1. 使用AWS SDK或CLI上传S3时，请确保manifest文件不超过5000行。
2. 可以将manifest文件拆分为多个文件，以确保每个文件行数不超过5000。
3. 使用AWS Rekognition时，请确保使用正确的文件格式和参数，以确保上传的数据符合要求，参考以下代码示例：

import boto3
import os
import codecs
import json

rekognition = boto3.client('rekognition')

bucket = "my-bucket"
photos = ["photo1.jpg", "photo2.jpg", "photo3.jpg"]
manifest_filename = "my-manifest-file.json"

manifest = []
for photo in photos:
    full_path = os.path.join(bucket, photo)
    manifest.append({"source-ref": full_path})

#Write the manifest to disk
with codecs.open(manifest_filename, 'w', encoding="utf8") as json_file:
    json_file.write(json.dumps(manifest, ensure_ascii=False))

#Upload the manifest file and the images to Amazon S3
s3 = boto3.resource('s3')
s3_bucket = s3.Bucket(bucket)
s3_bucket.upload_file(manifest_filename, manifest_filename)

for photo in photos:
    s3_bucket.upload_file(photo, photo)

#Start the search using Amazon Rekognition
response = rekognition.start_face_search(Video = {"S3Object": {"Bucket": bucket, "Name": "my-video.mp4"}},
                                         FaceMatchThreshold = 80,
                                         CollectionId = "my-collection-id",
                                         JobTag = "my-job-tag",
                                         NotificationChannel = {"RoleArn": "arn:aws:iam::0123456789012:role/my-notification-role", "SNSTopicArn": "arn:aws:sns:us-east-1:0123456789012:my-topic"})
        
job_id=response['JobId']
print('Started job:' + job_id)

在这个例子中，我们制作了一个搜索视频中人脸的示例，其中上传了多个图像并使用了一个manifest文件。该文件是包含每个图像S3位置的JSON文件。请注意manifest文件必须少于或等