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--- products:sbc:vim3:npu:ksnn:demos:yolov8n [2023/12/22 03:41]
louis created
+++ products:sbc:vim3:npu:ksnn:demos:yolov8n [2024/02/17 22:37]
louis
@@ Line 1: / Line 1: @@
 ~~tag> NPU YOLO KSNN VIM3 ~~
-====== YOLOv8n KSNN Demo - 1 ======
+====== YOLOv8n KSNN Demo - 2 ======
 {{indexmenu_n>2}}
@@ Line 34: / Line 34: @@
 After training the model, modify ''ultralytics/ultralytics/nn/modules/head.py'' as follows.
-```diff
+```diff head.py
 diff --git a/ultralytics/nn/modules/head.py b/ultralytics/nn/modules/head.py
 index 0b02eb3..0a6e43a 100644
@@ Line 62: / Line 62: @@
 +
 ```
+<WRAP important>
+If you pip-installed ultralytics package, you should modify in package.
+</WRAP>
 Create a python file written as follows to export ONNX model.
@@ Line 74: / Line 78: @@
 $ python export.py
 ```
+<WRAP important>
+Use [[https://netron.app/ | Netron]] to check your model output like this. If not, please check your ''head.py''.
+{{:products:sbc:vim3:npu:ksnn:yolov8n-vim3-ksnn-output.png?600|}}
+</WRAP>
 Enter ''aml_npu_sdk/acuity-toolkit/python'' and run command as follows.
@@ Line 112: / Line 122: @@
 Put ''yolov8n.nb'' and ''libnn_yolov8n.so'' into ''ksnn/examples/yolov8n/models/VIM3'' and ''ksnn/examples/yolov8n/libs''
+If your model's classes is not 80, please remember to modify the parameter, ''LISTSIZE''.
+```shell
+LISTSIZE = classes number + 64
+```
 ==== Picture input demo ====

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