Comments (13)
Suppose you have 3 gallery samples with ID 0,1,1
and 4 query samples with ID 0,0,1,1
, then you need to
Compute 3x4 pairwise distance matrix D
, where D[i, j]
= distance between gallery-i and query-j
Create a query ID list qids = [0,0,1,1]
Create a gallery ID list gids = [0,1,1]
Then you can call reid.evaluation_metrics.cmc(D, qids, gids)
to get CMC.
from open-reid.
1.why is ID 0,1,1 ? it mean the second and the third are the same person ?
2.so ID 0,1,1 don't have like cuhk03 ID 0000 0001 0002 0003 .....(many ID) ?
from open-reid.
- Yeah, it's just an example. The second and the third belong to the same person identity.
- It's just an example to help you understand.
from open-reid.
cuhk03 is use val to compute CMC right?
from open-reid.
I am not sure what you refer to. All the results here in open reid are reported on the test set.
from open-reid.
hi
1. what are the gallery , query and probe ?
- if the value of distance matrix is large = the pairwise is not the same person
the value of distance matrix is small= the pairwise is the same person
right?
from open-reid.
@Phoebe-star query is the same means as probe,you have a query(probe)image and then you should find the image that have the same id in the gallery. and we have a rank list of the gallery images ,CMC is caculated based on the list
from open-reid.
@Linranran Thank you very much for the explanation!
@Phoebe-star Yes, large distance value implies the pair is probably not the same person, and vice versa.
from open-reid.
@Cysu its my pleasure,haha
from open-reid.
I got it , thanks you ^^
from open-reid.
I have another problem
how to select cuhk03 dataset validation to compute CMC ??
every time , I got a different cmc value
from open-reid.
I have another question in computing CMC and mAP of cuhk03. Open reid gived me the result that rank1 was greater than mAP, but When I read some papers such as “SVDNet for Pedestrian Retrieval”, they showed the results that mAP was greater than rank1. I'm comfused all the time even after I read Evaluation Metrics in docs of open reid. Could anyone help me figure out that or just point me to some helpful website?
from open-reid.
what is your cmc code ?
from open-reid.
Related Issues (20)
- Dependencies - setup.py
- is it generalised
- DukeMTMC dataset can't be downloaded HOT 2
- Problem with the file examine.softmax_loss.py HOT 5
- It can not converge on non-pretrained model HOT 1
- Train with only 1 camera in duke
- Viper is missing HOT 2
- TypeError: Can't instantiate abstract class Euclidean with abstract methods get_metric, score_pairs HOT 1
- How much video memory do I need? HOT 1
- DukeMTMC result reporting
- OIM loss HOT 1
- OIM loss initialize error
- IndexError: invalid index of a 0-dim tensor. HOT 6
- RuntimeError: zero-dimensional tensor (at position 0) cannot be concatenated
- RuntimeError: Duke
- TypeError: Can't instantiate abstract class Euclidean with abstract methods get_metric, score_pairs HOT 2
- something miss with sort and match? HOT 1
- AssertionError: Torch not compiled with CUDA enabled
- Oim Loss with 'NAN' problem
- eep q learning
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