0123

.python-version

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+ml311

app.py

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+import gradio as gr
+import pandas as pd
+import pickle
+
+# 모델 로딩 함수
+def load_model(시설유형):
+    with open(시설유형+".pkl", "rb") as file:
+        loaded_pipeline = pickle.load(file)
+    return loaded_pipeline
+
+# 예측 함수 정의
+def predict_cost(시설유형, 구조, 지하층수, 지상층수, 기준층층고, 최고높이, 연면적, 대지면적, 건축면적, 조경면적, 주차대수, 발주년도, 발주월, 현장위치):
+    new_project = {
+        '구조': [구조],
+        '지하층수': [지하층수],
+        '지상층수': [지상층수],
+        '기준층층고': [기준층층고],
+        '최고높이': [최고높이],
+        '주차대수': [주차대수],
+        '연면적': [연면적],
+        '대지면적': [대지면적],
+        '건축면적': [건축면적],
+        '조경면적': [조경면적],
+        '발주년도': [발주년도],
+        '발주월': [발주월],
+        '현장위치': [현장위치],
+    }
+       
+    model = load_model(시설유형)
+    pred = model.predict(pd.DataFrame.from_dict(new_project))
+
+    return f'{pred[0]:,.0f}일'
+
+with gr.Blocks() as demo:
+    gr.Markdown("## HG 공사기간 예측 모델")
+    with gr.Row():
+        시설유형 = gr.Dropdown(label="시설유형", choices=["일반청사","일반형초중고","기타시설","복합형초중고","대형청사","일반형연구소","노유자시설","일반형전시시설","실험용연구시설","복합형체육시설","복합형대학교","강의형대학교","복지시설","도서관","일반형수련시설","기숙사","대형의료시설","일반형공장","첨단연구시설","복합형수련시설","특수형공장"], 
+                           value='강의형대학교')  # '...'부분에 다른 시설유형 추가
+        현장위치 = gr.Dropdown(label="현장위치", choices=['서울특별시', '제주특별자치도', '경상북도', '울산광역시', '광주광역시', '경기도', '충청북도',
+       '경상남도', '전라남도', '부산광역시', '충청남도', '대구광역시', '강원도', '인천광역시', '전라북도',
+       '세종특별자치시', '대전광역시', '강원특별자치도'], value='광주광역시')  
+        구조 = gr.Dropdown(label="구조", choices=['철근콘크리트조', '철골조', '철골철근콘크리트조', '기타'], value='철골철근콘크리트조')  # '...'부분에 다른 구조 타입 추가
+    with gr.Row():
+        지하층수 = gr.Number(label="지하층수", value=0)
+        지상층수 = gr.Number(label="지상층수", value=7)
+        기준층층고 = gr.Number(label="기준층층고(m)", value=4.5)
+        최고높이 = gr.Number(label="최고높이(m)", value=33.9)
+    with gr.Row():
+        연면적 = gr.Number(label="연면적(m2)", value=4451)
+        대지면적 = gr.Number(label="대지면적(m2)", value=989860)
+        건축면적 = gr.Number(label="건축면적(m2)", value=922)
+        조경면적 = gr.Number(label="조경면적(m2)", value=180)
+    with gr.Row():
+        주차수 = gr.Number(label="주차대수", value=7)
+        발주년 = gr.Number(label="발주년도", value=2023)
+        발주월 = gr.Number(label="발주월", value=8)
+    btn = gr.Button("공사기간 예측")
+    
+    btn.click(
+        predict_cost,
+        inputs=[
+            시설유형, 구조, 지하층수, 지상층수, 기준층층고, 최고높이, 연면적, 대지면적, 건축면적, 조경면적, 주차수, 발주년, 발주월, 현장위치
+        ],
+        outputs=[
+            gr.Textbox(label="공사기간")
+        ]
+    )
+
+demo.launch()

requirements.txt

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+pandas
+scikit-learn==1.3.2
+gradio

강의형대학교.pkl

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+size 137788

기숙사.pkl

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+oid sha256:9fe3cb72c6bb901a74221292df697a0efaffd2dd6052293fec5f141fdda3f437
+size 102405

기타시설.pkl

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+oid sha256:7d86f79a8bddcc35119414f4b350c86db7a52869bae5fa7b00d0ab6b6aff4928
+size 536593

노유자시설.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:6bb06c478fe2ea07d873cbed9815c5a27f1756a1a698e7bd073b7e295a2137c7
+size 290345

대형의료시설.pkl

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+size 109325

대형청사.pkl

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+size 437507

도서관.pkl

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복지시설.pkl

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+size 133060

복합형대학교.pkl

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+size 203353

복합형수련시설.pkl

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복합형체육시설.pkl

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복합형초중고.pkl

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실험용연구시설.pkl

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일반청사.pkl

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일반형공장.pkl

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일반형수련시설.pkl

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일반형연구소.pkl

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일반형전시시설.pkl

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일반형초중고.pkl

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첨단연구시설.pkl

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특수형공장.pkl

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