Why did my Facial Detection Script suddenly stop working?

Question

I am using Google Cloud Vision to detect faces within images. Earlier today, my code was working perfectly fine. This code is supposed to create a JSON string explaining if the image has a face, how certain Google vision is, and if there is an exception. However, now it is giving me an error message that I am finding hard to debug. The code is seen below:

import io
import os
import json

# Imports the Google Cloud client library
from google.cloud import vision
from google.cloud.vision import types

class Face_Detector:

# Constructor for Face Detector
def __init__(self, im):
    self.im_file = im

# Creates String in Json format given whether a face was detected
# the confidence if yes, and the name of an exception if one was triggered
# (f_d is false if an exception is triggered)
# (con is None if f_d is false)
# (ex is None if an exception is not triggered)
def formatJson(self, f_d, con, ex):
    # Generates json String
    dic = { 
        "face_detected" :   f_d,
         "confidence"   :   con,
         "exception"    :   ex
        }
    jsonA = json.dumps(dic);

    return jsonA

# Checks image to see if a face exists
def detect_face(self):

    # vairbles to be used in Json

    # is face detected
    f_d = False
    # with what ertainty
    con = None
    # if there is an exception, displays which one
    ex = None

    try:
        # Creates an environment variable
        credential_path = "C:\\Users\\Nick\\Desktop\\Proj1-7f68a23c3dd0.json"
        os.environ['GOOGLE_APPLICATION_CREDENTIALS'] = credential_path

        # Uses object field to define local variable
        im_file = self.im_file

        # Checks for valid file type
        if(not (im_file[-4:] == ".jpg" or im_file[-4:] == ".png" or im_file[-5:] == ".jpeg")):
            ex = "Invalid file type."
            return Face_Detector.formatJson(self, f_d, con, ex)

        # Checks for images that are too large or too small
        im_size = os.stat(im_file).st_size
        if(im_size == 0):
            ex = "Image file size of 0."
            return Face_Detector.formatJson(self, f_d, con, ex)
        elif(im_size > 10485760):
            ex = "Exceeds image file size limit of 10MB."
            return Face_Detector.formatJson(self, f_d, con, ex)

        # Instantiates a client
        client = vision.ImageAnnotatorClient()

        # Concatenates the service key address and the image file address
        file_name = os.path.join(
            os.path.dirname("C:\\Users\\Nick\\Desktop\\<ProjectName>"),
            im_file)

        # Loads the image into RAM
        with io.open(file_name, 'rb') as image_file:
            content = image_file.read()

        # Makes data type compatable with the Google Cloud API
        image = types.Image(content=content)

        # Performs face detection
        response = client.face_detection(image=image)
        faces = response.face_annotations

        # Checks for the existance of face and confidence
        for face in faces:
            f_d = True
            con = face.detection_confidence
        return Face_Detector.formatJson(self, f_d, con, ex)

    except FileNotFoundError:
        ex = "File Not Found."
        return Face_Detector.formatJson(self, f_d, con, ex)


im = r"C:\\Users\\Nick\\Desktop\\Images\\Face2.jpg"
i = Face_Detector(im)
print(i.detect_face())

As of now, it seems to be producing this error:

Traceback (most recent call last):
File "C:\Users\Nick\AppData\Local\Programs\Python\Python36\lib\site-packages\google\api_core\grpc_helpers.py", line 57, in error_remapped_callable
    return callable_(*args, **kwargs)
  File "C:\Users\Nick\AppData\Local\Programs\Python\Python36\lib\site-packages\grpc\_channel.py", line 549, in __call__
    return _end_unary_response_blocking(state, call, False, None)
  File "C:\Users\Nick\AppData\Local\Programs\Python\Python36\lib\site-packages\grpc\_channel.py", line 466, in _end_unary_response_blocking
    raise _Rendezvous(state, None, None, deadline)
grpc._channel._Rendezvous: <_Rendezvous of RPC that terminated with:
    status = StatusCode.UNAVAILABLE
    details = "Getting metadata from plugin failed with error: ('invalid_grant: Invalid JWT: Token must be a short-lived token (60 minutes) and in a reasonable timeframe. Check your iat and exp values and use a clock with skew to account for clock differences between systems.', '{\n  "error": "invalid_grant",\n  "error_description": "Invalid JWT: Token must be a short-lived token (60 minutes) and in a reasonable timeframe. Check your iat and exp values and use a clock with skew to account for clock differences between systems."\n}')"
    debug_error_string = "{"created":"@1553027287.140000000","description":"Getting metadata from plugin failed with error: ('invalid_grant: Invalid JWT: Token must be a short-lived token (60 minutes) and in a reasonable timeframe. Check your iat and exp values and use a clock with skew to account for clock differences between systems.', '{\n  "error": "invalid_grant",\n  "error_description": "Invalid JWT: Token must be a short-lived token (60 minutes) and in a reasonable timeframe. Check your iat and exp values and use a clock with skew to account for clock differences between systems."\n}')","file":"src/core/lib/security/credentials/plugin/plugin_credentials.cc","file_line":79,"grpc_status":14}"
>

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "C:\Users\Nick\Desktop\Python Stuff\Face_Detector.py", line 97, in <module>
    print(i.detect_face())
  File "C:\Users\Nick\Desktop\Python Stuff\Face_Detector.py", line 81, in detect_face
    response = client.face_detection(image=image)
  File "C:\Users\Nick\AppData\Local\Programs\Python\Python36\lib\site-packages\google\cloud\vision_helpers\decorators.py", line 101, in inner
    response = self.annotate_image(request, retry=retry, timeout=timeout)
  File "C:\Users\Nick\AppData\Local\Programs\Python\Python36\lib\site-packages\google\cloud\vision_helpers\__init__.py", line 72, in annotate_image
    r = self.batch_annotate_images([request], retry=retry, timeout=timeout)
  File "C:\Users\Nick\AppData\Local\Programs\Python\Python36\lib\site-packages\google\cloud\vision_v1\gapic\image_annotator_client.py", line 234, in batch_annotate_images
    request, retry=retry, timeout=timeout, metadata=metadata
  File "C:\Users\Nick\AppData\Local\Programs\Python\Python36\lib\site-packages\google\api_core\gapic_v1\method.py", line 143, in __call__
    return wrapped_func(*args, **kwargs)
  File "C:\Users\Nick\AppData\Local\Programs\Python\Python36\lib\site-packages\google\api_core\grpc_helpers.py", line 59, in error_remapped_callable
    six.raise_from(exceptions.from_grpc_error(exc), exc)
  File "<string>", line 3, in raise_from
google.api_core.exceptions.ServiceUnavailable: 503 Getting metadata from plugin failed with error: ('invalid_grant: Invalid JWT: Token must be a short-lived token (60 minutes) and in a reasonable timeframe. Check your iat and exp values and use a clock with skew to account for clock differences between systems.', '{\n  "error": "invalid_grant",\n  "error_description": "Invalid JWT: Token must be a short-lived token (60 minutes) and in a reasonable timeframe. Check your iat and exp values and use a clock with skew to account for clock differences between systems."\n}')
[Finished in 1.6s]

Could someone help me with this issue? This is my first time using Google Cloud Vision.

Answer 1

According to this post, you will get this error when your computer clock is not in sync with the google server clock. Just put your computer clock in sync with the google server clock, and your problem is solved.