import requests
import cv2
import json
import base64

# Load an image from file
im = cv2.imread("im.png")

# Base64 encode it 
# (you can also load the raw png data from file using open instead of opencv)
encoded = base64.b64encode(cv2.imencode(".png",im)[1].tostring())

# Wrap it in json (tf-serving compatible with instances and b64)
instance =[{"b64":encoded.decode("utf-8")}]
data = json.dumps({"instances": instance})

# Standard port for tf-serving rest interface is 8501
# Request Format: http://domain:[tf-serving-port]/v1/models/[model_name]:predict
resp = requests.post("http://127.0.0.1:8501/v1/models/test_model:predict",data)

# Load base 64 encoded image string from response
prediction = resp.json()["predictions"][0]["b64"]

# Decode base64 to binary string
png_str = base64.b64decode(prediction)

# Write image to disk
with open("pred.png","wb") as file:
  file.write(png_str)