Name¶
dnn_rf_us - Visualize receptive field using up-sampling(us) method for interested channels
Synopsis¶
dnn_rf_us -net Net -layer Layer -chn Channel -stim Stimulus -ip_metric InterpolateMetric -up_thres Threshold -out Output
Arguments¶
Required Arguments¶
Argument |
Discription |
|---|---|
net |
Name of a neural network |
stim |
Path of a .stim.csv file which contains stimulus information |
layer |
Name of the target layer.Only support one layer each time.E.g., ‘conv1’ represents the first convolution layer, and ‘fc1’ represents the first full connection layer. |
chn |
Index of target channel.Only support one channel each time.Channel index starts from 1. |
ip_metric |
Interpolate method for magnifying the feature map.Only support nearest/linear/bilinear/bicubic/trilin ear/bicubic. |
up_thres |
Threshold for activation.The threshold(float) is in the range of 0-1. |
out |
Output path to save the upsampling image |
Outputs¶
A series of upsampling images based on your stimilus and interested net information
Examples¶
dnn_rf_us -net AlexNet -layer conv5 -chn 122 -stim ./flowers.stim.csv -ip_metric bicubic -up_thres 0.95 -out ./image/rf_us/
The original image used in this doc is displayed as below:
The receptive field upsampling is displayed as below:
