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Resnet9

Dependencies

  • pytorch = 1.8
  • cuda 10.2
  • torchvision
  • matplotlib

Training:

Uncompress the folder in any location and run the following command

python test_geo.py --train PATH_TO_TRAINIG_DATA

The training data folder must have 2 folders called set_test and set_train

Testing

For testing you can run the following command

python test_geo.py --test PATH_TO_TEST_IMAGE --k 10

where k is the number of top k images similar to the testing one

References

https://github.com/matthias-wright/cifar10-resnet https://github.com/lambdal/cifar10-fast https://medium.com/swlh/natural-image-classification-using-resnet9-model-6f9dc924cd6d https://github.com/digantamisra98/Mish

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