.. _restapisearchimagesrst:

============================================
Search engines for images through a REST API
============================================


.. only:: html

    **Links:** :download:`notebook <rest_api_search_images.ipynb>`, :downloadlink:`html <rest_api_search_images2html.html>`, :download:`PDF <rest_api_search_images.pdf>`, :download:`python <rest_api_search_images.py>`, :downloadlink:`slides <rest_api_search_images.slides.html>`, :githublink:`GitHub|_doc/notebooks/api_rest/rest_api_search_images.ipynb|*`


This example starts a `waitress <https://github.com/Pylons/waitress>`__
server, creates a
`WSGI <https://en.wikipedia.org/wiki/Web_Server_Gateway_Interface>`__
application based on `falcon <https://falconframework.org/>`__ and
queries the REST API. This application takes an image and searches for
similar images based on features produced by a deep learning model.

.. code:: ipython3

    from jyquickhelper import add_notebook_menu
    add_notebook_menu()






.. contents::
    :local:





.. code:: ipython3

    %matplotlib inline

Settings
--------

.. code:: ipython3

    host = '127.0.0.1'
    port = 8085

Creates the search engine and starts a server in a different process.
See
`search_images_dogcat <http://www.xavierdupre.fr/app/ensae_projects/helpsphinx/ensae_projects/restapi/search_images_dogcat.html?highlight=search_images_dogcat#module-ensae_projects.restapi.search_images_dogcat>`__.

.. code:: ipython3

    code = """
    def process_server_images(host, port):
        # Enable the section to intercept logged information.
        import logging
        logging.basicConfig(level=logging.DEBUG)
        logger = logging.getLogger('search_images_dogcat')
        logger.setLevel(logging.INFO)
        hdlr = logging.FileHandler('search_images_dogcat.log')
        formatter = logging.Formatter('%(asctime)s %(levelname)s %(message)s')
        hdlr.setFormatter(formatter)
        logger.addHandler(hdlr)
    
        url = None
        # If not specified, the application looks for zip file:
        # http://www.xavierdupre.fr/enseignement/complements/dog-cat-pixabay.zip
        from ensae_projects.restapi import search_images_dogcat
        app = search_images_dogcat(url_images=url, module="torch")
    
        from waitress import serve
        print("Start")
        serve(app, host=host, port=port)
    
    print("Begin")
    """

Saves this code into a file and adds additional paths.

.. code:: ipython3

    import os
    import ensae_projects
    
    def path_module(mod):
        m = __import__(mod)
        return os.path.normpath(os.path.abspath(os.path.join(os.path.dirname(m.__file__), '..')))
    
    
    code = code + "\nprocess_server_images('{0}', {1})\n".format(host, port)
    dest = os.path.abspath('temp_scripts')
    if not os.path.exists(dest):
        os.mkdir(dest)
    code_file = os.path.join(dest, "_start_server.py")
    print("Write file '{0}'.".format(code_file))
    with open(code_file, "w") as f:
        f.write(code)
    
    print('# final code to run')
    print(code)


.. parsed-literal::
    Write file 'C:\xavierdupre\__home_\GitHub\ensae_projects\_doc\notebooks\api_rest\temp_scripts\_start_server.py'.
    # final code to run
    def process_server_images(host, port):
        # Enable the section to intercept logged information.
        import logging
        logging.basicConfig(level=logging.DEBUG)
        logger = logging.getLogger('search_images_dogcat')
        logger.setLevel(logging.INFO)
        hdlr = logging.FileHandler('search_images_dogcat.log')
        formatter = logging.Formatter('%(asctime)s %(levelname)s %(message)s')
        hdlr.setFormatter(formatter)
        logger.addHandler(hdlr)
        url = None
        # If not specified, the application looks for zip file:
        # http://www.xavierdupre.fr/enseignement/complements/dog-cat-pixabay.zip
        from ensae_projects.restapi import search_images_dogcat
        app = search_images_dogcat(url_images=url, module="torch")
        from waitress import serve
        print("Start")
        serve(app, host=host, port=port)
    print("Begin")
    process_server_images('127.0.0.1', 8085)
    


Starts the server
-----------------

.. code:: ipython3

    import sys
    from subprocess import Popen
    if sys.platform.startswith('win'):
        cmd = '{0} -u "{1}"'.format(sys.executable.replace('w.exe', '.exe'),
                                    code_file)
        print("Running '{0}'".format(cmd))
        proc = Popen(cmd)
    else:
        cmd = [sys.executable, '-u', code_file]
        print("Running '{0}'".format(cmd))
        proc = Popen(cmd)
    print('Start server, process id', proc.pid)


.. parsed-literal::
    Running 'c:\python370_x64\python.exe -u "C:\xavierdupre\__home_\GitHub\ensae_projects\_doc\notebooks\api_rest\temp_scripts\_start_server.py"'
    Start server, process id 15556


Let’s wait.

.. code:: ipython3

    from time import sleep
    sleep(10)

Let’s load an image.
--------------------

.. code:: ipython3

    from lightmlrestapi.args import image2base64
    import ensae_projects.datainc.search_images as si
    imgfile = os.path.abspath(os.path.join(
        os.path.dirname(si.__file__), "cat-1192026__480.jpg"))
    if not os.path.exists(imgfile):
        raise FileNotFoundError("Unable to find '{0}'".format(imgfile))

.. code:: ipython3

    from PIL import Image
    img = Image.open(imgfile)
    
    import numpy
    from matplotlib.pyplot import imshow
    imshow(numpy.asarray(img));



.. image:: rest_api_search_images_15_0.png


Let’s query the server
----------------------

The first query is quite long as it loads the model.

.. code:: ipython3

    import requests
    import ujson
    
    b64 = image2base64(imgfile)[1]
    features = ujson.dumps({'X': b64})
    url_api = 'http://127.0.0.1:%d' % port
    r = requests.post(url_api, data=features, timeout=15)
    r




.. parsed-literal::
    <Response [201]>



.. code:: ipython3

    js = r if isinstance(r, dict) else r.json()
    if 'description' in js:
        # This is an error.
        print("ERROR:", js['description'])
        res = None
    else:
        res = []
        ans = js['Y']
        print("Number of neighbors:", len(ans))
        for n in ans:
            print("score, id", n[:2])
            shortname = n[2]['name'].replace("\\", "/").split('/')
            res.append((n[0], "/".join(shortname[-2:])))


.. parsed-literal::
    Number of neighbors: 5
    score, id [45.7871682992, 1]
    score, id [66.0685246001, 11]
    score, id [82.5819784952, 5]
    score, id [83.3830068399, 28]
    score, id [85.5619601811, 0]


.. code:: ipython3

    %timeit requests.post(url_api, data=features, timeout=60)


.. parsed-literal::
    107 ms ± 551 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)


Let’s display the images.

.. code:: ipython3

    txts = list(map(lambda x: str(x[0]), res))
    imgs = list(map(lambda x: os.path.join(
        'temp_scripts', 'images', x[1]), res))
    if not os.path.exists(imgs[0]):
        imgs = list(map(lambda x: os.path.join(
            'images', x[1]), res))
    
    from mlinsights.plotting import plot_gallery_images
    try:
        plot_gallery_images(imgs, txts)
    except FileNotFoundError as e:
        raise FileNotFoundError("Unable to find images '{0}' - cwd='{1}' full='{2}'".format(
            imgs[0], os.getcwd(), os.path.abspath(imgs[0])))



.. image:: rest_api_search_images_21_0.png


Stop the server
---------------

.. code:: ipython3

    from pyquickhelper.loghelper import reap_children
    reap_children(subset={proc.pid}, fLOG=print)


.. parsed-literal::
    process psutil.Process(pid=15556, status='terminated') terminated with exit code 15




.. parsed-literal::

    {15556}