url="https://path_to_your_image.jpg"image=Image.open(requests.get(url,stream=True).raw)# 对图像进行预处理 inputs=processor(images=image,return_tensors="pt")# 推理并获取检测结果withtorch.no_grad():outputs=model(**inputs)# 处理检测结果(无需NMS) target_sizes=torch.tensor([image.size[::...
第五,改进检测头,更换检测头这种也算个大的改进点。 第六,改进损失函数,nms、框等,要是有提升检测效果的话,算是一个小的改进点,也可以凑字数。 第七,对图像输入做改进,改进数据增强方法等。 第八,剪枝以及蒸馏等,这种用于特定的任务,比如轻量化检测等,但是这种会带来精度的下降。 ...未完待续 一、创新改...
This is because there are NaN values produced in training process. The rtdetr training withamp=Trueis more sensitive than yolo models to custom datasets, probably it's related to the transformer architecture and nms-free design(we might figure out a better solution for this in the future). ...
However, W-MSA only processes self-attention within each window, meaning there is no information exchange between windows. To address this limitation, the SW-MSA module is introduced, allowing information to be exchanged between windows and enhancing the overall information flow in the model. The ...
-maximum suppression (NMS) process. In addition, the mosaic augmentation technique of stitching four images together into one is partially removed, a method that does not use mosaic more than ten epochs before the end of training. With these changes, YOLOv8 improves both accuracy and inference ...
However, the issue of the high computational cost of DETRs has not been effectively addressed, limiting their practical application and preventing them from fully exploiting the benefits of no post-processing, such as non-maximum suppression (NMS). In this paper, we first analyze the influence ...
(NMS). In 2023, Wenyu Lv proposed the real-time detection transformer (RT-DETR) [20], a real-time end-to-end object detector. In particular, they designed an efficient hybrid encoder to process multi-scale features efficiently by decoupling intra-scale interactions and cross-scale fusion. RT...