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FRCNN-for-Aircraft-Detection

FRCNN for remote sensing image aircraft detection

this is a very userful implementation of faster-rcnn based on tensorflow and keras, the model is very clear and just saved in .h5 file, out of box to use, and easy to train on other data set with full support.

Requirements

Basically, this code supports both python2.7 and python3.5, the following package should installed:

tensorflow
keras
scipy
cv2

Out of box model to predict

I have trained a model to predict xingtubei. I will update a dropbox link here later. Let's see the result of predict:

Image text

Train New Dataset

to train a new dataset is also very simple and straight forward. Simply convert your detection label file whatever format into this format:

/path/training/image_2/000000.png,712.40,143.00,810.73,307.92,Pedestrian
/path/training/image_2/000001.png,599.41,156.40,629.75,189.25,Truck

Which is /path/to/img.png,x1,y1,x2,y2,class_name, with this simple file, we don't need class map file, our training program will statistic this automatically.

For Predict

If you want see how good your trained model is, simply run:

python test_frcnn_xingtubei.py

you can also using -p to specific single image to predict, or send a path contains many images, our program will automatically recognise that.

That's all, hope you enjoy!