Upload 3 files

best v3(100).pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:5b9dc012a5c2e4861c60691272dea39bb065bf709f22182e90c7f90d87ce9619
+size 52054603

main.py

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+from fastapi import FastAPI, UploadFile, File, Form
+from fastapi.responses import JSONResponse
+from ultralytics import YOLO
+import numpy as np
+from PIL import Image
+from datetime import datetime, timedelta
+import psycopg2
+import io
+
+app = FastAPI()
+
+model = YOLO('./best v3(100).pt')
+
+'''def init_connection():
+    return psycopg2.connect(
+        host="localhost",
+        database="water_meter",
+        user="postgres",
+        password="16ecr193@kec"
+    )
+
+def insert_detection(conn, detection_date, water_meter_column, detected_values_str):
+    with conn.cursor() as cur:
+        created_time = datetime.now().strftime("%H:%M:%S")
+
+        cur.execute(f"""
+            INSERT INTO water_meter_readings (detection_date, {water_meter_column}, created_time)
+            VALUES (%s, %s, %s)
+            ON CONFLICT (detection_date) DO UPDATE
+            SET {water_meter_column} = EXCLUDED.{water_meter_column},
+                created_time = EXCLUDED.created_time
+        """, (detection_date, int(detected_values_str), created_time))
+
+        meter_number = water_meter_column.split('_')[-1]
+        difference_column = f'difference_{meter_number}'
+
+        yesterday = detection_date - timedelta(days=1)
+
+        cur.execute(f"""
+            SELECT {water_meter_column}
+            FROM water_meter_readings
+            WHERE detection_date = %s
+        """, (yesterday,))
+        yesterday_result = cur.fetchone()
+
+        if yesterday_result and yesterday_result[0] is not None:
+            difference = int(detected_values_str) - yesterday_result[0]
+        else:
+            difference = None
+
+        if difference is not None:
+            cur.execute(f"""
+                UPDATE water_meter_readings
+                SET {difference_column} = %s
+                WHERE detection_date = %s
+            """, (difference, detection_date))
+        else:
+            cur.execute(f"""
+                UPDATE water_meter_readings
+                SET {difference_column} = NULL
+                WHERE detection_date = %s
+            """, (detection_date,))
+
+        conn.commit()'''
+
+@app.get("/")
+def read_root():
+    return {"message": "Welcome to Water Meter Detection API"}
+
+@app.post("/detect/")
+async def detect_water_meter(
+    #detection_date: str = Form(...),
+    #water_meter: int = Form(...),
+    file: UploadFile = File(...)
+):
+    image_data = await file.read()
+    image = Image.open(io.BytesIO(image_data))
+    img_array = np.array(image)
+
+    results = model.predict(source=img_array, conf=0.25, imgsz=640)
+
+    detected_numbers = []
+    for result in results:
+        for box in result.boxes:
+            label = result.names[box.cls[0].item()]
+            x1, _, _, _ = box.xyxy[0].tolist()
+
+            if label.isdigit():
+                detected_numbers.append((x1, label))
+
+    detected_numbers.sort(key=lambda x: x[0])
+    sorted_numbers = [num for _, num in detected_numbers]
+    detected_values_str = ''.join(sorted_numbers)
+
+    '''if detected_values_str:
+        water_meter_column = f'water_meter_{water_meter}'
+        detection_date_obj = datetime.strptime(detection_date, "%Y-%m-%d").date()
+
+        conn = init_connection()
+        insert_detection(conn, detection_date_obj, water_meter_column, detected_values_str)
+        conn.close()'''
+
+    return JSONResponse(
+        content={
+            "status": "success",
+            "detected_values": detected_values_str if sorted_numbers else "No numeric values detected."
+        }
+    )
+
+if __name__ == "__main__":
+    import uvicorn
+    uvicorn.run(app, host="127.0.0.1", port=8000)

requirements.txt

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+fastapi
+uvicorn
+ultralytics
+Pillow
+numpy
+psycopg2
+python-multipart