re-implementation M2Det in pytorch based on official M2Det codes here, currently it only support 512x512 training like origianl repo.
- SSD algorithm is base on simple_ssd_pytorch which is extracted from mmdetection.
- pretrained vgg16 model weight was from caffe on here, so some slightly difference on backbone vgg16 model & mean/std setting as well.
- support single-GPU/multi-GPU training
- compatiable to mmdetection framework, the MLFPN module can be integrate to mmdetection lib. but for some reason, the interface was little different, little change may needed.
- from author's paper, it takes 6days for training with VGG16/512x512 on 4 Titan X, 3days for VGG16/320x320 on 4 Titan X.
- compare performance with original implementation
- support 320x320 input size
- support eval on voc
- support distributed training