SwinV2输出Transformer:这个版本依赖于原始的SwinV2 Backbone 网络,通过最小的架构更改进行训练。在简单的二分类任务上进行微调时,它具有轻量和高效的特点。 自定义层SwinV2输出 Transformer :此增强版在SwinV2 Backbone 网络的末端引入了额外的层,包括自注意力层和MLP层,以从输出数据中提取更细的特征。 每一版本的...
3、Swin预训练模型的加载(在ImageNet21K上训练) from transformers import AutoImageProcessor, Swinv2Model image_processor = AutoImageProcessor.from_pretrained("microsoft/swinv2-large-patch4-window12-192-22k") model = Swinv2Model.from_pretrained("microsoft/swinv2-large-patch4-window12-192-22k") image...
On top of that, we also introduce a Swin-Transformer-based UNet architecture, called Swinv2-Unet, which can address the problems stemming from the CNN convolution operations. Extensive experiments are conducted to evaluate the performance of the proposed model by using three real-world datasets, i...
huggingface_model_id : microsoft/swinv2-base-patch4-window12-192-22k training_dataset : imagenet-1k SharedComputeCapacityEnabled author : Microsoft license : apache-2.0 model_specific_defaults : ordereddict({'apply_deepspeed': 'true', 'apply_ort': 'true'}) task : image-classification hiddenlay...
Hello, we love and admire the work your doing :) Recently we tested SwinV2 capabilities for image restoration, compression artifacts removal and super-resolution. The properties it brings are amazing! we can achieve similar results to Sw...
作者验证了ViT-Adapter在多个下游任务上的有效性,包括目标检测、实例分割和语义分割。尤其,使用HTC++时,ViT-Adapter-L得到了60.1APb和52.1APm,在COCO test-dev上,超过 Swin-L 1.4APb和1.0APm。对于语义分割,ViT-Adapter-L在ADE20K val上建立了一个新的mIoU 60.5%,比SwinV2-G高0.6%。 开源地址:https://github...
NOTEBOOKS swinv2_small_window16_256 Language Python Table of Contents APTOS 2019 Blindness DetectionDetect diabetic retinopathy to stop blindness before it's too lateImporting Required LibrariesEDAData Splitting and TransformationFine Tuning The ModelsEvalutionEnd Competition Notebook APTOS 2019 Blindness Dete...
swinv2_small_window16_256_1.pt insert_drive_file swinv2_small_window16_256_2.pt insert_drive_file swinv2_small_window16_256_3.pt insert_drive_file swinv2_small_window16_256_4.pt insert_drive_file swinv2_small_window16_256_5.pt ...
通过扩大容量和分辨率,Swin Transformer 在四个具有代表性的视觉基准上创造了新记录:ImageNet-V2 图像分类的84.0% top-1 准确率,COCO对象检测的63.1 / 54.4 box / mask mAP,ADE20K语义分割的59.9 mIoU,和86.8%Kinetics-400视频动作分类的前 1 准确率。我们的技术通常适用于扩大视觉模型,但尚未像 NLP 语言模型...
PubDate: Sep 2022 Teams: University of W¨urzburg;MegaStudyEdu Writers: Marcos V. Conde, Ui-Jin Choi, Maxime Burchi, Radu Timofte PDF:Swin2SR: SwinV2 Transformer for Compressed Image Super-Resolution and Restoration Abstract Compression plays an important role on the efficient transmission and sto...