ESPCN-TensorFlow:TensorFlow中高效子像素卷积神经网络的实现

# ESPCN-TensorFlow TensorFlow implementation of the Efficient Sub-Pixel Convolutional Neural Network in TensorFlow (ESPCN). Network based on this [paper](https://arxiv.org/pdf/1609.05158.pdf) and code adapted from this [repo](https://github.com/JesseYang/Espcn). <br> This network can achieve the real-time performance of the [FSRCNN](https://arxiv.org/abs/1608.00367) while also surpassing the quality of the [SRCNN](https://arxiv.org/abs/1501.00092). ## Prerequisites * Python 2.7 * TensorFlow * Numpy * Scipy version > 0.18 ## Usage Run `prepare_data.py` to format the training and validation data before training each new model <br> For training: `python train.py` <br> Can specify epochs, learning rate, batch size etc: <br> `python train.py --epochs 10 --learning_rate 0.0001 --batch_size 32` <br> For generating: `python generate.py` <br> Must specify checkpoint, low-resolution image, and output path <br> `python generate.py --checkpoint logdir_2x/train --lr_image images/butterfly_GT.png --out_path result/butterfly_HR` Check `params.json` for parameter values and to change the upscaling ratio (2x, 3x, ...) the model is operating on. ## Result Original butterfly image: <br>  <br> Bicubic interpolated image: <br>  <br> Super-resolved image: <br>  ## References * [JesseYang/Espcn](https://github.com/JesseYang/Espcn)