Perform Foundational Data, ML, and AI Tasks in Google Cloud: Challenge Lab

 # TO GET LAB SCHEMA:

gsutil cp gs://cloud-training/gsp323/lab.csv .

cat lab.csv

gsutil cp gs://cloud-training/gsp323/lab.schema .

cat lab.schema

# TASK 4 - PART 1 - CLOUD NATURAL LANGUAGE:

gcloud iam service-accounts create my-natlang-sa \

  --display-name "my natural language service account"

gcloud iam service-accounts keys create ~/key.json \

  --iam-account my-natlang-sa@${GOOGLE_CLOUD_PROJECT}.iam.gserviceaccount.com

export GOOGLE_APPLICATION_CREDENTIALS="/home/$USER/key.json"

gcloud auth activate-service-account my-natlang-sa@${GOOGLE_CLOUD_PROJECT}.iam.gserviceaccount.com --key-file=$GOOGLE_APPLICATION_CREDENTIALS

gcloud ml language analyze-entities --content="Old Norse texts portray Odin as one-eyed and long-bearded, frequently wielding a spear named Gungnir and wearing a cloak and a broad hat." > result.json

gcloud auth login 

(Copy the token from the link provided)

gsutil cp result.json gs://YOUR_PROJECT-marking/task4-cnl.result

# TASK 4 - PART 2 - CLOUD SPEECH:

# CREATE AN API KEY AND EXPORT AS "API_KEY" VARIABLE IN CLOUD SHELL THEN CREATE THE FOLLOWING JSON

nano request.json

{

  "config": {

      "encoding":"FLAC",

      "languageCode": "en-US"

  },

  "audio": {

      "uri":"gs://cloud-training/gsp323/task4.flac"

  }

}

curl -s -X POST -H "Content-Type: application/json" --data-binary @request.json \

"https://speech.googleapis.com/v1/speech:recognize?key=${API_KEY}" > result.json

gsutil cp result.json gs://YOUR_PROJECT-marking/task4-gcs.result

# TASK 4 - PART 3 - VIDEO INTELLIGENCE:

gcloud iam service-accounts create quickstart

gcloud iam service-accounts keys create key.json --iam-account quickstart@${GOOGLE_CLOUD_PROJECT}.iam.gserviceaccount.com

gcloud auth activate-service-account --key-file key.json

export ACCESS_TOKEN=$(gcloud auth print-access-token)

nano request.json

{

   "inputUri":"gs://spls/gsp154/video/chicago.mp4",

   "features": [

       "TEXT_DETECTION"

   ]

}

curl -s -H 'Content-Type: application/json' \

    -H "Authorization: Bearer $ACCESS_TOKEN" \

    'https://videointelligence.googleapis.com/v1/videos:annotate' \

    -d @request.json

curl -s -H 'Content-Type: application/json' -H "Authorization: Bearer $ACCESS_TOKEN" 'https://videointelligence.googleapis.com/v1/operations/OPERATION_FROM_PREVIOUS_REQUEST' > result1.json

gsutil cp result1.json gs://YOUR_PROJECT-marking/task4-gvi.result

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