74 lines
2.2 KiB
Python
74 lines
2.2 KiB
Python
import json
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import math
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from pathlib import Path
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from ultralytics import YOLO
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import requests
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import argparse
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from clearml import Task # 1. ClearML 임포트
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# 방법 A) 가장 최신 트렌드인 NMS-Free 임베디드 특화 모델 로드
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model = YOLO("./weights/yolo26m.pt") # Medium 크기 가중치 자동 다운로드
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task = Task.init(
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project_name="Normal_Object_Detection",
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task_name="YOLOv26m_coco80_Inference_Agent"
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)
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def xyxy_to_xywh(box: dict) -> dict:
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x1 = math.floor(box["x1"])
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y1 = math.floor(box["y1"])
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x2 = math.ceil(box["x2"])
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y2 = math.ceil(box["y2"])
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return {"x": x1, "y": y1, "w": x2 - x1, "h": y2 - y1}
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# 방법 B) 복잡한 구도나 정밀 식별에 강한 어텐션 기반 모델 로드
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# model = YOLO("yolo12m.pt")
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def main(image_path: str):
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# 이미지 원격 추론 테스트 (COCO 80종 기본 탐지 가능)
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# results = model("https://acai.ketidev.kr:20443/detect/image/202606/20260619_145116_image.jpg")
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results = model(image_path)
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result = results[0]
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image_path = Path(result.path)
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marked_path = image_path.with_name(f"{image_path.stem}_marked{image_path.suffix}")
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result.save(filename=str(marked_path))
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detections = []
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for det in result.summary():
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detections.append({**det, "box": xyxy_to_xywh(det["box"])})
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output = {
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"path": result.path,
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"marked_path": str(marked_path),
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"shape": {"height": result.orig_shape[0], "width": result.orig_shape[1]},
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"speed_ms": result.speed,
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"detections": detections,
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}
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print(json.dumps(output, indent=2, ensure_ascii=False))
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result_data = {"output": output, "status": "PASS"}
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task.upload_artifact(name="final_result", artifact_object=result_data)
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if __name__ == "__main__":
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parser = argparse.ArgumentParser()
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parser.add_argument("--image_url", type=str)
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args = parser.parse_args()
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image_url = args.image_url
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if image_url is None:
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print("Image path is required")
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exit(1)
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response = requests.get(image_url)
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response.raise_for_status()
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image_data = response.content
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with open("image.jpg", "wb") as f:
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f.write(image_data)
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image_path = "image.jpg"
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main(image_path) |