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metadata
tags:
  - image-classification
  - ecology
  - fungi
  - FGVC
library_name: DanishFungi
license: cc-by-nc-4.0

Model card for BVRA/resnet34.ft_in1k_df20m_299

Model Details

Model Usage

Image Embeddings

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/resnet34.ft_in1k_df20m_299", pretrained=True)
model = model.eval()
train_transforms = T.Compose([T.Resize((299, 299)), 
                              T.ToTensor(), 
                              T.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])]) 
img = Image.open(PATH_TO_YOUR_IMAGE)
output = model(train_transforms(img).unsqueeze(0))  # output is (batch_size, num_features) shaped tensor

Citation

https://openaccess.thecvf.com/content/WACV2022/papers/Picek_Danish_Fungi_2020_-_Not_Just_Another_Image_Recognition_Dataset_WACV_2022_paper.pdf