Send and receive images using Flask, Numpy and OpenCV

client.py

from __future__ import print_function
import requests
import json
import cv2

addr = 'http://localhost:5000'
test_url = addr + '/api/test'

# prepare headers for http request
content_type = 'image/jpeg'
headers = {'content-type': content_type}

img = cv2.imread('lena.jpg')
# encode image as jpeg
_, img_encoded = cv2.imencode('.jpg', img)
# send http request with image and receive response
response = requests.post(test_url, data=img_encoded.tostring(), headers=headers)
# decode response
print(json.loads(response.text))

# expected output: {u'message': u'image received. size=124x124'}

server.py

from flask import Flask, request, Response
import jsonpickle
import numpy as np
import cv2

# Initialize the Flask application
app = Flask(__name__)


# route http posts to this method
@app.route('/api/test', methods=['POST'])
def test():
    r = request
    # convert string of image data to uint8
    nparr = np.fromstring(r.data, np.uint8)
    # decode image
    img = cv2.imdecode(nparr, cv2.IMREAD_COLOR)

    # do some fancy processing here....

    # build a response dict to send back to client
    response = {'message': 'image received. size={}x{}'.format(img.shape[1], img.shape[0])
                }
    # encode response using jsonpickle
    response_pickled = jsonpickle.encode(response)

    return Response(response=response_pickled, status=200, mimetype="application/json")


# start flask app
app.run(host="0.0.0.0", port=5000)

Anyone that wants to get image from client and store in buffer can use this snippet below for flask

       ```
        original_image = request.files.get('original image')
        compare_image = request.files.get('compare image')
        original_img = cv2.imdecode(np.frombuffer(original_image.read(), np.uint8), cv2.IMREAD_COLOR)
        compare_img = cv2.imdecode(np.frombuffer(compare_image.read(), np.uint8), cv2.IMREAD_COLOR)
        known_encoding = face_recognition.face_encodings(original_img)[0]
        unknown_encoding = face_recognition.face_encodings(compare_img)[0]

        results = face_recognition.compare_faces([known_encoding], unknown_encoding)

@kylehounslow Thanks for the this understandable scripts.
I would like to pass some more additional information along with image to server. Something like below

meta = {'camera': 'camera', 'distance': 'distance'}
response = requests.post(test_url, data=img_encoded.tostring(), headers=headers, json=meta)

And I access this meta information on the server as input_json = r.get_json(force=True)

But this results in error in client side as below.

Traceback (most recent call last):
  File "/home/keerti/PycharmProjects/Flask_Api/client.py", line 21, in <module>
    print(json.loads(response.text))
  File "/usr/lib/python3.10/json/__init__.py", line 346, in loads
    return _default_decoder.decode(s)
  File "/usr/lib/python3.10/json/decoder.py", line 337, in decode
    obj, end = self.raw_decode(s, idx=_w(s, 0).end())
  File "/usr/lib/python3.10/json/decoder.py", line 355, in raw_decode
    raise JSONDecodeError("Expecting value", s, err.value) from None
json.decoder.JSONDecodeError: Expecting value: line 1 column 1 (char 0)

Could you please help me with this? If this is the right way to pass additional information