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Real-time face detection and recognition using deep learning

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real-time-face-recognition

pipeline

Running FaceRecognitionPipeline.ipynb

$ jupyter notebook

Pre-trained Tensroflow Facenet Model

Github: TensorFlow implementation of the face recognizer described in the paper "FaceNet: A Unified Embedding for Face Recognition and Clustering".

Facenet Model Visualization

$ tensorboard --logdir='logs/'

Porting to iOS

https://github.com/tensorflow/tensorflow/tree/master/tensorflow/contrib/makefile https://github.com/tensorflow/tensorflow/tree/master/tensorflow/examples/ios 大家无法直接将该计算图加载至iOS应用当中。完整的计算图中包含的操作目前还不受TensorFlow C++ API的支持。正因为如此,我们才需要使用刚刚构建完成的其它两款工具。其中freeze_graph负责获取graph.pb以及包含有W与b训练结果值的checkpoint文件。其还会移除一切在iOS之上不受支持的操作。

在终端当中立足tensorflow目录运行该工具:

$ bazel-bin/tensorflow/python/tools/freeze_graph \ 
--input_graph=/tmp/voice/graph.pb --input_checkpoint=/tmp/voice/model \
--output_node_names=model/y_pred,inference/inference --input_binary \
--output_graph=/tmp/voice/frozen.pb 

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