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View Code? Open in Web Editor NEWA new test set for ImageNet
License: MIT License
A new test set for ImageNet
License: MIT License
I try to use eval.py to replicate your experiments.
But I get hang on downloading the needed pickle file.
When I check the boto document, it says that you must provide access key and access token for using boto3.
Is AWS needed or there are some other ways to download the data?
I tried this dataset on some models trained with ImageNet but got extremely bad accuracy. Later, I find that the class index may not match with ImageNet. Did I do something wrong?
I nearly find the following relationship:
Index 0 in V2 ---> 782 screen, CRT screen in original ImageNet
Index 1 in V2 ---> 263 Pembroke, Pembroke Welsh corgi in original ImageNet
Could you please public the "original" dataset that is not scaled? I need it because flickr seems lost/change some of the images and it's hard to retrieve all non-scaled images now.
hello
i am having permission denied error when using this command to download the dataset
wget https://s3-us-west-2.amazonaws.com/imagenetv2public/imagenetv2-matched-frequency.tar.gz
HTTP request sent, awaiting response... 403 Forbidden
Do you have any plan to make the human selection frequency public for ImageNetV2? If it is already available, where can we find it?
I followed the instructions and ran eval.py. It seems that everything works fine until it tries to download "metadata/candidate_metadata_2018-12-13_04-35-19_UTC.pickle" in candidate_data.py. It is hanging here for hours and I also try to use wget to manually get the data but it is 403 forbidden:
wget http://imagenet2datav2.s3.amazonaws.com/metadata/candidate_metadata_2018-12-13_04-35-19_UTC.pickle
--2019-03-10 22:00:38-- http://imagenet2datav2.s3.amazonaws.com/metadata/candidate_m
etadata_2018-12-13_04-35-19_UTC.pickle
Resolving imagenet2datav2.s3.amazonaws.com (imagenet2datav2.s3.amazonaws.com)... 52.2
18.209.74
Connecting to imagenet2datav2.s3.amazonaws.com (imagenet2datav2.s3.amazonaws.com)|52.
218.209.74|:80... connected.
HTTP request sent, awaiting response... 403 Forbidden
2019-03-10 22:00:38 ERROR 403: Forbidden.
Could you help me with this issue please?
Also what I tried to get is the frequency of manual labeled pictures that discussed in the paper.
It is said that the matchedFrequency test set follows the estimation of frequency in original test set. But the imagenet data doesn't have this frequency information. May I know where I can also get the frequency information for the original test set please? (everything I need is to reproduce Figure 15-17 in the paper)
Thanks!
Hello,
It seems that the file names of ImageNetV2 have been changed.
Could you provide the mappings between old and new filenames?
Thanks!
Hello! First of all, thank you for sharing your work :)
I tried downloading the dataset from the link specified in the README (http://imagenetv2public.s3-website-us-west-2.amazonaws.com/) but I'm getting a 403 forbidden error. Would you please look into this?
https://paperswithcode.com/sota/image-classification-on-imagenet-v2
as we can see the sota on paperwithcode, but I didn't find which dataset they use.
imagenetv2-matched-frequency
imagenetv2-threshold0.7
imagenetv2-topimages
Hello.
I found that for some OS system (my environment is Ubuntu20.04), the class_to_idx
property of dataset.ImageFolder
is not aligned with the directories' name, so it leads to wrongly label samples.
For instance, the directory 100 (str)
is labelled with 2 (int)
class. The easiest way to resolve the above issue is, from the dataset.ImageFolder
source code (https://pytorch.org/vision/stable/_modules/torchvision/datasets/folder.html#ImageFolder), modifying the line in find_classes
function class_to_idx = {cls_name: i for i, cls_name in enumerate(classes)}
with class_to_idx = {cls_name: int(cls_name) for cls_name in classes}
.
(stated in the paper)
Just wondering!
Hello, I'm trying to get the mapping from class labels to IDs, and presumably this is done by running python generate_class_info_file.py
from within the code
directory (please let me know if this is wrong).
Upon running this, I hit the following error:
Traceback (most recent call last):
File "generate_class_info_file.py", line 8, in <module>
imgnet = imagenet.ImageNetData(load_class_info=False)
TypeError: __init__() got an unexpected keyword argument 'load_class_info'
Indeed, imagenet.ImageNetData does not have a kwarg called "load_class_info". Perhaps this code is outdated?
If there is an easier way for me to simply get the map from label IDs to the original class name strings, please let me know. Thank you!
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