YOLOS (small sized) model This model is a fine tuned version of hustvl/yolos small on the licesne plate recognition dataset from Roboflow which contains 5200 images in the training set and 380 in the validation set. The original YOLOS model was fine tuned on COCO 2017 object detection (118k annotated images). Model description YOLOS is a Vision Transformer (ViT) trained using the DETR loss. Despite its simplicity, a base sized YOLOS model is able to achieve 42 AP on COCO validation 2017 (similar to DETR and more complex frameworks such as Faster R CNN). Intended uses & limitations You can use the raw model for object detection. See the model hub to look for all available YOLOS models. How to use Here is how to use this model: Currently, both the feature extractor and model support PyTorch. Training data The YOLOS model 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. Training This model was fine tuned for 200 epochs on the licesne plate recognition. Evaluation results This model achieves an AP (average precision) of 49.0 . Accumulating evaluation results... IoU metric:…
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