After creating your Edge Impulse Studio project, you will be directed to the project's dashboard. The dashboard gives a quick overview of your project such as your project ID, the number of devices connected, the amount of data collected, the preferred labeling method, among other editable properties. You can also enable some additional capabilities to your project such as collaboration, making your project public, and showcasing your public projects using Markdown READMEs as we will see.
The figure below shows the various sections and widgets of the dashboard that we will cover here.
The Edge Impulse Studio dashboard.
The Getting Started section is here to help. You can choose from 3 different options to get started:
- Add existing data: When selecting this option, you can then choose to Upload data from your computer or to Add storage bucket
- Collect new data: When selecting this option, the getting started guide will ask you to either Scan QR code to connect to your phone, Connect to your computer, or to Connect your device or developer board. Make sure that your device or development board is flashed with the Edge Impulse official firmware.
To share your private project with the world, and click Make this project public.
Make your Edge Impulse Studio project public.
By doing this, all of your data, block configurations, intermediate results, and final models will be shared with the world. Your project will be publicly accessible and can be cloned with a single click with the provided URL:
A public project in the Edge Impulse Studio.
You can also create a private clone of your project by selecting the version you wish to copy and choosing the Restore option, using the desired name for the clone.
When you have a trained model available in your project, this card will appear to let you test your model with your phone or your computer. This is particularly useful to validate the behaviour of your model before integrating it into your targeted embedded firmware.
You can invite up to three collaborators to join and contribute to your project. To have unlimited collaborators on your private project, it needs to be part of an organization. If you are not on an enterprise license, you need to make your project public to unlock collaboration and be able to add up to three collaborators to join and contribute to your project.
To add a collaborator, go to your project's dashboard and find the "Collaborators" widget. Click the '+' icon and type the username or e-mail address of the other user. The user will be invited to create an Edge Impulse account if it doesn't exist.
The user will be automatically added to the project and will get an email notification inviting them to start contributing to your project. To remove a user, simply click on the three dots besides the user then tap ‘Delete’ and they will be automatically removed.
The project README enables you to explain the details of your project in a short way. Using this feature, you can add visualizations such as images, GIFs, code snippets, and text to your project in order to bring your colleagues and project viewers up to speed with the important details of your project. In your README you might want to add things like:
- What the project does
- Why the project is useful
- Motivations of the project
- How to get started with the project
- What sensors and target deployment devices you used
- How you plan to improve your project
- Where users can get help with your project
To create your first README, navigate to the "about this project" widget and click "add README"
The Edge Impulse Studio project README.
For more README inspiration, check out the public Edge Impulse project tutorials below:
The project info widget shows the project's specifications such as the project ID, labeling method, and latency calculations for your target device.
Edge Impulse Studio project information.
- The project ID is a unique numerical value that identifies your project. Whenever you have any issue with your project on the studio, you can always share your project ID on the forum for assistance from edge Impulse staff.
- On the labeling method dropdown, you need to specify the type of labeling your dataset and model expect. This can be either one label per data item or bounding boxes. Bounding boxes only work for object detection tasks in the studio. Note that if you interchange the labeling methods, learning blocks will appear to be hidden when building your impulse.
- One of the amazing Edge Impulse superpowers is the latency calculation component. This is an approximate time in milliseconds that the trained model and DSP operations are going to take during inference based on the selected target device. This hardware in the loop approach ensures that the target deployment device compute resources are not underutilized or over-utilized. It also saves developers' time associated with numerous inference iterations back and forth the studio in search of optimum models.
In the Block Output section, you can download the results of the DSP and ML operations of your impulse.
Download Edge Impulse Studio project block output.
The downloadable assets include the extracted features, Tensorflow SavedModel, and both quantized and unquantized TensorFlow lite models. This is particularly helpful when you want to perform other operations to the output blocks outside the Edge Impulse studio. For example, if you need a TensorflowJS model, you will just need to download the TensorFlow saved model from the dashboard and convert it to TensorFlowJS model format to be served on a browser.
This section consists of editable parameters that directly affect the performance of the studio when building your impulse. Depending on the selected or available settings, your jobs can either be fast or slow.
The Edge Impulse Studio project performance settings.
The use of GPU for training and Parallel DSP jobs is currently an internal experimental feature that will be soon released.
To bring even more flexibility to projects, the administrative zone gives developers the power to enable other additional features that are not found in edge impulse projects by default. Most of these features are usually advanced features intended for organizations or sometimes experimental features.
To activate these features you just need to check the boxes against the specific features you want to use and click save experiments.
Edge Impulse Studio project danger zone settings.
The danger zone widget consists of irrevocable actions that let you to:
- Perform train/test split. This action re-balances your dataset by splitting all your data automatically between the training and testing set and resets the categories for all data.
- Launch the getting started wizard. This will remove all data, and clear out your impulse.
- Transfer ownership. This action is available for users who have one or more organizations linked with their accounts. With it, you can start working on a project with your user profile and then transfer the ownership to your organization.
- Delete your project. This action removes all devices, data, and impulses from your project.
- Delete all data in this project.