Aid Learning FrameWork is a Linux system running on Android phone for AI programming. It means that when it is installed, your Android phone owned a Linux system which can run AI program in it. Now we support Caffe, Tensorflow, Mxnet, ncnn, Keras, cv2, Git/SSH powerfully.

Furthermore we provide an AI coding develop tool named Aid_code. It can provide you a visual AI programming experience by using Python from zero on our framework!

Now you have a complete linux with a GUI running on Android (Real linux running on the busybox and not virtul environment. So it is faster and almost real-time.) and can tap your AI code on it visually!

Fast:already converted to ncnn,so it is fast and multi-threads. 15 fps running on the mobile with NO tracking!

Input data 0 1 data Convolution conv1 1 1 data conv1 0=32 1=3 11=3 5=1 6=864 BatchNorm bn1 1 1 conv1 bn1 0=32 PReLU prelu1 1 1 bn1 prelu1 0=32 ConvolutionDepthWise conv2_dw 1 1 prelu1 conv2_dw 0=32 1=2 11=2 5=1 6=128 7=32 BatchNorm bn2_dw 1 1 conv2_dw bn2_dw 0=32 PReLU prelu2_dw 1 1 bn2_dw prelu2_dw 0=32 Convolution conv2_sep 1 1 prelu2_dw conv2_sep 0=32 1=1 11=1 5=1 6=1024 BatchNorm bn2_sep 1 1 conv2_sep bn2_sep 0=32 PReLU prelu2_sep 1 1 bn2_sep prelu2_sep 0=32 ConvolutionDepthWise conv3_dw 1 1 prelu2_sep conv3_dw 0=32 1=3 11=3 3=2 13=2 5=1 6=288 7=32 BatchNorm bn3_dw 1 1 conv3_dw bn3_dw 0=32 PReLU prelu3_dw 1 1 bn3_dw prelu3_dw 0=32 Convolution conv3_sep 1 1 prelu3_dw conv3_sep 0=64 1=1 11=1 5=1 6=2048 BatchNorm bn3_sep 1 1 conv3_sep bn3_sep 0=64 PReLU prelu3_sep 1 1 bn3_sep prelu3_sep 0=64 ConvolutionDepthWise conv4_dw 1 1 prelu3_sep conv4_dw 0=64 1=2 11=2 5=1 6=256 7=64 BatchNorm bn4_dw 1 1 conv4_dw bn4_dw 0=64 PReLU prelu4_dw 1 1 bn4_dw prelu4_dw 0=64 Convolution conv4_sep 1 1 prelu4_dw conv4_sep 0=64 1=1 11=1 5=1 6=4096 BatchNorm bn4_sep 1 1 conv4_sep bn4_sep 0=64 PReLU prelu4_sep 1 1 bn4_sep prelu4_sep 0=64 ConvolutionDepthWise conv5_dw 1 1 prelu4_sep conv5_dw 0=64 1=3 11=3 3=2 13=2 5=1 6=576 7=64 BatchNorm bn5_dw 1 1 conv5_dw bn5_dw 0=64 PReLU prelu5_dw 1 1 bn5_dw prelu5_dw 0=64 Convolution conv5_sep 1 1 prelu5_dw conv5_sep 0=64 1=1 11=1 5=1 6=4096 BatchNorm bn5_sep 1 1 conv5_sep bn5_sep 0=64 PReLU prelu5_sep 1 1 bn5_sep prelu5_sep 0=64 ConvolutionDepthWise conv6_dw 1 1 prelu5_sep conv6_dw 0=64 1=2 11=2 5=1 6=256 7=64 BatchNorm bn6_dw 1 1 conv6_dw bn6_dw 0=64 PReLU prelu6_dw 1 1 bn6_dw prelu6_dw 0=64 Convolution conv6_sep 1 1 prelu6_dw conv6_sep 0=64 1=1 11=1 5=1 6=4096 BatchNorm bn6_sep 1 1 conv6_sep bn6_sep 0=64 PReLU prelu6_sep 1 1 bn6_sep prelu6_sep 0=64 ConvolutionDepthWise conv7_dw 1 1 prelu6_sep conv7_dw 0=64 1=3 11=3 3=2 13=2 5=1 6=576 7=64 BatchNorm bn7_dw 1 1 conv7_dw bn7_dw 0=64 PReLU prelu7_dw 1 1 bn7_dw prelu7_dw 0=64 Convolution conv7_sep 1 1 prelu7_dw conv7_sep 0=128 1=1 11=1 5=1 6=8192 BatchNorm bn7_sep 1 1 conv7_sep bn7_sep 0=128 PReLU prelu7_sep 1 1 bn7_sep prelu7_sep 0=128 ConvolutionDepthWise conv8_dw 1 1 prelu7_sep conv8_dw 0=128 1=2 11=2 5=1 6=512 7=128 BatchNorm bn8_dw 1 1 conv8_dw bn8_dw 0=128 PReLU prelu8_dw 1 1 bn8_dw prelu8_dw 0=128 Convolution conv8_sep 1 1 prelu8_dw conv8_sep 0=128 1=1 11=1 5=1 6=16384 BatchNorm bn8_sep 1 1 conv8_sep bn8_sep 0=128 PReLU prelu8_sep 1 1 bn8_sep prelu8_sep 0=128 ConvolutionDepthWise conv9_dw 1 1 prelu8_sep conv9_dw 0=128 1=3 11=3 3=2 13=2 5=1 6=1152 7=128 BatchNorm bn9_dw 1 1 conv9_dw bn9_dw 0=128 PReLU prelu9_dw 1 1 bn9_dw prelu9_dw 0=128 Convolution conv9_sep 1 1 prelu9_dw conv9_sep 0=256 1=1 11=1 5=1 6=32768 BatchNorm bn9_sep 1 1 conv9_sep bn9_sep 0=256 PReLU prelu9_sep 1 1 bn9_sep prelu9_sep 0=256 ConvolutionDepthWise conv10_dw 1 1 prelu9_sep conv10_dw 0=256 1=2 11=2 5=1 6=1024 7=256 BatchNorm bn10_dw 1 1 conv10_dw bn10_dw 0=256 PReLU prelu10_dw 1 1 bn10_dw prelu10_dw 0=256 Convolution conv10_sep 1 1 prelu10_dw conv10_sep 0=256 1=1 11=1 5=1 6=65536 BatchNorm bn10_sep 1 1 conv10_sep bn10_sep 0=256 PReLU prelu10_sep 1 1 bn10_sep prelu10_sep 0=256 ConvolutionDepthWise conv11_dw 1 1 prelu10_sep conv11_dw 0=256 1=3 11=3 5=1 6=2304 7=256 BatchNorm bn11_dw 1 1 conv11_dw bn11_dw 0=256 PReLU prelu11_dw 1 1 bn11_dw prelu11_dw 0=256 Convolution conv11_sep 1 1 prelu11_dw conv11_sep 0=256 1=1 11=1 5=1 6=65536 BatchNorm bn11_sep 1 1 conv11_sep bn11_sep 0=256 PReLU prelu11_sep 1 1 bn11_sep prelu11_sep 0=256 InnerProduct conv6_3 1 1 prelu11_sep conv6_3 0=212 1=1 2=54272 BatchNorm bn6_3 1 1 conv6_3 bn6_3 0=212

the example of landmark is inside the AidLearning Framework. !Download now