A project aimed to classify dog breeds and search for the most matched image in the database
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Updated
Jan 17, 2019 - Python
A project aimed to classify dog breeds and search for the most matched image in the database
A simple classification model takes the advantage of transfer learning to train the model to identify the dog images.
Transfer Learning with TensorFlow
🐶 Deploy a predictive classification model for dog breeds using Flask + Keras!
A convolutional neural network trained to classify dog breeds.
Udacity Machine Learning Nanodegree - Deep learning project (Jan 2019)
Project 1 as part of Udacity's `AI Programming with Python` Nanodegree.
Dogs Image Classifier classifies pet images to dogs and not dogs and identify the breeds of the classified dogs using transfer learning via PyTorch pretrained models.
The image classifier to recognize different breeds of dog. Dataset used contains 50 images of dogs. In Image Classifier Project Resnet18, Alexnet, VGG16 from torchvision.models pretrained models were used. It was loaded as a pre-trained network, in which input images are transformed and resized for better prediction.
Determine how well the "best" classification algorithm works on correctly identifying a dog's breed. If you are confused by the term image classifier look at it simply as a tool that has an input and an output. The Input is an image. The output determines what the image depicts. (for example, a dog).
AI Programming with Python - Project 1
Deep learning solution for dog breed classification using MobileNet - 76% accuracy on 120 classes
Predict Dog Breed using Python Function instead of Using Actual Classifier
Image Classification for a City Dog Show Project Goal Improving your programming skills using Python. In this project, I use a created image classifier to identify dog breeds. It is for one of the submission for the udacity nanodegree program
This project aimed to utilize a pre-trained image classifier to identify dog breeds for a citywide dog show. The primary goal was to improve programming skills using Python, focusing on utilizing the classifier rather than developing it.
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