Closed dzambrano closed 5 years ago
I didn't try all, but same with me VGG_VOC0712_SSD_300x300_ft_iter_120000 achieved 80.6 instead of 81.2 mAP
. In evalutation code, there are two evaluation metric. 'Previous metric' and 'Recent metric'. I think code author wrote using recent VOC metric, cause, recent one give us higher mAP than previous one in my model. I didn't try using VGG_VOC0712_SSD_300x300_ft_iter_120000.h5
though. My guess.
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I am having the same issue also. I cannot get the reported mAP neither for the provided ported weights from Caffe nor for the pretrained model from scratch.
The reported mAP should be 0.772
according to the original caffe or 0.775
according to the repo. Also, how is that to use the caffe ported pretrained weights and get 0.3% higher performance?
The reported mAP for the provided model trained from scratch should be 0.771
while I get 0.761
. Any explanation on that divergence?
Dear @pierluigiferrari,
Thank you so much for this repo, I found it really useful. I am trying to evaluate the models you provided and I can't achieve exactly the same numbers are shown in the documentation.
ssd300_evaluation.ipynb
example, you load the weights of a model fine tuned (weights_path = 'path/to/trained/weights/VGG_VOC0712_SSD_300x300_ft_iter_120000.h5'
) which should have the scales for MS COCO. However, the scales for Pascal are used.VGG_VOC0712_SSD_300x300_iter_120000
achieved 76.5 instead of 77.5 mAP;VGG_VOC0712_SSD_300x300_ft_iter_120000
achieved 80.6 instead of 81.2 mAP;VGG_VOC0712_SSD_512x512_iter_120000
achieved 78.9 instead of 79.8 mAP;VGG_VOC0712_SSD_512x512_ft_iter_120000
achieved 82.7 instead of 83.2 mAP.I used the same settings you described in
ssd300_evaluation.ipynb
(with the relative changing in scales or input image where needed). My system runs on Tensorflow 1.12 and cuDNN 7.0.Am I doing something wrong? Is there a specific parameter that needs to change in your example?