From 82c0a2ff1279de472b704330f046acfb4b6bbe9f Mon Sep 17 00:00:00 2001 From: Ross Wightman Date: Sun, 2 Feb 2020 19:37:18 -0800 Subject: [PATCH] Update README.md Fix relative paths (I think) --- results/README.md | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/results/README.md b/results/README.md index 40bb8682..6bb160d7 100644 --- a/results/README.md +++ b/results/README.md @@ -6,28 +6,28 @@ This folder contains validation results for the models in this collection having There are currently results for the ImageNet validation set and 3 additional test sets. -### ImageNet Validation - [`results-imagenet.csv`](results/results-imagenet.csv) +### ImageNet Validation - [`results-imagenet.csv`](results-imagenet.csv) * Source: http://image-net.org/challenges/LSVRC/2012/index * Paper: "ImageNet Large Scale Visual Recognition Challenge" - https://arxiv.org/abs/1409.0575 The standard 50,000 image ImageNet-1k validation set. Model selection during training utilizes this validation set, so it is not a true test set. -### ImageNetV2 Matched Frequency - [`results-imagenetv2-matched-frequency.csv`](results/results-imagenetv2-matched-frequency.csv) +### ImageNetV2 Matched Frequency - [`results-imagenetv2-matched-frequency.csv`](results-imagenetv2-matched-frequency.csv) * Source: https://github.com/modestyachts/ImageNetV2 * Paper: "Do ImageNet Classifiers Generalize to ImageNet?" - https://arxiv.org/abs/1902.10811 An ImageNet test set of 10,000 images sampled from new images roughly 10 years after the original. Care was taken to replicate the original ImageNet curation/sampling process. -### ImageNet-Sketch - [`results-sketch.csv`](results/results-imagenet-sketch.csv) +### ImageNet-Sketch - [`results-sketch.csv`](results-imagenet-sketch.csv) * Source: https://github.com/HaohanWang/ImageNet-Sketch * Paper: "Learning Robust Global Representations by Penalizing Local Predictive Power" - https://arxiv.org/abs/1905.13549 50,000 non photographic (or photos of such) images (sketches, doodles, mostly monochromatic) covering all 1000 ImageNet classes. -### ImageNet-Adversarial - [`results-imagenet-a.csv`](results/results-imagenet-a.csv) +### ImageNet-Adversarial - [`results-imagenet-a.csv`](results-imagenet-a.csv) * Source: https://github.com/hendrycks/natural-adv-examples * Paper: "Natural Adversarial Examples" - https://arxiv.org/abs/1907.07174