Using pytineye to automate searching for images.

The TinEye API is ideally suited for image and profile verification, UGC moderation, copyright compliance and fraud detection.
Read more about the TinEye API here.
You need to use authentication for this API, read here.
To use the TinEye API you must purchase a search bundle.
The documentation for Python can be found here.
Let's start with the installation.
You need to download the zip file from GitHub and install using the pip tool:

C:\Python373\Scripts>pip3.7.exe install pytineye-master.zip
...
Successfully installed pytineye-1.3

>>> import pytineye
>>> from pytineye import TinEyeAPIRequest
>>> myapi = TinEyeAPIRequest('http://api.tineye.com/rest/', 'your_public_key', 'your_private_key')
>>> myapi.remaining_searches()
{'bundles': [], 'total_remaining_searches': 0}

Because I don't have search the python code return an error:

>>> myapi.search_url(url='http://en.es-static.us/upl/2019/03/rogue-planet-CFBD-S
IR-J214947.2-040308.9-2012-800x450.jpg')
Traceback (most recent call last):
  File "", line 1, in 
  File "C:\Python373\lib\site-packages\pytineye\api.py", line 304, in search_url

    obj = self._request('search', params, **kwargs)
  File "C:\Python373\lib\site-packages\pytineye\api.py", line 276, in _request
    raise TinEyeAPIError(obj['code'], obj.get('messages'))
pytineye.exceptions.TinEyeAPIError: APIError:
                   code    = 401
                   message = ['AUTHORIZATION_ERROR', 'You have no more searches
available. Please purchase another bundle if you wish to make more searches.']

If you want to buy TinEye API searches then the prices start from:
5,000 searches $200.00 USD($0.04 per search)
10,000 searches $300.00 USD($0.03 per search)
50,000 searches $1,000.00 USD($0.02 per search)
1,000,000 searches $10,000.00 USD($0.01 per search)

First test with 3.7.3 and opencv-python module version 4.0.0 .

The Python 3.7.3 is the third maintenance release of Python 3.7 and is released at March 25, 2019.
More about this new released version can be found at official website.

C:\Python373\Scripts>pip install opencv-python
Collecting opencv-python
...
Installing collected packages: numpy, opencv-python
Successfully installed numpy-1.16.2 opencv-python-4.0.0.21

Let's test it:

C:\Python373>python.exe
Python 3.7.3 (v3.7.3:ef4ec6ed12, Mar 25 2019, 22:22:05) [MSC v.1916 64 bit (AMD64)]
 on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> import cv2
>>> cv2.__version__
'4.0.0'

Let test a simple example that computes a dense optical flow using the Gunnar Farneback’s algorithm.

import cv2
import numpy as np
cap = cv2.VideoCapture(0)
ret, frame1 = cap.read()
prvs = cv2.cvtColor(frame1,cv2.COLOR_BGR2GRAY)
hsv = np.zeros_like(frame1)
hsv[...,1] = 255
while(1):
    ret, frame2 = cap.read()
    next = cv2.cvtColor(frame2,cv2.COLOR_BGR2GRAY)
    flow = cv2.calcOpticalFlowFarneback(prvs,next, None, 0.1, 1, 2, 3, 5, 11.2, 0)
    mag, ang = cv2.cartToPolar(flow[...,0], flow[...,1])
    hsv[...,0] = ang*180/np.pi/2
    hsv[...,2] = cv2.normalize(mag,None,0,255,cv2.NORM_MINMAX)
    bgr = cv2.cvtColor(hsv,cv2.COLOR_HSV2BGR)
    cv2.imshow('frame2',bgr)
    k = cv2.waitKey(30) & 0xff
    if k == 27:
        break
    prvs = next
cap.release()
cv2.destroyAllWindows()