alievk / nexar2

Nexar Challenge 2

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Nexar Challenge 2

First of all:

  • assuming Nexar dataset is in $HOME/datasets/nexar and train images are in the 'train' subfolder, test images are in the 'test' subfolder
  • git clone
  • cd nexar2
  • nexar$ git clone -b nexar caffe-ssd-nexar
  • nexar$ cd caffe-ssd-nexar
  • follow the instructions in the README to build Caffe

To train the model:

  • download the pretrained imagenet model and put it in caffe-ssd-nexar/models/VGGNet
  • caffe-ssd-nexar$ python data/nexar2/ --single-class --train 40000 --val 10000 --gen-annos
  • caffe-ssd-nexar$ data/nexar2/
  • caffe-ssd-nexar& python examples/ssd/
  • when training is complete, find the model in models/VGGNet/nexar2/SSD_600x600

Or download the models from:


  • cd ..
  • nexar$ mkdir out
  • nexar$ python --gpu 0 --model1 /path/to/VGG_nexar2_SSD_600x600_iter_60000.caffemodel --def1 /path/to/deploy.prototxt --model2 /path/to/VGG_nexar2_SSD_600x600_iter_70000.caffemodel --def2 /path/to/deploy.prototxt
  • evaluation csv will be written to ./out


  • --def1 and --def2 must be the same deploy.prototxt files
  • you can run in parallel on multiple GPUs using --gpu option and --from A and --to B options, where A and B is the start and the end image number. this will produce file in ./out called test_A-B_.csv. then you have to concatenate these files into one (don't forget to remove the headers from the csv files when concatenating).
  • if two models does not fit into the memory, you can either specify a single model through --model1 and --def1 or disable some augmentations here.


Nexar Challenge 2


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