pytorch-ssd for TME Dataset

A Pytorch implementation of Single Shot MultoBox Detector. The original code can be found here.

Installation

For installation, you can follow this repository (https://github.com/amdegroot/ssd.pytorch) The only difference is that this code is perfectly operated with pytorch 0.4.0.

I added some Modules such as Extension Module and Spatial Weight Module for accurate vehicle detection.

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You can get the TME Dataset from here (http://cmp.felk.cvut.cz/data/motorway/).

First download the fc-reduced VGG-16 PyTorch base network weights at: https://s3.amazonaws.com/amdegroot-models/vgg16_reducedfc.pth
By default, we assume you have downloaded the file in the ssd.pytorch/weights dir:

mkdir weights
cd weights
wget https://s3.amazonaws.com/amdegroot-models/vgg16_reducedfc.pth

To train SSD_TME using the train script simply specify the parameters listed in train_tme_sw_deconv.py as a flag or manually change them.

python train_tme_sw_deconv.py

Name		Name	Last commit message	Last commit date
Latest commit History 10 Commits
data		data
demo		demo
doc		doc
layers		layers
utils		utils
weights		weights
LICENSE		LICENSE
README.md		README.md
eval_tme.py		eval_tme.py
eval_tme_cut_bot.py		eval_tme_cut_bot.py
eval_tme_mix_cut_bot.py		eval_tme_mix_cut_bot.py
eval_tme_sw_deconv.py		eval_tme_sw_deconv.py
log.py		log.py
nms.py		nms.py
ssd.py		ssd.py
ssd_tme.py		ssd_tme.py
ssd_tme_sw_deconv.py		ssd_tme_sw_deconv.py
train.py		train.py
train_tme_sw_deconv.py		train_tme_sw_deconv.py