Question

我已经使用gcloud命令行成功运行了预测。我正在尝试运行Python脚本来运行预测。但我面临的错误。

预测失败：模型执行期间出错：AbortionError（code = StatusCode.INVALID_ARGUMENT，details =＆＃34;断言失败：[无法将字节解码为JPEG，PNG，GIF或BMP] [[Node：map / while / decode_image / cond_jpeg / cond_png / cond_gif / Assert_1 / Assert = Assert [T = [DT_STRING]，summary = 3，_device =＆＃34; / job：localhost / replica：0 / task：0 / device：CPU：0＆＃34;]（map / while / decode_image / cond_jpeg / cond_png / cond_gif / is_bmp，map / while / decode_image / cond_jpeg / cond_png / cond_gif / Assert_1 / Assert / data_0）]]＆＃34;）

from oauth2client.client import GoogleCredentials
from googleapiclient import discovery
from googleapiclient import errors

PROJECTID = 'ai-assignment-185606'
projectID = 'projects/{}'.format(PROJECTID)
modelName = 'food_model'
modelID = '{}/models/{}/versions/{}'.format(projectID, modelName, 'v3')

scopes = ['https://www.googleapis.com/auth/cloud-platform']
credentials = GoogleCredentials.get_application_default()
ml = discovery.build('ml', 'v1', credentials=credentials)

with open('1.jpg', 'rb') as f:
    b64_x = f.read()
import base64
import json

name = "7_5790100434_e2c3dbfdba.jpg";
with open("images/"+name, "rb") as image_file:
    encoded_string = base64.b64encode(image_file.read()).decode('utf-8')
    row = json.dumps({'inputs': {'b64': encoded_string}})

request_body = {"instances": row}

request = ml.projects().predict(name=modelID, body=request_body)
try:
    response = request.execute()
except errors.HttpError as err:
    print(err._get_reason())

if 'error' in response:
    raise RuntimeError(response['error'])

print(response)

此answer表明版本必须相同。我检查了版本1.4和1.4.1。

Answer 1

根据https://cloud.google.com/ml-engine/docs/v1/predict-request，该行应该是数据列表。每个数据可以是值，JSON对象或列表/嵌套列表：

{
  "instances": [
    <value>|<simple/nested list>|<object>,
    ...
  ]
}

相反，您的行是表示JSON的文本字符串（即，收件人必须使用json.loads（行）来获取JSON）。试试这个：

instances = []
with open("images/"+name, "rb") as image_file:
    encoded_string = base64.b64encode(image_file.read()).decode('utf-8')
    instances.append({'b64': encoded_string})

request_body = {"instances": instances}

Answer 2

根据文档here，看起来格式应为：
{"instances": [{"b64": "X5ad6u"}, {"b64": "IA9j4nx"}]}。
但出现以下错误。
RuntimeError: Prediction failed: unknown error.

我必须添加image_bytes才能使其按照this post的要求工作。外观如下：
{"instances": [{"image_bytes": {"b64": encoded_string}, "key": "0"}]

下面的代码段：

@app.route('/predict', methods=['POST'])
def predict():
    if 'images' in request.files:
        file = request.files['images']
        image_path = save_image(file)
        # Convert image to base64
        encoded_string = base64.b64encode(open(file=image_path, mode="rb").read()).decode('utf-8')

        service = discovery.build('ml', 'v1', credentials=credentials)
        name = 'projects/{}/models/{}'.format('my-project-name', 'my-model-name')
        name += '/versions/{}'.format('v1')

        response = service.projects().predict(
            name=name,
            body= {"instances": [{"image_bytes": {"b64": encoded_string}, "key": "0"}]}

        ).execute()

        if 'error' in response:
            raise RuntimeError(response['error'])

        print(response['predictions'])
        return jsonify({'result': response['predictions']})
    else:
        return jsonify({'result': 'Since Image tag is empty, cannot predict'})

Google ML引擎：预测失败：模型执行期间出错

2 个答案: