e7d5e460cd9ca70ed8e455ff7d4c00d93a1034fa,tf_unet/unet.py,Trainer,store_prediction,#Trainer#,256

Before Change

        img = util.combine_img_prediction(batch_x, batch_y, prediction)
        util.save_image(img, "%s/%s.jpg"%(self.prediction_path, name))
        
        return prediction.shape
    
    def output_epoch_stats(self, epoch, total_loss, training_iters, lr):
        print("Epoch {:}, Average loss: {:.4f}, learning rate: {:.4f}".format(epoch, (total_loss / training_iters), lr))
    

After Change

        prediction = sess.run(self.net.predicter, feed_dict={self.net.x: batch_x, 
                                                             self.net.y: batch_y, 
                                                             self.net.keep_prob: 1.})
        pred_shape = prediction.shape
        
        loss = sess.run(self.net.cost, feed_dict={self.net.x: batch_x, 
                                                       self.net.y: util.crop_to_shape(batch_y, pred_shape), 
                                                       self.net.keep_prob: 1.})
        
        print("Prediction error= {:.1f}%, loss= {:.4f}".format(error_rate(prediction,
                                                                          util.crop_to_shape(batch_y,
                                                                                             prediction.shape)),

Instances