Khadas Docs

Amazing Khadas, always amazes you!

User Tools

Site Tools


products:sbc:edge2:npu:demos:yolov8n

Differences

This shows you the differences between two versions of the page.

Link to this comparison view

Both sides previous revision Previous revision
products:sbc:edge2:npu:demos:yolov8n [2024/07/03 21:44]
louis
products:sbc:edge2:npu:demos:yolov8n [2025/04/09 23:20] (current)
louis
Line 5: Line 5:
 {{indexmenu_n>2}} {{indexmenu_n>2}}
  
-===== Get Source Code =====+===== Introduction ===== 
 + 
 +YOLOv8n is an object detection model. It uses bounding boxes to precisely draw each object in image. 
 + 
 +Inference results on Edge2. 
 + 
 +{{:products:sbc:edge2:npu:demos:yolov8n-result.jpg?800|}} 
 + 
 +**Inference speed test**: USB camera about **52ms** per frame. MIPI camera about **40ms** per frame. 
 + 
 +===== Train Model =====
  
 Download YOLOv8 official code [[gh>ultralytics/ultralytics]] Download YOLOv8 official code [[gh>ultralytics/ultralytics]]
Line 191: Line 201:
 $ bash build.sh $ bash build.sh
  
-# Run+# Run USB camera 
 +$ cd install/yolov8n_cap 
 +$ ./yolov8n_cap data/model/yolov8n_cap.rknn usb 60 
 + 
 +# Run MIPI camera
 $ cd install/yolov8n_cap $ cd install/yolov8n_cap
-$ ./yolov8n_cap data/model/yolov8n_cap.rknn 33+$ ./yolov8n_cap data/model/yolov8n_cap.rknn mipi 42
 ``` ```
  
 <WRAP info > <WRAP info >
-''33'' is camera device index.+''60'' and ''42'' are camera device index.
 </WRAP> </WRAP>
  
Last modified: 2025/04/09 23:20 by louis