这是Keras版的Gcn代码，有助于理解图卷积网络，配合原版的论文看起来会比较不错。

使用fasterrcnn实现口罩检测，fasterrcnn基于keras搭建，训练需要口罩数据集，数据集必须是VOC格式，预测需要权重文件，权重文件已经存在

Learn how to model and train advanced neural networks to implement a variety of Computer Vision tasks Key FeaturesTrain different kinds of deep learning model from scratch to solve specific problems in Computer VisionCombine the power of Python, Keras, and TensorFlow to build deep learning models for object detection, image classification, similarity learning, image captioning, and moreIncludes tips on optimizing and improving the performance of your models under various constraintsBook Description Deep learning has shown its power in several application areas of Artificial Intelligence, especially in Computer Vision. Computer Vision is the science of understanding and manipulating images, and finds enormous applications in the areas of robotics, automation, and so on. This book will also show you, with practical examples, how to develop Computer Vision applications by leveraging the power of deep learning. In this book, you will learn different techniques related to object classification, object detection, image segmentation, captioning, image generation, face analysis, and more. You will also explore their applications using popular Python libraries such as TensorFlow and Keras. This book will help you master state-of-the-art, deep learning algorithms and their implementation. What you will learnSet up an environment for deep learning with Python, TensorFlow, and KerasDefine and train a model for image and video classificationUse features from a pre-trained Convolutional Neural Network model for image retrievalUnderstand and implement object detection using the real-world Pedestrian Detection scenarioLearn about various problems in image captioning and how to overcome them by training images and text togetherImplement similarity matching and train a model for face recognitionUnderstand the concept of generative models and use them for image generationDeploy your deep learning models and optimize them for high performanceWho This Book Is For This book is targeted

keras 各种fine tune，深度学习专用，机器学习专用，代码简单，vgg resnet inception..

为了方便各位做车牌识别项目，提供数据集便于使用

https://github.com/fchollet/deep-learning-models/releases/tag/v0.1 这网址下的keras的所有的预训练模型，包含vgg16,vgg19,resnt50,官方下载实在是太慢了。我这里提供了百度云链接，注册一天的百度云会员下载会很快的。

从Gitbub下载的，外网下载速度10k+，好不容易下的，需要的请拿走。在Keras上预训练的VGG16模型，基于ImageNet

Keras实现实时语义分割的深层神经网络架构ENET

完全基于Keras官方在线中文文档页面制作（截至日期是2019年7月16日），有目录，可复制，可高清打印。

boston_housing.npz，imdb.npz，imdb_word_index.json，mnist.npz，reuters.npz，reuters_word_index.json共6个数据集