TF Serving blog post: sending payloads for inference

TF_servingPost_inference_payload.py

import json
import base64
import requests

# Modify the name of your model (`hv_grid` here) to match what you used in Section 2
server_endpoint = 'http://localhost:8501/v1/models/hv_grid:predict'
img_fpaths = ['path/to/my_image_1.png', 'path/to/my_image_2.png']

# Load and Base64 encode images
data_samples = []
for img_fpath in img_fpaths:
    with open(img_fpath, 'rb') as image_file:
        b64_image = base64.b64encode(image_file.read())
        data_samples.append({'image_bytes': {'b64': b64_image.decode('utf-8')}})

# Create payload request 
payload = json.dumps({"instances": data_samples})