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Why Train Your Own Models?

Using pre-trained AI models might seem convenient, but training custom models gives your FIRST team a competitive edge.

The Problem with Generic Models​

Every robot is unique. A model trained on someone else's robot won't work optimally on yours because:

🎥 Camera Differences​

  • Mounting Position: Your camera's height and angle are unique
  • Hardware Variations: Different sensors capture images differently (color, exposure, distortion)
  • Lens Characteristics: Each camera sees the world slightly differently

⚡ Performance Benefits​

  • Fewer False Positives: Waste less autonomous time on incorrect detections
  • Faster Inference: Optimized for exactly what you need to detect
  • Tunable Confidence: Adjust thresholds for your strategy

Optional: Lighting Calibration​

Advanced Technique

While you can capture training images in specific competition venue which can help with variations in backgrounds, carpet colors, and lighting this is usually overkill. YOLO-Pro handles typical lighting variations well. Focus on diverse angles and distances instead—only worry about lighting if you're experiencing actual detection failures.

The Bottom Line​

Your robot → Your camera → Your model

Custom training means your robot sees the world the way it actually experiences it. This is what separates good vision systems from great ones.

Ready to get started? Continue to learn about AI basics and follow our step-by-step tutorial.