标签:

• 图像分类
• 生态学
• 真菌
• FGVC 库名称: DanishFungi 许可证: cc-by-nc-4.0

BVRA/beit_base_patch16_384.in1k_ft_df24_384 模型卡

模型详情

• 模型类型: 丹麦真菌分类
• 模型统计:
  • 参数量 (百万): 88.2
  • 图像尺寸: 384 x 384
• 相关论文:
• 原始论文: ??
• 训练数据集: DF24 --> https://sites.google.com/view/danish-fungi-dataset

模型使用

图像嵌入

import timm
import torch
import torchvision.transforms as T
from PIL import Image
from urllib.request import urlopen
model = timm.create_model("hf-hub:BVRA/beit_base_patch16_384.in1k_ft_df24_384", pretrained=True)
model = model.eval()
train_transforms = T.Compose([T.Resize((384, 384)), 
                              T.ToTensor(), 
                              T.Normalize([0.5, 0.5, 0.5], [0.5, 0.5, 0.5])]) 
img = Image.open(您的图片路径)
output = model(train_transforms(img).unsqueeze(0))
# 输出为形状 (1, 特征数) 的张量

引用文献

@InProceedings{Picek_2022_WACV,
    author    = {Picek, Luk'a{s} and {S}ulc, Milan and Matas, Ji{r}{'\i} and Jeppesen, Thomas S. and Heilmann-Clausen, Jacob and L{e}ss{\o}e, Thomas and Fr{\o}slev, Tobias},
    title     = {Danish Fungi 2020 - Not Just Another Image Recognition Dataset},
    booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
    month     = {January},
    year      = {2022},
    pages     = {1525-1535}
}

@article{picek2022automatic,
  title={Automatic Fungi Recognition: Deep Learning Meets Mycology},
  author={Picek, Luk{'a}{{s}} and {{S}}ulc, Milan and Matas, Ji{{r}}{'\i} and Heilmann-Clausen, Jacob and Jeppesen, Thomas S and Lind, Emil},
  journal={Sensors},
  volume={22},
  number={2},
  pages={633},
  year={2022},
  publisher={Multidisciplinary Digital Publishing Institute}
}