Migrations
/
pytorch-image-models
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Update README.md

Browse Source 
Fix relative paths (I think)
pull/83/head
Ross Wightman 5 years ago committed by GitHub
parent 1ffd2d0694
commit 82c0a2ff12
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
1 changed files with 4 additions and 4 deletions
Show Stats Download Patch File Download Diff File

8
results/README.md
Unescape View File

@ -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. 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 * Source: http://image-net.org/challenges/LSVRC/2012/index
* Paper: "ImageNet Large Scale Visual Recognition Challenge" - https://arxiv.org/abs/1409.0575 * 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. 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 * Source: https://github.com/modestyachts/ImageNetV2
* Paper: "Do ImageNet Classifiers Generalize to ImageNet?" - https://arxiv.org/abs/1902.10811 * 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. 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 * Source: https://github.com/HaohanWang/ImageNet-Sketch
* Paper: "Learning Robust Global Representations by Penalizing Local Predictive Power" - https://arxiv.org/abs/1905.13549 * 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. 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 * Source: https://github.com/hendrycks/natural-adv-examples
* Paper: "Natural Adversarial Examples" - https://arxiv.org/abs/1907.07174 * Paper: "Natural Adversarial Examples" - https://arxiv.org/abs/1907.07174

Write Preview
Loading…
Cancel
Save