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{ | |
"citation": "@inproceedings{vinyals2016matching,\n title={Matching networks for one shot learning},\n author={Vinyals, Oriol and Blundell, Charles and Lillicrap, Timothy and Wierstra, Daan and others},\n booktitle={Advances in neural information processing systems},\n pages={3630--3638},\n year={2016}\n}\n", | |
"description": "miniImageNet (Vinyals et al., 2016) is a modified version of the ILSVRC-12\ndataset (Russakovsky et al., 2015), in which 600 images for each of 100 classes\nwere randomly chosen to be part of the dataset. We rely on the class split used\nby Ravi & Larochelle (2017). These splits use 64 classes for training, 16 for\nvalidation, and 20 for test. All images are of size 84 \u00d7 84 pixels.\n", | |
"downloadChecksums": { | |
"https://drive.google.com/uc?export=download&id=16V_ZlkW4SsnNDtnGmaBRq2OoPmUOc5mY": "30052347dd33f3ea3ee4a4ad65d72152bf657aac41891299dfa614a3235947ed" | |
}, | |
"location": { | |
"urls": [ | |
"https://github.com/renmengye/few-shot-ssl-public#miniimagenet" | |
] |
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# Adapted from `demo.py` | |
import sys; sys.path.append('..') # add settings. | |
import os | |
import torch | |
import cv2 | |
import time | |
import pyrender | |
import numpy as np | |
import trimesh |