Car Classification using Inception-v3. Article on training 3 models to classify the Make, Model and Year of a car using Monk and deploying them through a Flask API
This article is about training 3 deep convolutional neural networks using Monk, which is an open source library for computer vision, and then deploying them through an API. The models take an image of a car as the input and then predict the Make, Model and Year of the car. The models have been trained on the Cars Dataset.
For transfer learning, the Inception-v3 architecture with pre-trained weights was used. Some initial layers were frozen and training was done on the remaining layers.
After training, the models were deployed through a Flask API. It accepts an image through a POST request and returns the predictions to the user.
For the *training notebook, *check this.
For the *Flask API, *check this.
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