build: 更新 ONNX 构建指南并添加训练配置文件

- 更新 README.md 中的 ONNX构建指南，增加新版本的安装步骤
- 在 runs/detect/final_model 和 runs/detect/train 目录下添加训练配置文件 args.yaml
- 配置文件包含模型训练的各种参数设置，为后续训练提供详细配置

README.md

@@ -9,4 +9,19 @@ git submodule update --init --recursive
 # prefer lite proto
 set CMAKE_ARGS=-DONNX_USE_LITE_PROTO=ON
 pip install -e .
+```
+
+```bash 
+git clone -b rel-1.17.0 https://github.com/onnx/onnx.git
+cd onnx
+git submodule update --init --recursive
+# prefer lite proto
+set CMAKE_ARGS="-DONNX_USE_PROTOBUF_SHARED_LIBS=ON"
+set CMAKE_ARGS=-DONNX_USE_LITE_PROTO=ON
+pip install -e .
+```
+
+```bash
+set CMAKE_ARGS="-DONNX_USE_PROTOBUF_SHARED_LIBS=ON"
+pip install onnx<1.18.0   
 ```

runs/detect/final_model/args.yaml

@@ -0,0 +1,110 @@
+task: detect
+mode: train
+model: yolo12s.yaml
+data: data.yaml
+epochs: 150
+time: null
+patience: 20
+batch: 16
+imgsz: 640
+save: true
+save_period: 5
+cache: false
+device: '0'
+workers: 4
+project: null
+name: final_model
+exist_ok: false
+pretrained: true
+optimizer: AdamW
+verbose: true
+seed: 0
+deterministic: false
+single_cls: false
+rect: false
+cos_lr: false
+close_mosaic: 10
+resume: null
+amp: true
+fraction: 1.0
+profile: false
+freeze:
+- 0
+- 1
+- 2
+- 3
+- 4
+multi_scale: false
+overlap_mask: false
+mask_ratio: 4
+dropout: 0.0
+val: true
+split: val
+save_json: false
+conf: null
+iou: 0.7
+max_det: 300
+half: false
+dnn: false
+plots: true
+source: null
+vid_stride: 1
+stream_buffer: false
+visualize: false
+augment: false
+agnostic_nms: false
+classes: null
+retina_masks: false
+embed: null
+show: false
+save_frames: false
+save_txt: false
+save_conf: false
+save_crop: false
+show_labels: true
+show_conf: true
+show_boxes: true
+line_width: null
+format: torchscript
+keras: false
+optimize: false
+int8: false
+dynamic: false
+simplify: true
+opset: null
+workspace: null
+nms: false
+lr0: 0.0001
+lrf: 0.01
+momentum: 0.937
+weight_decay: 0.001
+warmup_epochs: 10
+warmup_momentum: 0.8
+warmup_bias_lr: 0.1
+box: 5.0
+cls: 1.0
+dfl: 1.5
+pose: 12.0
+kobj: 1.0
+nbs: 64
+hsv_h: 0.01
+hsv_s: 0.7
+hsv_v: 0.4
+degrees: 10.0
+translate: 0.1
+scale: 0.5
+shear: 1.5
+perspective: 0.005
+flipud: 0.2
+fliplr: 0.5
+bgr: 0.0
+mosaic: true
+mixup: 0.2
+cutmix: 0.0
+copy_paste: 0.05
+copy_paste_mode: flip
+auto_augment: randaugment
+erasing: 0.1
+cfg: null
+tracker: botsort.yaml
+save_dir: runs\detect\final_model

runs/detect/final_model/results.csv

@@ -0,0 +1,151 @@
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runs/detect/train/args.yaml

@@ -0,0 +1,110 @@
+task: detect
+mode: train
+model: yolo12s.yaml
+data: data.yaml
+epochs: 75
+time: null
+patience: 20
+batch: 32
+imgsz: 640
+save: true
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+- 2
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+tracker: botsort.yaml
+save_dir: runs\detect\train

runs/detect/train/results.csv

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test.py

@@ -4,7 +4,7 @@ import os
 
 def main():
     # 加载训练后的模型
-    model = YOLO("runs/detect/final_model3/weights/best.pt")
+    model = YOLO("runs/detect/final_model/weights/best.pt")
 
     # 在验证集上评估模型性能（添加 workers=0 参数）
     results2 = model.val(data="data.yaml", workers=0)

test_onnx.py

@@ -0,0 +1,8 @@
+import onnx
+import sys
+
+# 打印sys.path以检查模块搜索路径
+print("sys.path:", sys.path)
+
+# 打印onnx模块的属性
+print("dir(onnx):", dir(onnx))

train.py

@@ -115,7 +115,7 @@ def main():
         format="onnx",  # 优先导出ONNX
         # format="torchscript",
         dynamic=True,   # 动态维度
-       # simplify=True   # 简化模型
+        simplify=True   # 简化模型
     )
 
 if __name__ == "__main__":