{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Requirement already satisfied: roboflow in c:\\users\\ai_team\\.conda\\envs\\yolov11\\lib\\site-packages (1.1.50)\n", "Requirement already satisfied: certifi in c:\\users\\ai_team\\.conda\\envs\\yolov11\\lib\\site-packages (from roboflow) (2024.12.14)\n", "Requirement already satisfied: idna==3.7 in c:\\users\\ai_team\\.conda\\envs\\yolov11\\lib\\site-packages (from roboflow) (3.7)\n", "Requirement already satisfied: cycler in c:\\users\\ai_team\\.conda\\envs\\yolov11\\lib\\site-packages (from roboflow) (0.12.1)\n", "Requirement already satisfied: kiwisolver>=1.3.1 in c:\\users\\ai_team\\.conda\\envs\\yolov11\\lib\\site-packages (from roboflow) (1.4.8)\n", "Requirement already satisfied: matplotlib in c:\\users\\ai_team\\.conda\\envs\\yolov11\\lib\\site-packages (from roboflow) (3.10.0)\n", "Requirement already satisfied: numpy>=1.18.5 in 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c:\\users\\ai_team\\.conda\\envs\\yolov11\\lib\\site-packages (from roboflow) (2.3.0)\n", "Requirement already satisfied: tqdm>=4.41.0 in c:\\users\\ai_team\\.conda\\envs\\yolov11\\lib\\site-packages (from roboflow) (4.67.1)\n", "Requirement already satisfied: PyYAML>=5.3.1 in c:\\users\\ai_team\\.conda\\envs\\yolov11\\lib\\site-packages (from roboflow) (6.0.2)\n", "Requirement already satisfied: requests-toolbelt in c:\\users\\ai_team\\.conda\\envs\\yolov11\\lib\\site-packages (from roboflow) (1.0.0)\n", "Requirement already satisfied: filetype in c:\\users\\ai_team\\.conda\\envs\\yolov11\\lib\\site-packages (from roboflow) (1.2.0)\n", "Requirement already satisfied: colorama in c:\\users\\ai_team\\.conda\\envs\\yolov11\\lib\\site-packages (from tqdm>=4.41.0->roboflow) (0.4.6)\n", "Requirement already satisfied: contourpy>=1.0.1 in c:\\users\\ai_team\\.conda\\envs\\yolov11\\lib\\site-packages (from matplotlib->roboflow) (1.3.1)\n", "Requirement already satisfied: fonttools>=4.22.0 in c:\\users\\ai_team\\.conda\\envs\\yolov11\\lib\\site-packages (from matplotlib->roboflow) (4.55.3)\n", "Requirement already satisfied: packaging>=20.0 in c:\\users\\ai_team\\.conda\\envs\\yolov11\\lib\\site-packages (from matplotlib->roboflow) (24.2)\n", "Requirement already satisfied: pyparsing>=2.3.1 in c:\\users\\ai_team\\.conda\\envs\\yolov11\\lib\\site-packages (from matplotlib->roboflow) (3.2.1)\n", "Requirement already satisfied: charset-normalizer<4,>=2 in c:\\users\\ai_team\\.conda\\envs\\yolov11\\lib\\site-packages (from requests->roboflow) (3.4.1)\n", "loading Roboflow workspace...\n", "loading Roboflow project...\n", "Exporting format coco in progress : 85.0%\n", "Version export complete for coco format\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Downloading Dataset Version Zip in AI-ELANG-availability-5 to coco:: 100%|██████████| 66591/66591 [00:09<00:00, 6979.17it/s]" ] }, { "name": "stdout", "output_type": "stream", "text": [ "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "\n", "Extracting Dataset Version Zip to AI-ELANG-availability-5 in coco:: 100%|██████████| 930/930 [00:00<00:00, 1075.75it/s]\n" ] } ], "source": [ "!pip install roboflow\n", "\n", "from roboflow import Roboflow\n", "rf = Roboflow(api_key=\"SPm4M5SwBEk2iz9jgn6G\")\n", "project = rf.workspace(\"elang-kub3m\").project(\"ai-elang-availability\")\n", "version = project.version(5)\n", "dataset = version.download(\"coco\")" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "ename": "ModuleNotFoundError", "evalue": "No module named 'detectron2'", "output_type": "error", "traceback": [ "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[1;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)", "Cell \u001b[1;32mIn[2], line 2\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21;01mos\u001b[39;00m\n\u001b[1;32m----> 2\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21;01mdetectron2\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mengine\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m DefaultTrainer\n\u001b[0;32m 3\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21;01mdetectron2\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mconfig\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m get_cfg\n\u001b[0;32m 4\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21;01mdetectron2\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mdata\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mdatasets\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m register_coco_instances\n", "\u001b[1;31mModuleNotFoundError\u001b[0m: No module named 'detectron2'" ] } ], "source": [ "import os\n", "from detectron2.engine import DefaultTrainer\n", "from detectron2.config import get_cfg\n", "from detectron2.data.datasets import register_coco_instances\n", "from detectron2 import model_zoo\n", "import torch\n", "\n", "# Periksa apakah GPU tersedia\n", "device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n", "print(f\"Menggunakan perangkat: {device}\")\n", "\n", "# Path ke dataset\n", "dataset_dir = r\"G:\\MAGANG\\ai elang coco update 17 januari 2025\\AI-ELANG-availability-5\"\n", "train_images = os.path.join(dataset_dir, \"train\")\n", "val_images = os.path.join(dataset_dir, \"val\")\n", "train_annotations = os.path.join(dataset_dir, \"annotations/instances_train.json\")\n", "val_annotations = os.path.join(dataset_dir, \"annotations/instances_val.json\")\n", "\n", "# Registrasi dataset ke Detectron2\n", "register_coco_instances(\"ai_elang_train\", {}, train_annotations, train_images)\n", "register_coco_instances(\"ai_elang_val\", {}, val_annotations, val_images)\n", "\n", "# Konfigurasi model\n", "cfg = get_cfg()\n", "cfg.merge_from_file(model_zoo.get_config_file(\"COCO-Detection/faster_rcnn_R_50_FPN_3x.yaml\")) # Ganti model jika perlu\n", "cfg.DATASETS.TRAIN = (\"ai_elang_train\",)\n", "cfg.DATASETS.TEST = (\"ai_elang_val\",)\n", "cfg.DATALOADER.NUM_WORKERS = 4\n", "cfg.MODEL.WEIGHTS = model_zoo.get_checkpoint_url(\"COCO-Detection/faster_rcnn_R_50_FPN_3x.yaml\") # Pretrained weights\n", "cfg.SOLVER.IMS_PER_BATCH = 4 # Sesuaikan dengan GPU Anda\n", "cfg.SOLVER.BASE_LR = 0.001 # Learning rate\n", "cfg.SOLVER.MAX_ITER = 3000 # Jumlah iterasi\n", "cfg.SOLVER.STEPS = [] # Milestones untuk penurunan LR\n", "cfg.MODEL.ROI_HEADS.BATCH_SIZE_PER_IMAGE = 128 # Per batch\n", "cfg.MODEL.ROI_HEADS.NUM_CLASSES = 1 # Ganti sesuai jumlah kelas dataset Anda\n", "\n", "# Set perangkat ke GPU/CPU\n", "cfg.MODEL.DEVICE = device\n", "\n", "# Path untuk menyimpan hasil\n", "output_dir = r\"G:\\MAGANG\\ai elang coco update 17 januari 2025\\output\"\n", "os.makedirs(output_dir, exist_ok=True)\n", "cfg.OUTPUT_DIR = output_dir\n", "\n", "# Mulai pelatihan\n", "trainer = DefaultTrainer(cfg)\n", "trainer.resume_or_load(resume=False)\n", "trainer.train()\n", "\n", "print(\"Pelatihan selesai. Model disimpan di:\", cfg.OUTPUT_DIR)\n" ] } ], "metadata": { "kernelspec": { "display_name": "yolov11", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.12" } }, "nbformat": 4, "nbformat_minor": 2 }