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The yuv_dnn_app sample application has the following files, so you can check the operation without using the AI model conversion tool. [For ambaCV2X app] |
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Next, place the model-converted mobilenet_cavalry.bin file in the sample app directory with the following configuration.
[For ambaCV2X app]
${SDK_DIR}/src/adamapp/yuv_dnn_app/data_CV2X/cnn/mobilenet_cavalry.bin
[For ambaCV5X app]
${SDK_DIR}/src/adamapp/yuv_dnn_app/data_CV5X/cnn/mobilenet_cavalry.bin
make.
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$ cd src/adamapp/yuv_dnn_app $ make |
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Next, place the model-converted mobilenet_cavalry.bin file in the sample app directory with the following configuration.
[For ambaCV2X app]
${SDK_DIR}/src/adamapp-py/yuv_dnn_app/data_CV2X/cnn/mobilenet_cavalry.bin
[For ambaCV5X app]
${SDK_DIR}/src/adamapp/yuv_dnn_app/data_CV5X/cnn/mobilenet_cavalry.bin
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How to change AI model
Please replace
data_CV2X/cnn/mobilenetv1_ssd_cavalry.bin
data_CV5X/cnn/mobilenetv1_ssd_cavalry.bin
and
data_CV2X/cnn/mobilenet_priorbox_fp32.bin
data_CV5X/cnn/mobilenet_priorbox_fp32.bin
with your model.Please change the following part of main.cpp according to your model.
#define OUTSIZE_HEIGHT<Input height of your model>
#define OUTSIZE_WIDTH<Input width of your model>
#define NETNAME<File name of your model>
#define PRIORBOXFILE<File name of prior box>
#define LAYERNAMEIN<Input layer name of your model>
#define LAYERNAMEOUT_MBOX_LOC<Output layer name of your model to indicate boundary box location>
#define LAYERNAMEOUT_MBOX_CONF_FLATTEN<Output layer name of your model to indicate boundary box confidence>
#define PROPERTY_NUMCLASSES<Number of classes including background label>
#define PROPERTY_MBOXLOCSIZE<Number of boundary boxes * 4> : 4 means (x,y,w,h)
#define PROPERTY_BACKGROUND_LABEL_ID<Background label id>
Following parameters are valid only for tensorflow SSD. For caffe SSD, please set these values to 0.
#define X_SCALE<X scale value>
#define Y_SCALE<Y scale value>
#define WIDTH_SCALE<Width scale value>
#define HEIGHT_SCALE<Height scale value>Please describe "objectname" (label-objectname matrix) according to your model.
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