Creating annotated data sets with IBM Cloud Annotations
By the end of this tutorial, you will be able to generate datasets with annotated images that can be used in Create ML for building and training object detection machine learning models for Core ML.
To train Image Classification models is quite simple, you just need to have your dataset organized in folders and you are good to go. To train Object Detection models, on the other hand, requires a special file telling Create ML where each of the objects is located in each image of your dataset.
This special file is a JSON file named annotations.json, and trust me when I say that creating it manually is an herculean task.
Imagine having to write down the coordinates for the position of each object in each image of your dataset?
[
{
"image": "image1.jpg",
"annotations": [
{
"label": "salmon",
"coordinates": {
"x": 120, "y": 164, "width": 230, "height": 119
}
},
{
"label": "tuna",
"coordinates": {
"x": 230, "y": 321, "width": 50, "height": 50
}
}
]
}
]Luckily there are tools and platforms out there to support you in this task.
One of them is the IBM Cloud Annotations. It offers fast and easy image annotation in the browser and supports training machine learning models in the cloud as well as exporting datasets for Create ML.
It can be used for free, with some limitations, and should provide everything you need to create annotated datasets to train Object Detection models. Let's see how that works.
Become a free member or log in to proceed.