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Official implementation of "RCS-YOLO: A Fast and High-Accuracy Object Detector for Brain Tumor Detection".

License: GNU General Public License v3.0

Python 99.47% Shell 0.38% Dockerfile 0.15%
brain-tumor-detection computer-vision convolutional-neural-networks deep-learning deep-neural-networks medical-image-analysis object-detection reparameterization yolo br35h-brain-tumor-detection-2020

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rcs-yolo's Issues

Missing Model Weights for Reproduction

Thanks to the authors for the interesting work and for sharing your code.

I'd love to reproduce the results presented at MICCAI23. However, I couldn't find best.pt following the link from your documentation:

The model weights we pretrained on the brain tumor detection was saved as best.pt in the directory ./runs/train/exp/weights/.

Can you point me to the correct folder for the trained weights?

Thx!

The model cannot complete the detection.

Hello, I encountered the issue shown in the image below while reproducing your work. I used the data you provided, but it seems that the model cannot complete the training properly. What could be the reason for this?
4dbb8091babaa5fcb68e3d1eb5ecda9

请问RCS-OSA模块替换YOLOv5中的C3模块是否可以提升检测速度?

首先非常感谢您的工作!在您的论文中提到在RCS-YOLO、RepVGG-CSP的消融实验,想请问一下是否是在相同的位置采用BottleneckCSPC、RCS-OSA两个模块进行实验对比?如果是我认为的这样,BottleneckCSPC仅比C3模块多一个conv1x1,那在YOLOv5中,采用RCS-OSA替换C3模块应该也可以提升模型的检测性能。请问您是否做过RCS-OSA有效性的验证实验?该模块是否能提升检测速度?

pt转trt后为什么速度提升不大?

pt模型下,在YOLOv5中加了rcsosa模块后比原始yolov5精度高、速度快;
但转成tensorrt后,速度比原始yolov5慢很多,请问是什么原因?

A videographic Demonstration on how to execute the code

Hello,
I have executed the code many times but I still can't figure out where I am going wrong. When I run train.py it creates runs/exp/weights, but there are no best.pt and las.pt files in that. Please help me on how to execute the code from scratch

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