Comments (1)
@lengly Hi, comparing with our Titan X (Maxwell) x 4, your speed is much faster! You can try to train SSD_VOC2007_512_VGG16, which do not have TCBs and ODM module. His speed may be similar to ours, so we think the connections between TCB is not the main reason. Every batch has 32 images with 512 x 512 resolution for VGG16, we think the speed 1.2 s/iter is totally acceptable. We do not try to remove connections between TCB, you can try it and check the speed.
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Related Issues (20)
- test时的IOU标准在哪里设置 HOT 1
- 代码编译不通过 HOT 3
- 关于多尺度训练 HOT 6
- bash ./data/VOC0712/create_data.sh HOT 1
- asking for SRN training code HOT 2
- 帮忙看下detection_out层输出结果不正常 HOT 4
- map question HOT 2
- AttributeError: module 'caffe.proto.caffe_pb2' has no attribute 'LabelMap'
- I got low mAP HOT 3
- Test parameters
- batch inference issue HOT 2
- How to train this model on costumer dataset HOT 2
- About Tranfer Connection Block HOT 3
- More bounding boxes in images with people HOT 2
- Simple C++ implementation of any object classification HOT 2
- how to create single_test_deploy.prototxt HOT 3
- Where and how to modify the loss function ? HOT 1
- It doesn't work in OpenCV c++
- Quesation finetune a custom dataset with only 33 class
- 运行VGG16_VOC2007_320.py报错
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