% Read the image to classify
I = imread('peppers.png');
% Adjust size of the image
sz = net.Layers(1).InputSize
I = I(1:sz(1),1:sz(2),1:sz(3));
% Classify the image using DarkNet-53
scores = predict(net, single(I));
label = scores2label(scores, classes)
% Show the image and the classification results
figure
imshow(I)
text(10,20,char(label),'Color','white')
Compatibilité avec les versions de MATLAB
              Créé avec
              R2020a
            
            
              Compatible avec les versions R2020a à R2026a
            
          Plateformes compatibles
Windows macOS (Apple Silicon) macOS (Intel) LinuxCatégories
      En savoir plus sur Deep Learning Toolbox dans Help Center et MATLAB Answers
    
  Tags
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!Découvrir Live Editor
Créez des scripts avec du code, des résultats et du texte formaté dans un même document exécutable.
