Synthetic Data for Computer Vision

Why use Synthetic Data and Augmented Data?

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To build robust, high-performing computer vision models, you need data—and lots of it. That’s why synthetic data and augmented data tools have now been integrated into the Chooch AI Platform.

This means the AI lifecycle is now shorter, because you can train AI models faster and with less data. How? By automatically generating thousands of annotated images, and then using these synthetic images to train and deploy computer vision models.

Data augmentation takes your annotated images and transforms them: e.g. distorting them, cropping them, flipping and rotating them, adding noise, and pasting objects onto new backgrounds.

Synthetic data generation creates training data for your AI models in the form of high-quality, realistic, and highly diverse computer-generated images. With just two files of the desired object—a 3D geometry file and its corresponding texture file—you can generate hundreds or thousands of images that will significantly boost the performance of your computer vision models.

The result? Computer vision with synthetic data.

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Generating Synthetic Data for Computer Vision AI Training

What are the Benefits of Synthetic Data for Computer Vision?

The benefits of synthetic data generation and data augmentation include:

Better model performance: By training on larger, more diverse datasets, computer vision models are more likely to generalize well to real-world scenarios. Data augmentation forces the model to learn the underlying concepts and patterns in the dataset, instead of “overfitting” by learning to recognize the data itself. Meanwhile, synthetic data generation varies factors such as the image viewpoint, object pose, backgrounds, and lighting conditions so that the model learns the underlying truth about what the object really looks like.
Less time, money, and effort: Automated data augmentation generates potentially dozens of augmented images from a single source image, almost instantaneously. Similarly, synthetic data generation can create hundreds or thousands of realistic, high-quality, labeled training data with just a few clicks. With synthetic data generation, there’s no need for humans to spend time manually collecting and annotating training data.
Greater control: Generating synthetic data allows you to specify exactly the types of images you want to create. This can be helpful for enhancing your dataset with images that are less common or hard to find.

What are the Use Cases of Synthetic Data Generation?

Any object that can be modeled in 3D can also be used for synthetic data generation. Below are just a few possible use cases of synthetic data generation:

Generating different angles of a piece of machinery in order to identify the different components and parts.
Generating images of biological cells to train a computer vision model (e.g., identifying different cell types or distinguishing between cancerous and non-cancerous cells).
Generating various manufacturing defects (e.g., cracks, missing parts, misshaped items, etc.) so that a computer vision model can learn to identify defective products.

How to Generate Synthetic Data and Augmented Data

There’s just one question: how do you generate synthetic data and augmented data? With the help of visual AI platforms like Chooch, synthetic data generation and data augmentation are as simple as a few clicks.

Data augmentation: Click on the “Augmentation” button in the Chooch dashboard to augment a given dataset. You can choose from multiple options: shifting, scaling, rotating, flipping, noise, blurring, contrast, and brightness. You can use the default parameters, or fine-tune them to your liking. Finally, select the number of augmented images to generate from each source image.

Synthetic data generation: First, upload your .OBJ 3D geometry file and the associated .MTL texture file to Chooch. Then, you can specify the image background and the number of images you want to create. The Chooch platform will automatically generate images, along with their corresponding bounding box annotations, in a matter of seconds.

Data Augmentation

Data augmentation on Chooch AI provides the ability to copy and modify 2D objects hundreds of times to train AI models faster.

Next Steps

With Chooch AI, you can quickly generate models onto your devices so you can start testing the platform immediately. We can also create custom models for your particular use case. To get started with a drone-based AI solution, fill out the form to create an account on the Chooch AI platform now.

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