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Hi, I've followed along with your Medium article successfully. I've also done this sagemaker tutorial: tensorflow_bring_your_own/tensorflow_bring_your_own.ipynb. The format required to send an image to the TF Serving RESTful endpoint in this tutorial is:
import json
import numpy as np
from PIL import Image
img_path = './img.jpg'
image = np.asarray(Image.open(img_path)).astype(np.float32)
image = np.expand_dims(image, axis=0)
data = {'instances': image}
data = json.dumps({k: _ndarray_to_list(v) for k, v in six.iteritems(data)}) # or sagemaker.predictor.json_serializer
request_args = {}
request_args['Body'] = data
request_args['EndpointName'] = 'my-endpoint-name'
request_args['ContentType'] = 'application/json'
request_args['Accept'] = 'application/json'
response = sagemaker_session.sagemaker_runtime_client.invoke_endpoint(**request_args)
I'm struggling to figure out how I can send either a jpg or image as numpy array to Chalice in order to preprocess the image into this format required for TF serving. Any chance you might be able to help?
The text was updated successfully, but these errors were encountered:
Hi, I've followed along with your Medium article successfully. I've also done this sagemaker tutorial: tensorflow_bring_your_own/tensorflow_bring_your_own.ipynb. The format required to send an image to the TF Serving RESTful endpoint in this tutorial is:
I'm struggling to figure out how I can send either a jpg or image as numpy array to Chalice in order to preprocess the image into this format required for TF serving. Any chance you might be able to help?
The text was updated successfully, but these errors were encountered: