FCN (Fully Convolutional Network) is deep fully convolutional neural network architecture for semantic pixel-wise segmentation

Last update: Aug 30, 2022

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Overview

FCN_via_Keras

FCN

FCN (Fully Convolutional Network) is deep fully convolutional neural network architecture for semantic pixel-wise segmentation. This is implementation of "https://arxiv.org/abs/1605.06211" by using Keras which is a neural networks library. FCN can train by using any size of image, but I trained this network using the images of the same size (224 * 224).

Usage

train

$ python train.py -tr 
   
     -ta 
    
      -tt 
      -e 
     
       -b

Example

$ python train.py -tr /Volumes/DATASET2/VOCdevkit/VOC2012/JPEGImages/ -ta /Volumes/DATASET2/VOCdevkit/VOC2012/SegmentationClass/ -t train.txt

predict

$ pyton predict.py -i

Example

$ python train.py -i demo_imgs/2011_003255.jpg

Caution

Please use theano as backend because this couldn't work on tensorflow backend. I'm trying debug now. I update this code if I get factor of that.

Owner

Kento Watanabe

GitHub Repository

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FCN (Fully Convolutional Network) is deep fully convolutional neural network architecture for semantic pixel-wise segmentation

Related tags

Overview

FCN_via_Keras

FCN

Usage

train

Example

predict

Example

Caution

Owner

Kento Watanabe

Code for STFT Transformer used in BirdCLEF 2021 competition.

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