Im using a pre-trained image classifier to evaluate input data treatments. I downloaded the ImageNet ILSVRC2014 CLS-LOC validation dataset to use as base. I need to know the actual classes of the images to evaluate my treatments (need to detect correct classifications). In the 2014 toolkit there is ILSVRC2014_clsloc_validation_ground_truth.txt file that according to the readme is supposed to contain class labels (in form of ID:s) for the 50 000 images in the data set. There are 50 000 entries/lines in the file so this far all seems good but i also want the corresponding semantic class labels/names.
I found these in a couple of places online and they seem to be coherent (1000 classes). But then i looked at the first image which is a snake, the ground truth for the first pic is 490, the 490:th row in the semantic name list is "chain". That's weird but still kind of close. The second image is two people skiing, the derived class "polecat". I tried many more with similar results.
I must have misunderstood something. Isn't the ground truth supposed to be the "correct" answers for the validation set? Have i missed something in the translation between ID:s and semantic labels?
The readme in the 2014 imagenet dev-kit states: " There are a total of 50,000 validation images. They are named as
ILSVRC2012_val_00000001.JPEG
ILSVRC2012_val_00000002.JPEG
...
ILSVRC2012_val_00049999.JPEG
ILSVRC2012_val_00050000.JPEG
There are 50 validation images for each synset.
The classification ground truth of the validation images is in data/ILSVRC2014_clsloc_validation_ground_truth.txt, where each line contains one ILSVRC2014_ID for one image, in the ascending alphabetical order of the image file names.
The localization ground truth for the validation images can be downloaded in xml format. "
Im doing this as part of my bachelor thesis and really want to get it right.
Thanks in advance
This problem is now solved. In the ILSVRC2017 development kit there is a map_clsloc.txt file with the correct mappings.