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StarDet: Detecting objects in astronomical images with CNN

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StarDet

Objects detection in defective astronomical images using FPN-based CNN.

Models based on mask_rcnn_X_101_32x8d_FPN_3x by detectron2.

Description

StarDet has been trained on defective astronomical images, allowing it to be used on images with background irregularities, star blooms and other defects. Example of detection on real images:

Trained 2 models differing in anchor size, number of epochs and lr decay coeffitient. Models can be downloaded here: https://drive.google.com/drive/folders/1yaLpcUBMpBNxMih3BnnM3UbAxmd1b-08?usp=sharing.

An example of detection on real astronomical images with the listed models is presented in example_real_images.ipynb. In model_training.ipynb you can see the training approach or train your own model with an example.

The model parameters and the CLAHE coefficients need to be adjusted for the images of the observatory of interest.

Models

model_24e_anc4-64 params:

  • Anchor_generator.sizes = [4, 8, 16, 32, 64]
  • Num_epoch = 24

Evaluate and Losses of the model:

model_22e_anc8-128 params:

  • Anchor_generator.sizes = [8, 16, 32, 64, 128]
  • Num_epoch = 22

Evaluate and Losses of the model: