commit 20b660c943228f731fc14a6a5d9f36120af473d9 Author: fly6516 Date: Thu May 29 19:59:57 2025 +0800 feat(datasets): 添加新的训练数据标签 - 在 datasets/train/labels 目录下新增了多个标签文件 - 文件命名格式为：视频ID-帧序号.jpg.rf.哈希值.txt -标签内容包括物体类别和位置信息，用于训练目标检测模型 diff --git a/README.dataset.txt b/README.dataset.txt new file mode 100644 index 0000000..35da9bc --- /dev/null +++ b/README.dataset.txt @@ -0,0 +1,6 @@ +# control panel v4 > 2023-06-06 6:44pm +https://universe.roboflow.com/class-swogf/control-panel-v4 + +Provided by a Roboflow user +License: Public Domain + diff --git a/README.roboflow.txt b/README.roboflow.txt new file mode 100644 index 0000000..54a5dda --- /dev/null +++ b/README.roboflow.txt @@ -0,0 +1,29 @@ + +control panel v4 - v19 2023-06-06 6:44pm +============================== + +This dataset was exported via roboflow.com on May 29, 2025 at 10:27 AM GMT + +Roboflow is an end-to-end computer vision platform that helps you +* collaborate with your team on computer vision projects +* collect & organize images +* understand and search unstructured image data +* annotate, and create datasets +* export, train, and deploy computer vision models +* use active learning to improve your dataset over time + +For state of the art Computer Vision training notebooks you can use with this dataset, +visit https://github.com/roboflow/notebooks + +To find over 100k other datasets and pre-trained models, visit https://universe.roboflow.com + +The dataset includes 98 images. +Buttons-on are annotated in YOLOv12 format. + +The following pre-processing was applied to each image: +* Auto-orientation of pixel data (with EXIF-orientation stripping) +* Resize to 416x416 (Stretch) + +No image augmentation techniques were applied. + + diff --git a/data.yaml b/data.yaml new file mode 100644 index 0000000..8d18f35 --- /dev/null +++ b/data.yaml @@ -0,0 +1,6 @@ +train: ../train/images +val: ../valid/images +test: ../test/images + +nc: 3 +names: ['button-off', 'button-on', 'gauge'] diff --git 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b/datasets/valid/labels/trial01_0029_jpg.rf.9b32c71001ee348503f3630f0df7ae8d.txt new file mode 100644 index 0000000..c00afbe --- /dev/null +++ b/datasets/valid/labels/trial01_0029_jpg.rf.9b32c71001ee348503f3630f0df7ae8d.txt @@ -0,0 +1 @@ +1 0.5072115384615384 0.3641826923076923 0.026442307692307692 0.052884615384615384 \ No newline at end of file diff --git a/datasets/valid/labels/trial01_0035_jpg.rf.e68c7cf7671497d22c6370ab5bc9dfa9.txt b/datasets/valid/labels/trial01_0035_jpg.rf.e68c7cf7671497d22c6370ab5bc9dfa9.txt new file mode 100644 index 0000000..f38b41b --- /dev/null +++ b/datasets/valid/labels/trial01_0035_jpg.rf.e68c7cf7671497d22c6370ab5bc9dfa9.txt @@ -0,0 +1,3 @@ +1 0.3786057692307692 0.34975961538461536 0.12860576923076922 0.2403846153846154 +1 0.5444711538461539 0.33653846153846156 0.12379807692307693 0.22235576923076922 +1 0.7043269230769231 0.328125 0.1346153846153846 0.23197115384615385 \ No newline at end of file diff --git a/test.py b/test.py new file mode 100644 index 0000000..f550a13 --- /dev/null +++ b/test.py @@ -0,0 +1,4 @@ +from ultralytics import YOLO + +model = YOLO("yolov12s.yaml") +print("Model loaded successfully!") diff --git a/train.py b/train.py new file mode 100644 index 0000000..c1e44b5 --- /dev/null +++ b/train.py @@ -0,0 +1,131 @@ + +""" +YOLOv12 绝缘子检测优化训练脚本（最终稳定版） +主要改进： +1. 适配YOLOv12 参数规范 +2. 移除已弃用参数 +3. 优化训练配置 +""" + +import torch +from ultralytics import YOLO +import shutil +import os +import glob +from PIL import Image, ImageDraw +import numpy as np + +# +++ 有效参数配置区块 +++ +TRAIN_CONFIG = { + "stage1": { + "freeze": [0, 1, 2, 3, 4], # 冻结前5层 + "epochs": 75, # 增加训练轮数 + "batch": 32, # 增加批量大小 + "lr0": 0.001, # 降低初始学习率 + "lrf": 0.1, # 提高最终学习率 + "hsv_h": 0.01, # 色相增强幅度 + "degrees": 10.0, # 增加旋转角度范围 + "perspective": 0.005, # 增加透视变换 + "flipud": 0.2, # 增加上下翻转概率 + "optimizer": "SGD", # 优化器类型 + "weight_decay": 0.001, # 权重衰减 + "label_smoothing": 0.1, # 标签平滑 + "mosaic": True, # 启用Mosaic增强 + # "class_weights": [1.0, 2.0] # 设置类别权重，insulator权重更高 + }, + "stage2": { + "epochs": 150, # 增加训练轮数 + "batch": 16, # 增加批量大小 + "lr0": 0.0001, # 降低初始学习率 + "lrf": 0.01, # 提高最终学习率 + "mixup": 0.2, # 增加MixUp增强系数 + "close_mosaic": 10, # 最后10epoch关闭Mosaic + "optimizer": "AdamW", # 切换优化器为AdamW + "warmup_epochs": 10 # 增大学习率预热轮数 + } +} + +def enhanced_data_check(): + """增强型数据验证（稳定版）""" + print("\n=== 执行增强数据验证 ===") + label_files = glob.glob("datasets/insulator/labels/*.txt") + class_dist = {} + + # 类别分布分析 + for lbl in label_files: + with open(lbl) as f: + for line in f: + class_id = int(line.strip().split()[0]) + class_dist[class_id] = class_dist.get(class_id, 0) + 1 + + print(f"类别分布：{class_dist}") + + # 样本可视化（示例保留结构） + sample_count = 3 + for i in range(sample_count): + img_path = f"datasets/insulator/images/{i:04d}.jpg" + lbl_path = f"datasets/insulator/labels/{i:04d}.txt" + # 添加实际可视化逻辑 + +def main(): + # 初始化模型（正确方式） + model = YOLO("yolo12s.yaml") # 确保yaml文件存在 + + # === 阶段一：冻结训练 === + print("\n=== 阶段一：特征提取层训练 ===") + stage1_results = model.train( + data="data.yaml", + **TRAIN_CONFIG["stage1"], + device=0, + workers=4, + box=5.0, # box损失权重 + cls=1.0, # 分类损失权重 + save_period=5, # 每5epoch保存检查点 + patience=20, # 早停等待周期 + deterministic=False # 禁用确定性模式 + ) + + # === 阶段二：全网络微调 === + print("\n=== 阶段二：全网络微调 ===") + stage2_results = model.train( + data="data.yaml", + **TRAIN_CONFIG["stage2"], + resume=True, # 从上一阶段继续 + name="final_model", # 实验名称 + shear=1.5, # 剪切变换幅度 + copy_paste=0.05, # 复制粘贴增强 + erasing=0.1, # 随机擦除概率 + overlap_mask=False # 禁用掩码重叠 + ) + + # === 模型验证 === + print("\n=== 最终模型验证 ===") + metrics = model.val( + data="data.yaml", + conf=0.35, # 置信度阈值 + iou=0.65, # IoU阈值 + plots=True, # 生成评估图表 + half=False # 禁用半精度验证 + ) + + # === 模型导出 === + print("\n=== 模型导出 ===") + model.export( + opset_version=15, + format="onnx", # 优先导出ONNX + # format="torchscript", + dynamic=True, # 动态维度 + simplify=True # 简化模型 + ) + +if __name__ == "__main__": + # 硬件优化配置 + torch.set_float32_matmul_precision('high') + torch.backends.cudnn.benchmark = True + os.environ["CUBLAS_WORKSPACE_CONFIG"] = ":16:8" + + # 数据检查 + enhanced_data_check() + + # 启动训练 + main()