Page Comparison

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1. Model Conversation

Before the conversion, it is necessary to first set up the environment for model conversion. Please refer to the following document to prepare the environment：NN Model Conversion

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We can get the nb file and a c file for NN graph setup information.

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1.3. Demo Video

This video is the demo for yolov8s-detection int16 quantize.

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2. Object Detection Program

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For detailed function implementation, please refer to the following file:

2.2. Program Compile

When compiling NN-related applications, SDK's headers and libraries must be included.

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3. Example flow of the program build and run

Unzipped

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/mnt/yolov8s_uint8_nbg_unify # ./yolov8s-detection-uint8 ./network_binary.nb
./input.jpg
Create Neural Network: 28ms31ms or 28375us31666us
Verify...
Verify Graph: 21ms18ms or 21116us18520us
Start run graph [1] times...
Run the 1 time: 5752.55ms67ms or 5754852667.24us43us
vxProcessGraph execution time:
Total   5852.05ms79ms or 5805352792.36us95us
Average 5852.05ms79ms or 58053.36us52792.95us
obj: L: 0 P:0.92, [(294, 264) - (209, 369)]
obj: L: 0 P:0.9392, [(0, 4244) - (200199, 599589)]
obj: L: 0 P:0.50, [(349, 169) - (179, 299)]
obj: L: 2 P:0.9133, [(309534, 279294) - (18074, 36164)]
obj: L: 0 P:0.5826, [(344539, 171264) - (17099, 301)]349)]

3.2. ImageWriter Tool

If you want to show the detection results in an image, we suggest using ImageWriter tools.

Please download

cd imageWriter
make -j

Then you can run the imageWriter application directly on c3v:

Param1 is the image which is the same as yolov8s-detection-uint8 param2. The yolov8s-detection-uint8 is the application that is built in step 3.1. build in c3v.

Param2 is the file detect_results.raw which was generated after the program yolov8s-detection-uint8 runs.

Param3 is the output name, which format is jpg.

./imageWriter ./input.jpg ./detect_results.raw ./output.jpg

The result is like this:

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3.3. Demo Video

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