ultralytics 8.3.104

v8.3.104 - YOLOE explicit source `is not None` check (#20046)

on Python PyPI

🌟 Summary

This release (8.3.104) focuses on improving error handling, model validation, export flexibility, and documentation clarity for a smoother user experience. 🚀

📊 Key Changes

• Error Fix in YOLOE Predictions: Resolved an issue where NumPy arrays caused ambiguous truth value errors during predictions.
• Improved YOLOE Validation: Added support for loading models directly from file paths during validation.
• IMX500 Export Enhancement: Introduced a device parameter to allow GPU or CPU selection for faster and more efficient exports.
• Documentation Updates: Fixed outdated links and improved clarity in YOLOv8 examples for MNN and ONNXRuntime integrations.

🎯 Purpose & Impact

• Error-Free Predictions: Ensures compatibility with all source types, including NumPy arrays, making predictions more robust and reliable. 🛡️
• Streamlined Validation: Simplifies workflows by enabling direct model loading from file paths, saving time and effort. ⏱️
• Export Flexibility: Allows users to optimize IMX500 exports by selecting the appropriate hardware (GPU or CPU), improving performance and adaptability. ⚡
• Enhanced Documentation: Reduces confusion and improves navigation for developers, fostering a better user experience and encouraging contributions. 📚

This update ensures smoother operations across various use cases, from model predictions to exports and documentation, benefiting both new and experienced users. 🌟

What's Changed

• YOLOE: Fix validation when model loading from local file by @Laughing-q in #20050
• Add device argument to Sony imx export by @lakshanthad in #19768
• Fix YOLOv8-ONNXRuntime example links by @glenn-jocher in #20059
• ultralytics 8.3.104 YOLOE explicit source is not None check by @JShengP in #20046

Full Changelog: v8.3.103...v8.3.104