I trained an object detection model on synthetic inputs
Description:
In this video, we dive into the fascinating world of training AI models using synthetic image data! By creating 3D renders of chocolate bars in Blender, we can significantly enhance object detection capabilities and expedite the generation of training data. Watch as we explore each step of the process, from modeling to testing on various colored chocolate bars.
Timestamps:
00:00 🍫 Training AI on synthetic image data for object detection using 3D modeling of chocolate bars in Blender and testing the algorithm on different colored bars.
00:50 👩🏫 AI is trained on synthetic image data for object detection using Blender and Unity to generate and save images with bounding boxes for training data.
01:19 🤖 Use synthetic image data to train AI for object detection, test models on phone using Ultralytics, and achieve successful training with bounding boxes.
02:00 🤖 The AI overfits on the red chocolate bar and gets confused when presented with the orange one.
02:41 🤖 Model trained on red and orange can accurately detect between the two, but not green, showing the specificity of the training data.
03:09 🤖 AI can detect images in milliseconds, unlike large Tech models which take longer, making it amazing.
03:53 🤖 Synthetic data generation helps AI models differentiate between similar colors and scenarios for object detection.
04:22 🤖 Large language models and multimodal models can be used to train smaller specific models for various applications, such as self-driving car technology, and the speaker is open to ideas for future projects.
Join us as we explore the potential of synthetic data in AI training and object detection. Don't forget to like, share, and subscribe for more insightful content!
