initial the models of yolov8 using ax650&ax620e

.gitattributes

@@ -33,3 +33,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+ax620e/yolov8s.axmodel filter=lfs diff=lfs merge=lfs -text
+ax650/yolov8s.axmodel filter=lfs diff=lfs merge=lfs -text

ax620e/yolov8s.axmodel

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+oid sha256:e75cbabc9fea453c7f3694826cdddd536653ecac643ec78f6b46daf207a5bec3
+size 11504561

ax650/yolov8s.axmodel

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+version https://git-lfs.github.com/spec/v1
+oid sha256:65da17e48e6d057fb18a1acf1e583c1534f9691944014357e35839479e3818a9
+size 11824773

cut-onnx.py

@@ -0,0 +1,10 @@
+import onnx
+
+input_path = "yolov8s.onnx"
+output_path = "yolov8s-cut.onnx"
+input_names = ["images"]
+output_names = ["/model.22/Concat_output_0", 
+                "/model.22/Concat_1_output_0", 
+                "/model.22/Concat_2_output_0",]
+
+onnx.utils.extract_model(input_path, output_path, input_names, output_names)

yolov8-test.py

@@ -0,0 +1,16 @@
+from ultralytics import YOLO
+
+# Load a model
+model = YOLO("yolov8s.pt")
+model.info()
+
+# Use the model
+results = model("./images/ssd_horse.jpg")
+
+# Save the results
+results[0].save("yolov8s-result.jpg")
+
+# Export to onnx with simplify
+model.export(format='onnx', simplify=True)
+
+

yolov8_config.json

@@ -0,0 +1,42 @@
+{
+  "model_type": "ONNX",
+  "npu_mode": "NPU1",
+  "quant": {
+    "input_configs": [
+      {
+        "tensor_name": "images",
+        "calibration_dataset": "./dataset/coco_1000.tar",
+        "calibration_size": 4,
+        "calibration_mean": [0, 0, 0],
+        "calibration_std": [255.0, 255.0, 255.0]
+      }
+    ],
+    "calibration_method": "MinMax",
+    "precision_analysis": true,
+    "precision_analysis_method":"EndToEnd"
+  },
+  "input_processors": [
+    {
+      "tensor_name": "images",
+      "tensor_format": "BGR",
+      "src_format": "BGR",
+      "src_dtype": "U8",
+      "src_layout": "NHWC"
+    }
+  ],
+  "output_processors": [
+    {
+      "tensor_name": "/model.22/Concat_output_0",
+      "dst_perm": [0, 2, 3, 1]
+    },    {
+      "tensor_name": "/model.22/Concat_1_output_0",
+      "dst_perm": [0, 2, 3, 1]
+    },    {
+      "tensor_name": "/model.22/Concat_2_output_0",
+      "dst_perm": [0, 2, 3, 1]
+    },
+  ],
+  "compiler": {
+    "check": 0
+  }
+}

yolov8s-cut.onnx

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+size 44681140

yolov8s.onnx

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+version https://git-lfs.github.com/spec/v1
+oid sha256:e4309ed01920fc09d6b71412988d074504d4ad6b0d27fb9a50d9f39541cd6e6f
+size 44855069

yolov8s.pt

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+version https://git-lfs.github.com/spec/v1
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