From 22400e607973224bc3219c1568f9f44954124c66 Mon Sep 17 00:00:00 2001
From: MCG <000914m@gmail.com>
Date: Fri, 15 Nov 2024 21:46:37 +0900
Subject: [PATCH] feat: YOLO_Detection_train 3type_box_detection #22

---
 box_detect/box_plot.ipynb   | 48 ++++++++++++++++++++++++++++++++++++-
 box_detect/yolov11_train.py | 27 +++++++++++++++++++++
 2 files changed, 74 insertions(+), 1 deletion(-)
 create mode 100644 box_detect/yolov11_train.py

diff --git a/box_detect/box_plot.ipynb b/box_detect/box_plot.ipynb
index 94b536d..faf6252 100644
--- a/box_detect/box_plot.ipynb
+++ b/box_detect/box_plot.ipynb
@@ -239,7 +239,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "metadata": {},
    "outputs": [
     {
@@ -313,6 +313,52 @@
     "print(f\"Train and validation datasets created.\")\n",
     "print(f\"Train files: {len(train_files)}, Validation files: {len(valid_files)}\")\n"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "data.yaml file has been created at: /data/ephemeral/home/MCG/yolo_dataset_split/data.yaml\n"
+     ]
+    }
+   ],
+   "source": [
+    "#yaml파일 생성\n",
+    "\n",
+    "import os\n",
+    "\n",
+    "# Define directories\n",
+    "dataset_dir = \"/data/ephemeral/home/MCG/yolo_dataset_split\"\n",
+    "train_dir = os.path.join(dataset_dir, \"train\")\n",
+    "valid_dir = os.path.join(dataset_dir, \"valid\")\n",
+    "yaml_file_path = \"/data/ephemeral/home/MCG/yolo_dataset_split/data.yaml\"\n",
+    "\n",
+    "# Define class names\n",
+    "classes = [\"finger\", \"radius_ulna\", \"others\"]\n",
+    "\n",
+    "# Generate YAML content\n",
+    "yaml_content = f\"\"\"\n",
+    "train: {train_dir}\n",
+    "val: {valid_dir}\n",
+    "\n",
+    "# Number of classes\n",
+    "nc: {len(classes)}\n",
+    "\n",
+    "# Class names\n",
+    "names: {classes}\n",
+    "\"\"\"\n",
+    "\n",
+    "# Write to data.yaml\n",
+    "with open(yaml_file_path, \"w\") as yaml_file:\n",
+    "    yaml_file.write(yaml_content)\n",
+    "\n",
+    "print(f\"data.yaml file has been created at: {yaml_file_path}\")\n"
+   ]
   }
  ],
  "metadata": {
diff --git a/box_detect/yolov11_train.py b/box_detect/yolov11_train.py
new file mode 100644
index 0000000..14771d0
--- /dev/null
+++ b/box_detect/yolov11_train.py
@@ -0,0 +1,27 @@
+from ultralytics import YOLO
+
+# Load a COCO-pretrained YOLO11n model
+model = YOLO("yolo11x.pt")
+
+# Train the model on the COCO8 example dataset for 100 epochs
+results = model.train(
+    data="/data/ephemeral/home/MCG/yolo_dataset_split/data.yaml",
+    epochs=500,
+    imgsz=2048,
+    batch=2,
+    hsv_h=0.0,         # Hue shift 비활성화
+    hsv_s=0.0,         # Saturation shift 비활성화
+    hsv_v=0.2,         # Brightness shift 비활성화
+    degrees=0.2,       # 이미지 회전 비활성화
+    translate=0.0,     # 이미지 이동 비활성화
+    scale=0.2,   
+    shear=0.2,         # 이미지 비틀기 비활성화
+    perspective=0.0,   # 원근 변환 비활성화
+    flipud=0.0,        # 상하 뒤집기 비활성화
+    mosaic=0.0,        # Mosaic 비활성화
+    mixup=0.0,         # Mixup 비활성화
+    copy_paste=0.0 ,    # Copy-Paste 비활성화
+    erasing=0.0,
+    crop_fraction=0.0
+)
+#유지한 증강: Scale, degrees, shear, hsv_v, fliplr