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NPU Kernel Driver | v6.4.15.9 | v6.4.18.5 |
Acuity Toolkit | 6.21.1 | 6.30.7 |
ViviantelIDE | 5.8.2 | 5.10.1 |
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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| Code Block |
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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, 301349)] |
3.2. ImageWriter Tool
If you want to show the detection results in an image, we suggest using ImageWriter tools.
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| Code Block |
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./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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