chore: initial commit for Infrared Equipment Detection System

- Add YOLO-based infrared thermal image detection system
- Add dataset configuration (dataset.yaml) with 12 equipment classes
- Add training, validation and detection scripts
- Add temperature feature extraction and fault diagnosis modules
- Update README and CLAUDE.md with correct dataset paths
- Optimize .gitignore to track dataset.yaml while ignoring large data files

pyproject.toml

@@ -0,0 +1,32 @@
+[project]
+name = "infrared-data"
+version = "0.1.0"
+description = "Infrared Equipment Detection based on YOLO - New Dataset"
+readme = "README.md"
+requires-python = ">=3.10"
+dependencies = [
+    "matplotlib>=3.10.8",
+    "numpy>=2.2.6",
+    "opencv-python>=4.13.0.92",
+    "pandas>=2.3.3",
+    "pillow>=12.1.1",
+    "scikit-learn>=1.7.2",
+    "seaborn>=0.13.2",
+    "torch>=2.5.1",
+    "torchvision>=0.20.1",
+    "tqdm>=4.67.3",
+    "ultralytics>=8.4.27",
+]
+
+# PyTorch CUDA版本配置
+[tool.uv]
+# 指定PyTorch使用CUDA索引
+[[tool.uv.index]]
+name = "pytorch-cu130"
+url = "https://download.pytorch.org/whl/cu130"
+explicit = true
+
+# torch和torchvision从PyTorch索引安装
+[tool.uv.sources]
+torch = [{ index = "pytorch-cu130" }]
+torchvision = [{ index = "pytorch-cu130" }]