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products:sbc:edge2:npu:demos:yolov7-tiny

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products:sbc:edge2:npu:demos:yolov7-tiny [2023/09/19 22:41]
louis 		products:sbc:edge2:npu:demos:yolov7-tiny [2025/04/09 23:10] (current)
louis
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 {{indexmenu_n>1}} {{indexmenu_n>1}}
 +
 +===== Introduction =====
 +
 +YOLOv7-Tiny 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:yolov7-tiny-result.jpg?800|}}
 +
 +**Inference speed test**: USB camera about **43ms** per frame. MIPI camera about **33ms** per frame.
  
 ===== Train Model ===== ===== Train Model =====
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 ==== Convert ==== ==== Convert ====
  
-After training model, run ''export.py'' to convert model from **pt** to **onnx**.+After training model, run ''export.py'' to convert model from **PT** to **ONNX**.
  
 Enter ''rknn-toolkit2/examples/onnx/yolov5'' and modify ''test.py'' as follows. Enter ''rknn-toolkit2/examples/onnx/yolov5'' and modify ''test.py'' as follows.
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 ``` ```
  
-Run ''test.py'' to generate rknn model.+Run ''test.py'' to generate RKNN model.
  
 ```shell ```shell
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 ==== Get source code ==== ==== Get source code ====
  
-Clone the source code form our [[gh>khadas/edge2-npu]].+Clone the source code from our [[gh>khadas/edge2-npu]].
  
 ```shell ```shell
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 $ bash build.sh $ bash build.sh
  
-# Run+# Run USB camera 
 +$ cd install/yolov7_tiny 
 +$ ./yolov7_tiny data/model/yolov7_tiny.rknn usb 60 
 + 
 +# Run MIPI camera
 $ cd install/yolov7_tiny $ cd install/yolov7_tiny
-$ ./yolov7_tiny data/model/yolov7_tiny.rknn 33+$ ./yolov7_tiny data/model/yolov7_tiny.rknn mipi 42
 ``` ```
  
 <WRAP info > <WRAP info >
-''33'' is camera device index.+''60'' and ''42'' are camera device index.
 </WRAP> </WRAP>
  
  
 <WRAP tip > <WRAP tip >
-If your **YOLOv7 tiny** model classes is not the same as **coco**, please change ''data/coco_80_labels_list.txt'' and the ''OBJ_CLASS_NUM'' in ''include/postprocess.h''.+If your **YOLOv7 tiny** model classes are not the same as **COCO**, please change ''data/coco_80_labels_list.txt'' and the ''OBJ_CLASS_NUM'' in ''include/postprocess.h''.
 </WRAP> </WRAP>
  
Last modified: 2023/09/19 22:41 by louis

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