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Processing satellite images

Installation

  • npm install for the labeling tool
  • Needed dependencies for the neural network: Tensorflow (please see the install instructions on their page), Numpy (install with pip), OpenCV2 (install with brew/pip)

Start

  • Clone the repository, cd satellite-images
  • Put the images to be labeled into "app/images_input"
  • In main directory: node server.js starts the labeling tool
  • In your browser go to http://localhost:8080/
  • Mark the points / label things
  • Then in main directory: python crop_images.py path/to/your/img.png will crop images into "images_cropped"
  • Now python convolutional_sat.py train will train the neural network and save it under "conv_mnist_model.ckpt", can take some time
  • python convolutional_sat.py path/to/your/img.png uses the saved network to run on an image and label it, produces an "output.jpeg"

I tried:

  • Didn't work with 40x40 pixel images (feeded to the network)
  • 60x60 pixels, more augmentation with rotations: not bad, but it recognices too much (where there is nothing)

Todo

  • Switch to hdfs. Does tensorflow support it?

Need to read some papers about this subject.