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tensorflow-tutorial - TensorFlow and Deep Learning Tutorials
Some examples require MNIST dataset for training and testing. Don't worry, this dataset will automatically be downloaded when running examples (with input_data.py). MNIST is a database of handwritten digits, for a quick description of that dataset, you can check this notebook.
recurrent-neural-networks convolutional-neural-networks deep-learning-tutorial tensorflow tensorlayer keras deep-reinforcement-learning tensorflow-tutorials deep-learning machine-learning notebook autoencoder multi-layer-perceptron reinforcement-learning tflearn neural-networks neural-network neural-machine-translation nlp cnnsrgan - Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
We run this script under TensorFlow 1.4 and the TensorLayer 1.8.0+. 🚀 This repo will be moved to here (please star) for life-cycle management soon. More cool Computer Vision applications such as pose estimation and style transfer can be found in this organization.
tensorlayer tensorflow super-resolution gan cnn srgan vgg16 vgg19 vggtensorlayer - Deep Learning and Reinforcement Learning Library for Developers and Scientists
TensorLayer is a novel TensorFlow-based deep learning and reinforcement learning library designed for researchers and engineers. It provides a large collection of customizable neural layers / functions that are key to build real-world AI applications. TensorLayer is awarded the 2017 Best Open Source Software by the ACM Multimedia Society. Simplicity : TensorLayer lifts the low-level dataflow interface of TensorFlow to high-level layers / models. It is very easy to learn through the rich example codes contributed by a wide community.
tensorlayer deep-learning tensorflow machine-learning data-science neural-network reinforcement-learning artificial-intelligence gan a3c tensorflow-tutorials dqn object-detection chatbot tensorflow-tutorial imagenet googleseq2seq-chatbot - Chatbot in 200 lines of code using TensorLayer
Chatbot in 200 lines of code using TensorLayer
tensorlayer tensorflow chatbot rnn lstm bot nlp chat corpustensorlayer-tricks - How to use TensorLayer
While research in Deep Learning continues to improve the world, we use a bunch of tricks to implement algorithms with TensorLayer day to day. Here are a summary of the tricks to use TensorLayer. If you find a trick that is particularly useful in practice, please open a Pull Request to add it to the document. If we find it to be reasonable and verified, we will merge it in.
tensorlayer tensorflow deep-learning machine-learning data-science neural-network reinforcement-learning neural-networks tensorflow-tutorials tensorflow-models computer-vision tensorflow-framework tensorflow-library tflearn keras tensorboard nlp natural-language-processing lasagne tensorflow-experimentsdeep-learning-book - 《Deep Learning》《深度学习》 by Ian Goodfellow, Yoshua Bengio and Aaron Courville
This book was downloaded in HTML form and conviniently joined as a single PDF file for your enjoyment. PLEASE SUPPORT IAN GOODFELLOW and the authors if you can purchase the paper book at Amazon. It is not expensive ($72) and probably contains content that is newer and without typographic mistakes.
deep-learning tensorlayer tensorflow gan machine-learningtext-to-image - Generative Adversarial Text to Image Synthesis / Please Star -->
This is an experimental tensorflow implementation of synthesizing images. The images are synthesized using the GAN-CLS Algorithm from the paper Generative Adversarial Text-to-Image Synthesis. This implementation is built on top of the excellent DCGAN in Tensorflow. N.B You can downloads all data files needed manually or simply run the downloads.py and put the correct files to the right directories.
tensorflow tensorlayer gan text-to-imageCycleGAN_Tensorlayer - Re-implement CycleGAN in Tensorlayer
Re-implement CycleGAN in Tensorlayer
cyclegan gan tensorlayer resize-convolutiontensorflow-wrapper-compare - Comparison of TensorFlow Wrappers
Run Keras, TensorLayer and Tflearn with same model and data on a same GPU machine. The parameter initialization may have slightly different, but would not effect the speed.
tflearn tensorflow-wrappers tensorlayer keras tensorflow neural-networks machine-learningawesome-tensorlayer - TensorLayer - A curated list of dedicated resources
You have just found TensorLayer! High performance DL and RL library for industry and academic. Contributions welcome! Read the contribution guidelines first.
tensorlayer tensorflow tensorflow-tutorials natural-language-processing reinforcement-learning adversarial-learning autoencoder database computer-vision keras tf-slim tflearn horovod lstm-neural-networks convolutional-neural-networks recurrent-neural-networks segmentation cifar-10 mnist generative-adversarial-networkchinese-book - 《深度学习：一起玩转TensorLayer》资源分享、讨论
《深度学习：一起玩转TensorLayer》资源分享、讨论
tensorflow tensorlayer deep-learningdcgan - Deep Convolutional Generative Adversarial Networks based on TensorFlow / TensorLayer
TensorFlow / TensorLayer implementation of Deep Convolutional Generative Adversarial Networks which is a stabilize Generative Adversarial Networks.
dcgan tensorflow tensorlayer gan generative-adversarial-networkopenpose-plus - High-Performance and Flexible Pose Estimation Framework using TensorFlow, OpenPose and TensorRT
train.py automatically download MSCOCO 2017 dataset into dataset/coco17. The default model is VGG19 used in the OpenPose paper. To customize the model, simply changing it in models.py.
tensorlayer tensorflow openpose pose-estimation tensorflow-tutorials mobilenet tensorrt vgg19 horovod jetson-tx1 jetson-tx2 computer-vision deep-learning deep-neural-networks distributed-training gpu affine-transformation vggpretrained-models
Feel free to add more. The tl.models API description here, and the discussion for network architecture that can be easily use here.
tensorlayer tensorflow vggim2txt2im - I2T2I: Text-to-Image Synthesis with textual data augmentation
This code run well under python2.7 and TensorFlow 0.11, if you use higher version of TensorFlow you may need to update the tensorlayer folder from TensorLayer Lib.
image-to-text text-to-image tensorflow tensorlayerImitation-Learning-Dagger-Torcs - A Simple Example for Imitation Learning with Dataset Aggregation (DAGGER) on Torcs Env
This repository implements a simple algorithm for imitation learning: DAGGER. In this example, the agent only learns to control the steer [-1, 1], the speed is computed automatically in gym_torcs.TorcsEnv. It will start a Torcs server at the beginning of every episode, and terminate the server when the car crashs or the speed is too low. Note that, the self-contained gym_torcs.py is modified from Gym-Torcs, you can try different settings (like default speed, terminated speed) by modifying it.
tensorlayer dagger gym-torcs imitation-learning torcs-env tensorflow tensorflow-tutorials torcsSpatial-Transformer-Nets - Spatial Transformer Nets in TensorFlow/ TensorLayer
Spatial Transformer Networks (STN) is a dynamic mechanism that produces transformations of input images (or feature maps)including scaling, cropping, rotations, as well as non-rigid deformations. This enables the network to not only select regions of an image that are most relevant (attention), but also to transform those regions to simplify recognition in the following layers. Video for different transformation click me.
tensorlayer tensorflow cnn deep-learning tensorflow-tutorials spatial-transformer-networkU-Net - U-Net: Convolutional Networks for Image Segmentation by TensorFlow
NEWS: click here for training.
image-segmentation tensorlayer tensorflowu-net-brain-tumor - U-Net Brain Tumor Segmentation in TensorFlow
🚀：Sep 2018 the data processing implementation in this repo is not the fastest, please use TensorFlow dataset API instead. This repo show you how to train a U-Net for brain tumor segmentation. By default, you need to download the training set of BRATS 2017 dataset, which have 210 HGG and 75 LGG volumes, and put the data folder along with all scripts.
tensorflow tensorlayer unet medical-imaging
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