This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" on Object Detection and Instance Segmentation. - SwinTransformer/Swin-Transformer-Object-Detection
This branch is 3 commits behind SwinTransformer/Swin-Transformer-Object-Detection:master.Folders and files Latest commit Cannot retrieve latest commit at this time. History1,510 Commits .dev_scripts [Fix] check for CLASSES in checkpoint meta (open-mmlab#4936) Apr 12, 2021 .github Add paper conf...
github下得很慢可以用这个 ghproxy.com下 8.测试验证 from mmdet.apis import init_detector, inference_detector config_file = '/root/Swin-Transformer-Object-Detection-master/Swin-Transformer-Object-Detection-master/configs/swin/mask_rcnn_swin_tiny_patch4_window7_mstrain_480-800_adamw_1x_coco.py' #...
Swin-Transformer代码地址:https://github.com/SwinTransformer/Swin-Transformer-Object-Detection,先按照说明安装。下面以Faster-RCNN进行说明,Swin-Transformer方法应该可类似处理。 第一步,准备数据,放置在data目录下 1 2 3 4 5 6 7 8 9 data coco train2017/1.jpg val2017/2.jpg test2017/3.jpg annotations...
Swin-Transformer-Object-Detection(Github):https://github.com/SwinTransformer/Swin-Transformer-Object-Detection [2] Swin Transformer 论文:https://arxiv.org/abs/2103.14030 [3] mmdetection(Github):https://github.com/open-mmlab/mmdetection [4] ...
源代码:https://github.com/microsoft/Swin-Transformer 计算机视觉研究院专栏 作者:Edison_G MSRA时隔大半年放出了Swin Transformer 2.0版本,在1.0版本的基础上做了改动,使得模型规模更大并且能适配不同分辨率的图片和不同尺寸的窗口!这也证实了,Transformer将是视觉领域的研究趋势!
这里选择的是 ”Faster-RCNN-Inception-V2“,下载完毕后放入上面模型库里的 object-detection-model\research\object_detection 下面。 3. 下载国外博主提供的 demo 地址:https://github.com/EdjeElectronics/TensorFlow-Object-Detection-API-Tutorial-Train-Multiple-Objects-Windows-10#3-gather-and-label-pictures,...
Swin-Transformer代码地址:https://github.com/SwinTransformer/Swin-Transformer-Object-Detection,先按照说明安装。下面以Faster-RCNN进行说明,Swin-Transformer方法应该可类似处理。 第一步,准备数据,放置在 data目录下 data coco train2017/1.jpg val2017/2.jpg ...
5. 需要提前下载预训练模型(.pth),并存进根目录。下载地址:https://github.com/SwinTransformer/Swin-Transformer-Object-Detection#cascade-mask-r-cnn 6. 测试环境配置是否成功所用命令: python demo/image_demo.py demo/demo.jpg configs/swin/mask_rcnn_swin_tiny_patch4_window7_mstrain_480-800_adamw_3x...
从链接https://github.com/SwinTransformer/Swin-Transformer-Object-Detection下载的pretrained model 会有问题,建议从链接https://github.com/microsoft/Swin-Transformer下载 swin_tiny_patch4_window7_224.pth 预训练模型。 问题梳理 训练启动后关于 backbone registry 的 KeyError的问题 ...