This page provides links to image-based examples using TensorFlow.
(Stay tuned, as I keep updating the post while I grow and plow in my deep learning garden:). Also, if you find a dead link, please email me –you can find my email address from the About page, which has a link to my academic website.)
- Fully Convolutional Networks (FCNs) for Image Segmentation (Jan 23, 2017)
Image Segmentation framework based on Tensorflow and TF-Slim library (GitHub repo) – up-to-date
- Image Segmentation with Tensorflow using CNNs and Conditional Random Fields (Dec 18, 2016)
- Upsampling and Image Segmentation with Tensorflow and TF-Slim (Nov 22, 2016)
- Image Classification and Segmentation with Tensorflow and TF-Slim (Oct 30, 2016)
- Tfrecords Guide (Dec 21, 2016) – this post is pretty good, it has example about extract object boundary from images.
- subpixel: A subpixel convolutional neural network implementation with Tensorflow
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Image Completion with Deep Learning in TensorFlow (August 9, 2016)
- How to Classify Images with TensorFlow (google research blog, tutorial)
- TensorFlow tutorials of image-based examples on GitHub – where cifar10 contains how to train and evaluate the model.
CIFAR-10 is a common benchmark in machine learning for image recognition.
http://www.cs.toronto.edu/~kriz/cifar.html
Code in this directory demonstrates how to use TensorFlow to train and evaluate a convolutional neural network (CNN) on both CPU and GPU. We also demonstrate how to train a CNN over multiple GPUs.
Detailed instructions on how to get started available at:
http://tensorflow.org/tutorials/deep_cnn/
- SketchToFace (Its GitHub repo)
