AIFuture

1 NNTest

1.0 Base Usage

python3 NNTest.py

1.1 Loss Results

Fig.1.1 Loss

1.2 Train Results

Fig.1.2 Train result

1.3 Load Model for Transfer Training

Fig.1.3 Accuracy

2 FaceRecognition

2.1 Base Usage

python3 findFaceInImages.py

2.2 Single Face

2.2.1 Source Image

Fig.2.1 Single face

2.2.2 Marked image with bounding box

Fig.2.2 Bounding box

2.3 Multi face

2.3.1 Source Image

Fig.2.3 Multi face

2.3.2 Marked image with bounding boxes

Fig.2.4 Bounding box

3 Get tickets info

3.1 Base Usage

python3 getData.py 深圳 上海 2018-12-25

3.2 Result

Fig.3.1 Search info

4 Get face images

4.1 Base Usage

python3 getImage.py

4.2 Get sixty images

Fig.5.1 Download images

4.3 Downloading status

Fig.5.2 Download status

5 Cluster Algorithm

5.1 Base Usage

python2 kmeans.py

5.2 Results

Fig.5.1 Cluster

6 NN tensorboard display

6.1 Base Usage

python3 NNtensorboard.py
tensorboard --logdir=~/logs

6.2 Reuslts

6.2.1 Global Graph Architecture

Fig.6.1 Global graph

6.2.2 Module Graph Architecture

Fig.6.2 Module graph

7 VGGNet

7.1 Base Usage

• run

python3 VGG_Cifar.py

• baseboard

tensorboard --logdir=/logdir

7.2 VGGNet Structure

Fig.7.1 VGGNet sturcture

7.3 Results

Fig.7.2 Source Data

Fig.7.3 Different convlution image feature

Fig.7.4 Cross entropy