From fc9c49b5f323d56e2b8f1bcfb35edc16895a93dd Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=EA=B9=80=EC=A7=84=ED=98=84?= <kimjh9903@naver.com>
Date: Wed, 18 Sep 2024 01:08:40 +0900
Subject: [PATCH] =?UTF-8?q?Feat:=20get=5Fmodel=5Finfo=20API=20=EA=B5=AC?=
 =?UTF-8?q?=ED=98=84?=
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---
 ai/app/api/yolo/model.py      | 14 ++++++++++++--
 ai/app/services/load_model.py | 17 ++++++++++++++++-
 2 files changed, 28 insertions(+), 3 deletions(-)

diff --git a/ai/app/api/yolo/model.py b/ai/app/api/yolo/model.py
index e9517df..403faac 100644
--- a/ai/app/api/yolo/model.py
+++ b/ai/app/api/yolo/model.py
@@ -1,13 +1,23 @@
 from fastapi import APIRouter, HTTPException
 from schemas.model_create_request import ModelCreateRequest
 from services.init_model import create_pretrained_model, create_default_model
+from services.load_model import load_model
 
 router = APIRouter()
 
 # modelType(detection/segmentation/classification), (default, pretrained), labelCategories
 @router.get("/info")
-def get_model_info(project_id:int, model_path:str):
-    pass
+def get_model_info(model_path:str):
+    try:
+        model = load_model(model_path=model_path)
+    except FileNotFoundError:
+        HTTPException(status_code=404,
+                        detail= f"Cannot found model")
+    except Exception as e:
+        raise HTTPException(status_code=500, detail="model load exception: " + str(e))
+    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'}
+
+    return {"type": model.task, "pretrained":pretrained, "labelCategories":model.names}
 
 #
 @router.get("/list")
diff --git a/ai/app/services/load_model.py b/ai/app/services/load_model.py
index 8693bd8..3359ba2 100644
--- a/ai/app/services/load_model.py
+++ b/ai/app/services/load_model.py
@@ -54,4 +54,19 @@ def load_segmentation_model(model_path: str = "test-data/model/yolov8n-seg.pt",
         model.to("cpu")
     else:
         model.to(device)
-    return model
\ No newline at end of file
+    return model
+
+def load_model(model_path: str):
+    if not os.path.exists(model_path):
+        raise FileNotFoundError(f"Model file not found at path: {model_path}")
+    
+    try:
+        model = YOLO(model_path)
+        if (torch.cuda.is_available()):
+            model.to("cuda")
+            print("gpu 사용")
+        else:
+            model.to("cpu")
+        return model
+    except:
+        raise Exception("YOLO model conversion failed: Unsupported architecture or invalid configuration.")
\ No newline at end of file