To automate dog breed classification an API is the most accurate choice. 

The dog is a popular pet. It is estimated that there are more than 70 million dogs in the United States, making it the most popular pet in the country. This is due to the fact that dogs are extremely social and friendly animals. They form strong bonds with their owners and have been domesticated for thousands of years, as pets as for other purposes. Dogs are special animals that are known for their loyalty and devotion to their owners. They are also very intelligent animals with a high level of cognitive ability. Because of these characteristics, dogs have been used for a variety of purposes throughout history, including hunting, herding, military purposes, and as a guide for blind people.

There are many types of dogs, each with their own characteristics and skills. However, one of the most important aspects when choosing a dog is its breed. There are many different breeds of dog, each with its own set of features and traits. Some breeds are better suited to certain environments than others. For example, some breeds are better suited to hunting while others are better suited to herding cattle. In order to choose the right breed, it is important to understand what each breed is like and what they are best suited for. 

However, classifying dog breeds can be hard; it requires knowledge of the different characteristics that each breed has and also requires a lot of time.So an API is here to automate the research: Dog Breed Information API.

What Is An API?

An API allows to classify dog breeds based on their characteristics by connecting the user with databases of information about each breed, and allowing to automate this task and save time.

The proposed method applies a deep learning based approach in order to recognize their breeds. The method begins with a transfer learning by retraining existing pre-trained convolutional neural networks (CNNs) on the public dog breed dataset. Then, the image augmentation with various settings is also applied on the training dataset, in order to improve the classification performance. The proposed method is evaluated using three different CNNs with various augmentation settings and comprehensive experimental comparisons. The proposed model achieves a promising accuracy of 89.92% on the published dataset with over 100 dog breeds.

How To Use This API?

The first step is to create an account on the API marketplace. Once the platform furnishes the API key, it allows to start using this API. The next step is to provide the image/s URL in order to receive the results from this API. After that, wait a few seconds while the computer analyzes the image, since it will use artificial intelligence to determine what type of dog it represents. And finally, the user receives two different outputs: the first one will be the breed and the second one will be the probability of the image being from that breed; so  this information is thorough and accurate.

The response will look like this:

{
  "results": [
    {
      "score": 0.9873785376548767,
      "label": "German shepherd, German shepherd dog, German police dog, alsatian"
    },
    {
      "score": 0.0025157087948173285,
      "label": "kelpie"
    },
    {
      "score": 0.0009707494755275548,
      "label": "malinois"
    },
    {
      "score": 0.0008986197062768042,
      "label": "dingo, warrigal, warragal, Canis dingo"
    },
    {
      "score": 0.0005087173776701093,
      "label": "bloodhound, sleuthhound"
    }
  ]
}