Hi, thanks for great work !
In the file tools/generate_detections.py, input of bgr image is feeded to the re-id encoder. The process of preprocessing only contain bgr --> rgb
But in the repo Cosine Metric Learning, the preprocessing is: bgr --> rgb --> divided by 255
I saw that you has noticed that two versions contain a minor differences. So I wondering that this current implementation (without normalization) is correct or not ?
I have tried with bgr --> rgb --> divide by 255. and it shows a significant losing performance. So I think the current implementation is correct but slightly difference with the repo Cosine Metric Learning.
Hi, thanks for great work ! In the file
tools/generate_detections.py
, input of bgr image is feeded to the re-id encoder. The process of preprocessing only containbgr --> rgb
But in the repo Cosine Metric Learning, the preprocessing is:bgr --> rgb --> divided by 255
I saw that you has noticed that two versions contain a minor differences. So I wondering that this current implementation (without normalization) is correct or not ?