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c00bc5179e
"data": {
"EventName": "s3:ObjectCreated:Put",
"Key": "mnist/0.png",
"Records": [
{
"eventVersion": "2.0",
"eventSource": "minio:s3",
"awsRegion": "",
"eventTime": "2024-07-31T06:20:44.731Z",
"eventName": "s3:ObjectCreated:Put",
"userIdentity": {
"principalId": "minio"
},
"s3": {
"s3SchemaVersion": "1.0",
"configurationId": "Config",
"bucket": {
"name": "mnist",
"ownerIdentity": {
"principalId": "minio"
},
"arn": "arn:aws:s3:::mnist"
},
"object": {
"key": "0.png",
"size": 324,
"eTag": "ebed21f6f77b0a64673a3c96b0c623ba",
"contentType": "image/png",
"
...
Co-authored-by: jongs <[email protected]>
72 lines
2.5 KiB
Python
72 lines
2.5 KiB
Python
#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from typing import Dict, Union
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import boto3
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import cv2
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import kserve
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from kserve import InferRequest, InferResponse
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from kserve.protocol.grpc.grpc_predict_v2_pb2 import ModelInferResponse
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from kserve.logging import logger
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session = boto3.Session()
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client = session.client(
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"s3",
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endpoint_url="http://minio-service:9000",
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aws_access_key_id="minio",
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aws_secret_access_key="minio123",
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)
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digits_bucket = "digits"
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def image_transform(image):
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img = cv2.imread(image, cv2.IMREAD_GRAYSCALE)
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g = cv2.resize(255 - img, (28, 28))
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g = g.flatten() / 255.0
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return g.tolist()
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class ImageTransformer(kserve.Model):
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def __init__(self, name: str, predictor_host: str):
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super().__init__(name)
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self.predictor_host = predictor_host
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self._key = None
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async def preprocess(
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self, inputs: Union[Dict, InferRequest], headers: Dict[str, str] = None
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) -> Union[Dict, InferRequest]:
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logger.info("Received inputs %s", inputs)
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if inputs["data"]["EventName"] == "s3:ObjectCreated:Put":
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bucket = inputs["data"]["Records"][0]["s3"]["bucket"]["name"]
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key = inputs["data"]["Records"][0]["s3"]["object"]["key"]
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self._key = key
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client.download_file(bucket, key, "/tmp/" + key)
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request = image_transform("/tmp/" + key)
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return {"instances": [request]}
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raise Exception("unknown event")
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async def postprocess(
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self,
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response: Union[Dict, InferResponse, ModelInferResponse],
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headers: Dict[str, str] = None,
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) -> Union[Dict, ModelInferResponse]:
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logger.info("response: %s", response)
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index = response["predictions"][0]["classes"]
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logger.info("digit:" + str(index))
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upload_path = f"digit-{index}/{self._key}"
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client.upload_file("/tmp/" + self._key, digits_bucket, upload_path)
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logger.info(f"Image {self._key} successfully uploaded to {upload_path}")
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return response
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