generate_tags.py

################################################################################
## Set up Personal Access Token and Access information
##     - This will be used by every Clarifai API call 
################################################################################
## Specify the Authorization key.  This should be changed to your Personal Access Token.
## Example: metadata = (('authorization', 'Key 123457612345678'),) 
##
## A UserAppIDSet object is needed for most rpc calls.  This object contains
## two pieces of information: the user id and the app id.  Both of these are
## specified as string values.
##
##     'user_id' : This is your user id
##     'app_id'  : This is the app id which contains the model of interest
# end of first trial

###################################################################################
# In this section, we set the user authentication, app and model IDs, and the URL
# of the image we want as an input. Change these strings to run your own example.
###################################################################################
import os
import pickle
USER_ID = "you should type your USER_ID"
# Your PAT (Personal Access Token) can be found in the portal under Authentification
PAT = "you should type your PAT"
APP_ID = "you should type your APP_ID"
# MODEL_ID = 'general-image-recognition'
MODEL_ID = "you should type your MODEL_ID"
# Change this to whatever image URL you want to process
# IMAGE_URL = 'https://samples.clarifai.com/metro-north.jpg'
IMAGE_FILE_LOCATION = '/Users/brain/Downloads/metro-north.jpeg'
# This is optional. You can specify a model version or the empty string for the default
MODEL_VERSION_ID = ''

############################################################################
# YOU DO NOT NEED TO CHANGE ANYTHING BELOW THIS LINE TO RUN THIS EXAMPLE
############################################################################

from clarifai_grpc.channel.clarifai_channel import ClarifaiChannel
from clarifai_grpc.grpc.api import resources_pb2, service_pb2, service_pb2_grpc
from clarifai_grpc.grpc.api.status import status_code_pb2

channel = ClarifaiChannel.get_grpc_channel()
stub = service_pb2_grpc.V2Stub(channel)

metadata = (('authorization', 'Key ' + PAT),)

userDataObject = resources_pb2.UserAppIDSet(user_id=USER_ID, app_id=APP_ID)

with open(IMAGE_FILE_LOCATION, "rb") as f:
    file_bytes = f.read()

post_model_outputs_response = stub.PostModelOutputs(
    service_pb2.PostModelOutputsRequest(
        user_app_id=userDataObject,  # The userDataObject is created in the overview and is required when using a PAT
        model_id=MODEL_ID,
        version_id=MODEL_VERSION_ID,  # This is optional. Defaults to the latest model version
        inputs=[
            resources_pb2.Input(
                data=resources_pb2.Data(
                    image=resources_pb2.Image(
                        base64=file_bytes
                    )
                )
            )
        ]
    ),
    metadata=metadata
)
if post_model_outputs_response.status.code != status_code_pb2.SUCCESS:
    print(post_model_outputs_response.status)
    raise Exception("Post model outputs failed, status: " + post_model_outputs_response.status.description)

# Since we have one input, one output will exist here
output = post_model_outputs_response.outputs[0]

# f = open('/Users/brain/Downloads/single_output.csv', 'w')
print("Predicted concepts:")
for concept in output.data.concepts:
    print(concept)
    # print("%s:%.2f" % (concept.name, concept.value))