hustvl/yolos-tiny
The YOLOS model, a Vision Transformer (ViT) trained using the DETR loss, achieved an AP of 28.7 on COCO 2017 validation, outperforming other state-of-the-art object detection models while being much simpler. It was pre-trained on ImageNet-1k and fine-tuned on COCO 2017 object detection, a dataset consisting of 118k/5k annotated images for training/validation respectively. The model uses a bipartite matching loss and is trained using standard cross-entropy and a linear combination of the L1 and generalized IoU loss.
The YOLOS model, a Vision Transformer (ViT) trained using the DETR loss, achieved an AP of 28.7 on COCO 2017 validation, outperforming other state-of-the-art object detection models while being much simpler. It was pre-trained on ImageNet-1k and fine-tuned on COCO 2017 object detection, a dataset consisting of 118k/5k annotated images for training/validation respectively. The model uses a bipartite matching loss and is trained using standard cross-entropy and a linear combination of the L1 and generalized IoU loss.
HTTP/cURL API
Input fields
webhookfile
The webhook to call when inference is done, by default you will get the output in the response of your inference request
