Feat: get_model_info API 구현
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@ -1,13 +1,23 @@
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from fastapi import APIRouter, HTTPException
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from schemas.model_create_request import ModelCreateRequest
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from services.init_model import create_pretrained_model, create_default_model
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from services.load_model import load_model
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router = APIRouter()
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# modelType(detection/segmentation/classification), (default, pretrained), labelCategories
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@router.get("/info")
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def get_model_info(project_id:int, model_path:str):
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pass
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def get_model_info(model_path:str):
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try:
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model = load_model(model_path=model_path)
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except FileNotFoundError:
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HTTPException(status_code=404,
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detail= f"Cannot found model")
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except Exception as e:
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raise HTTPException(status_code=500, detail="model load exception: " + str(e))
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pretrained = model.names == {0: 'person', 1: 'bicycle', 2: 'car', 3: 'motorcycle', 4: 'airplane', 5: 'bus', 6: 'train', 7: 'truck', 8: 'boat', 9: 'traffic light', 10: 'fire hydrant', 11: 'stop sign', 12: 'parking meter', 13: 'bench', 14: 'bird', 15: 'cat', 16: 'dog', 17: 'horse', 18: 'sheep', 19: 'cow', 20: 'elephant', 21: 'bear', 22: 'zebra', 23: 'giraffe', 24: 'backpack', 25: 'umbrella', 26: 'handbag', 27: 'tie', 28: 'suitcase', 29: 'frisbee', 30: 'skis', 31: 'snowboard', 32: 'sports ball', 33: 'kite', 34: 'baseball bat', 35: 'baseball glove', 36: 'skateboard', 37: 'surfboard', 38: 'tennis racket', 39: 'bottle', 40: 'wine glass', 41: 'cup', 42: 'fork', 43: 'knife', 44: 'spoon', 45: 'bowl', 46: 'banana', 47: 'apple', 48: 'sandwich', 49: 'orange', 50: 'broccoli', 51: 'carrot', 52: 'hot dog', 53: 'pizza', 54: 'donut', 55: 'cake', 56: 'chair', 57: 'couch', 58: 'potted plant', 59: 'bed', 60: 'dining table', 61: 'toilet', 62: 'tv', 63: 'laptop', 64: 'mouse', 65: 'remote', 66: 'keyboard', 67: 'cell phone', 68: 'microwave', 69: 'oven', 70: 'toaster', 71: 'sink', 72: 'refrigerator', 73: 'book', 74: 'clock', 75: 'vase', 76: 'scissors', 77: 'teddy bear', 78: 'hair drier', 79: 'toothbrush'}
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return {"type": model.task, "pretrained":pretrained, "labelCategories":model.names}
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#
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@router.get("/list")
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@ -54,4 +54,19 @@ def load_segmentation_model(model_path: str = "test-data/model/yolov8n-seg.pt",
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model.to("cpu")
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else:
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model.to(device)
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return model
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return model
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def load_model(model_path: str):
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if not os.path.exists(model_path):
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raise FileNotFoundError(f"Model file not found at path: {model_path}")
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try:
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model = YOLO(model_path)
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if (torch.cuda.is_available()):
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model.to("cuda")
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print("gpu 사용")
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else:
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model.to("cpu")
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return model
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except:
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raise Exception("YOLO model conversion failed: Unsupported architecture or invalid configuration.")
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