Training data is the initial dataset that is used by the object detection model to analyze data patterns, make interpretations, and arrive at a learning to detect objects. You need to train the model so that it can perceive the input information correctly and make accurate decisions based on the information provided. This ensures that the model performs the way it's intended to. For the Object Detection model, a set of images of the object that needs to be detected has to be uploaded as the model training data.
- Click + Add New Object to create an object folder. You can also import images from your .zip folder by clicking Import from folder .
- To help you get started quickly and explore the possibilities of our object detection model, you can download our sample data and start building models.
Note : This sample data will be available only when you're creating an object detection model for the first time.
- Enter the object's name in the New Object pop up that appears, then click Create. This is the name of the folder where you can add your input images. This object name will be displayed when the model detects your object from the input image.
- The object folder's name cannot exceed 30 characters in length.
- I f you've uploaded images from your folder, the folder name will be used as the object name. Make sure to give a proper name to your folder before uploading.
- Double -click the newly-created object folder to add the sample images.
- Click Upload Images to add different images of the same object at varying angles.
- A minimum of 10 images must be uploaded for each object.
- Compatible image formats are JPG, PNG, and TIF.
- Each image can have a file size up to 5 MB .
- For more image guidelines, click here .
- Click Add Images to upload more images. You can also upload multiple images at once by either dragging and dropping them or uploading them as a .zip folder.
Compatible image formats for.the zip folder include JPG, PNG, TIF.
- You can either click the Select All radio button or individually select images and click Delete to remove the images.
- Click Done . An object folder will be created.
- You can add additional objects (folders) by clicking + Add New Object or Import from folder in the dropdown beside it at the top-right corner of the Add Training Data screen .
- Select a folder to Rename or Delete it. Click Select All (ref above image) to Rename or Delete all object folders.
- Click Next . The Model Summary screen will open.
Step 3: Verify the model summary, train and test model
After adding the training data, you can review the model details, such as Model Name, Model Type, Model Size, and Total Size. If you need to make any modifications, you can go back to do so. Otherwise, you can proceed to train the model.
- Train model
- View and manage model details
- Test model
Before you can actually use your object detection model in your application, you have to train it to perform the way you want.
- Check the details of your model in the Model Summary page and make any necessary changes by going Back . You can modify the Model Name, upload additional images or remove unwanted images.
- Once you've made the necessary changes, click Train Model .
Note : Model training may take some time, so you can either stay on the page and wait, or you can close the page and come back later.
View and manage model details
After the training is complete, the user can view the status of the model ( t rained, failed, and draft), the model type, the date it was created on and updated on, and other details as mentioned below.