YOLO26

Why Isn’t a Ready-Made Model Enough? A Practical Lesson in Fine-Tuning Object Detection Models on Real-World Data

Through an experiment involving YOLO12, YOLO26, and RF-DETR, JetBrains shows that models pretrained on COCO can approach zero when transferred directly to specialized domains, while fine-tuning improves results to varying degrees. The experiment reveals that the similarity between the target domain and the training data, along with localization accuracy and inference time, matters more than relying on a model’s classification as the newest or best.