nicolalandro_ntsnet-cub200_ntsnet.md

layout	background-class	body-class	category	title	summary	image	author	tags	github-link	github-id	featured_image_1	featured_image_2	accelerator	demo-model-link
hub_detail	hub-background	hub	researchers	ntsnet	classify birds using this fine-grained image classifier	Cub200Dataset.png	Moreno Caraffini and Nicola Landro	vision	https://github.com/nicolalandro/ntsnet-cub200	nicolalandro/ntsnet-cub200	nts-net.png	no-image	cuda-optional	https://huggingface.co/spaces/pytorch/NTSNET

import torch
model = torch.hub.load('nicolalandro/ntsnet-cub200', 'ntsnet', pretrained=True,
                       **{'topN': 6, 'device':'cpu', 'num_classes': 200})

사용 예제

from torchvision import transforms
import torch
import urllib
from PIL import Image

transform_test = transforms.Compose([
    transforms.Resize((600, 600), Image.BILINEAR),
    transforms.CenterCrop((448, 448)),
    # transforms.RandomHorizontalFlip(),  # only if train
    transforms.ToTensor(),
    transforms.Normalize((0.485, 0.456, 0.406), (0.229, 0.224, 0.225)),
])


model = torch.hub.load('nicolalandro/ntsnet-cub200', 'ntsnet', pretrained=True, **{'topN': 6, 'device':'cpu', 'num_classes': 200})
model.eval()

url = 'https://raw.githubusercontent.com/nicolalandro/ntsnet-cub200/master/images/nts-net.png'
img = Image.open(urllib.request.urlopen(url))
scaled_img = transform_test(img)
torch_images = scaled_img.unsqueeze(0)

with torch.no_grad():
    top_n_coordinates, concat_out, raw_logits, concat_logits, part_logits, top_n_index, top_n_prob = model(torch_images)

    _, predict = torch.max(concat_logits, 1)
    pred_id = predict.item()
    print('bird class:', model.bird_classes[pred_id])

모델 설명

이 모델은 세분화된 조류 데이터셋인 CUB200 2011 데이터셋으로 사전 학습된 nts-net입니다.

참조

link - 여기에서 전체 내용을 읽을 수 있습니다.

@INPROCEEDINGS{Gallo:2019:IVCNZ,
  author={Nawaz, Shah and Calefati, Alessandro and Caraffini, Moreno and Landro, Nicola and Gallo, Ignazio},
  booktitle={2019 International Conference on Image and Vision Computing New Zealand (IVCNZ 2019)},
  title={Are These Birds Similar: Learning Branched Networks for Fine-grained Representations},
  year={2019},
  month={Dec},
}