Hornet Detector Tensorflow Model Trainer

Train a tensorflow model to detect hornets and bees in pictures

Dependencies

Some dependencies are listed in file toinstall.sourceme.sh.

source scripts/toinstall.sourceme.sh

Annotate new images

Automatic annotation from an existing model

The last iteration of the model can be used to annotate new image files, therefore the effort to annotate the images can be significantly reduced. After the automatic annotation you just need to browse the generated annotations and fix them if necessary.

For this, the script auto_annotate.py can be used:

./scripts/auto_annotate.py images/mynewpics/*.jpg

It will create a .xml next to each .jpg file. labelImg can then be used to see/fix the annotations.

Manually annotate

labelImg program is used to annotate image files, it can be compiled and launched simply with:

make label

Once labelImg is opened use "Open Dir" and "Change Save Dir" button to change the directory to you image directory.

Some useful shortcuts:

• d Next image
• a Previous image
• w Create a rect box

Note: the "Auto Save Mode" from "View" menu can be very useful

Run a training

Basically make train should do everything to create a new trained model. It might take several dozens of hours to run depending on the hardware.

make export-graph exports the trained model in graphs/ folder.

Folder description

• graphs Where generated graph are stored by make export-graph
• images All the image file for the model to train
  • test Image files for evaluation
  • train Image files for training
• training Where configuration files are stored, also used as working directory by make train
• scripts Some useful scripts
• videos Some videos to test the model