How to do incremental learning on MobileNet-SSD caffe

I'm training my classifier on 20k images but every week I get more new pictures so I want to incrementally train my previous model(last stopped iteration) instead of retraining 20k+new_images on all the images again which is a waste of time and compute

I figured out incremental training with Yolo but can't seem to find anything for MobileNet-SSD caffe implemented here https://github.com/chuanqi305/MobileNet-SSD

To understand more about what I'm talking about refer to this: How to do incremental training on the basis of yolov3.weights & answer to this mention here:

 darknet.exe partial cfg/yolov3.cfg yolov3.weights yolov3.conv.105 105

Solution

You need to pass previous iteration in train.sh instead of 73000 iteration. The new iteration are found in snapshot folder once you are done training

if ! test -f example/MobileNetSSD_train.prototxt ;then
echo "error: example/MobileNetSSD_train.prototxt does not exist."
echo "please use the gen_model.sh to generate your own model."
exit 1
fi
mkdir -p snapshot

#Initiate a new training
$CAFFE_ROOT/build/tools/caffe train -solver="solver_train.prototxt" \
-weights="mobilenet_iter_73000.caffemodel" \
-gpu 0