TensorFlow2.0_ResNet

A ResNet(ResNet18, ResNet34, ResNet50, ResNet101, ResNet152) implementation using TensorFlow-2.0

See https://github.com/calmisential/BasicCNNsTensorFlow2.0 for more CNNs.

Train

1. Requirements:
2. Python >= 3.6
3. Tensorflow == 2.0.0
4. To train the ResNet on your own dataset, you can put the dataset under the folder original dataset, and the directory should look like this:

   |——original dataset
   |——class_name_0
   |——class_name_1
   |——class_name_2
   |——class_name_3
   

5. Run the script split_dataset.py to split the raw dataset into train set, valid set and test set.
6. Change the corresponding parameters in config.py.
7. Run train.py to start training. ## Evaluate Run evaluate.py to evaluate the model's performance on the test dataset.

The networks I have implemented with tensorflow2.0:

• ResNet18, ResNet34, ResNet50, ResNet101, ResNet152
• InceptionV3

References

1. The original paper: https://arxiv.org/abs/1512.03385
2. The TensorFlow official tutorials: https://tensorflow.google.cn/beta/tutorials/quickstart/advanced