Vision AI Model
Vision AI Model layout
Vision AI models which run on the Vision AI DevKit consists of three files:
- .DLC file - containing the model
- .TXT file - containing a list of the objects recognized by the model
- .json file - containing the VAM engine configuration
the model is stored in camera in /data/misc/camera folder
In addition .dlc file the camera can run an AI model in .tflite (Tensorflow lite) format.
Contents of the .json VAM engine configuration file
You can check the VAM configuration file for the default model using platform tools (ADB):
adb shell cat /data/misc/camera/va-snpe-engine-library-config.json
Here is a breakdown of key attributes and their values in VAM config:
“EngineOutput”:0, –> Engine output: Possible values: ‘0’ –> Single; ‘1’ –> Multi;
“InputFormat”:3, –> SNPE input format: Possible values: ‘0’ –> RGB ‘1’ –> BGR ‘2’ –> RGB Float ‘3’ –> BGR Float
Note: SNPE common engine currently supports only BGR Float
“NetworkIO”:0” –> Network IO: Possible values: ‘0’ –> UserBufer ‘1’ –> ITensor
“ScaleWidth”:, –> ScaleWidth “ScaleHeight”:, –> ScaleHeight “BlueMean”:, –> BlueMean “GreenMean”:, –> GreenMean “RedMean”:, –> RedMean Mean Range [0 - 255]
“UseNorm”:1, –> Normalization ‘0’ –> Do not use normalization ‘1’ –> Use normalization
“TargetFPS”:30, –> Target Frames Per Second
“ConfThreshold”:0.0, –> ConfThreshold, percentage of confidence needed for labeling an object Range [0.0 - 1.0]
“DLC_NAME”:”.dlc”, –> dlc file name “LABELS_NAME”:”.txt”, –> labels file name “InputLayers” –> Input layers “OutputLayers” –> Output layers - array of strings. It is possible to have single entry
“ResultLayers” –> Used for comparing the results. It is possible to have single entry. For ComplexEngine, use the following convention: ‘[ ]’
“Runtime”:0, –> Runtime: Possible values: ‘0’ –> CPU; ‘1’ –> DSP;