利用AWS內的S3及Lambda上傳圖片及辨識文字

aws lambda aws s3 opencv

bob103 2024-04-30 18:55:49 ‧ 321 瀏覽

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import json
import base64
import boto3
from datetime import datetime
import numpy as np
import cv2
import os
import time


def lambda_handler(event, context):
    s3 = boto3.client('s3')
    
    #bucket_name要改為自己儲存貯體的名稱
    #file_name則是要從儲存貯體拿來辨識的圖片名稱
    bucket_name = 'detectword'
    file_name = "origin.png"
    
   
    img_data = s3.get_object(Bucket=bucket_name, Key=file_name)
    image_data = img_data['Body'].read()
    
    
    nparr = np.frombuffer(image_data, np.uint8)
    image = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
    
    

    
    print('Bucket name: {}'.format(bucket_name))
    print('Upload file name: {}'.format(file_name))
    #get current unix time
    created = int(datetime.now().timestamp())
    #OCR
    client=boto3.client('rekognition')
    response=client.detect_text(Image={'S3Object':{'Bucket':bucket_name,'Name':file_name}})
    print(json.dumps(response))
    
    
        
    # 获取文本区域的信息
    text_detections = response["TextDetections"]

    # 绘制矩形
    for detection in text_detections:
        # 检查是否检测到了文本
        if "Geometry" in detection and "BoundingBox" in detection["Geometry"]:
            box = detection["Geometry"]["BoundingBox"]
            x = int(box["Left"] * image.shape[1])
            y = int(box["Top"] * image.shape[0])
            w = int(box["Width"] * image.shape[1])
            h = int(box["Height"] * image.shape[0])
            cv2.rectangle(image, (x, y), (x+w, y+h), (0, 255, 0), 2)
    
    cv2.imwrite('/tmp/image.jpg', image)
    
    s3.upload_file('/tmp/image.jpg', bucket_name, f"result.png")
    
    return {
        'statusCode': 200,
        'body': json.dumps('Hello from Lambda!')
    }