transcript in threadpool #2

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s333949 merged 1 commits from reco into master 2020-02-22 12:48:19 +01:00
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@ -9,32 +9,52 @@ from google.protobuf.json_format import MessageToJson,MessageToDict
from storageUpload import getMongoCollection
from bson.objectid import ObjectId
import datetime
import time
import concurrent.futures
import re
def main(args):
uri = "gs://archspeechreco/wave/5df3e63d4c0402698d7837f3.wav"
reco = recognize(uri)
recoDict = MessageToDict(reco)
#print(json.dumps(transcript,indent=4,ensure_ascii=False))
words = recoDict["results"][-1]["alternatives"][0]["words"]
transcript = "".join( [ trans["alternatives"][0]["transcript"] for trans in recoDict["results"][:-1] ] )
mongoUri = "mongodb://speechRecoUser:speech!reco@localhost/archSpeechReco"
dbName = "archSpeechReco"
colName = "moviesMeta"
col = getMongoCollection(colName,dbName,mongoUri)
global col
col = getMongoCollection(colName,dbName,mongoUri)
batch_size = int(args.batch_size)
waves = getWavList(col,batch_size)
uris = [ w['gcsWawLocation'] for w in waves ]
start = time.perf_counter()
with concurrent.futures.ThreadPoolExecutor(max_workers=64) as executor:
executor.map(run_reco, uris)
stop = time.perf_counter()
print(f'Finished in {round(stop-start, 2)} seconds')
def run_reco(uri):
reco = recognize(uri)
recoDict = MessageToDict(reco)
if (len(recoDict) != 0):
words = recoDict["results"][-1]["alternatives"][0]["words"]
transcript = "".join( [ trans["alternatives"][0]["transcript"] for trans in recoDict["results"][:-1] ] )
elif (len(recoDict) == 0):
words = {}
transcript = "film niemy"
now = datetime.datetime.now()
try:
col.update_one(
{"_id": ObjectId("5df3e63d4c0402698d7837f3")},
{"_id": ObjectId(uri.split('/')[4].split('.')[0])},
{"$set":{"gcTextReco.transcript":transcript,
"gcTextReco.words":words,
"gcTextReco.transcripted":now.strftime("%Y-%m-%d %H:%M:%S")}}
)
except Exception as e: print(e)
else:
print("mongo update OK")
print(f"mongo update OK {uri.split('/')[4].split('.')[0]}")
def recognize(storage_uri):
"""
@ -78,18 +98,43 @@ def recognize(storage_uri):
audio = {"uri": storage_uri}
operation = client.long_running_recognize(config, audio)
print(f'{storage_uri} has been sent to reco')
print(u"Waiting for operation to complete...")
response = operation.result()
#for result in response.results:
# # First alternative is the most probable result
# alternative = result.alternatives[0]
# print(u"Transcript: {}".format(alternative.transcript))
return response
def getMongoCollection(colName,dbName,uri):
client = MongoClient(uri,maxPoolSize=512)
db = client[dbName]
col = db[colName]
return col
def getWavList(col,limit=32):
pipeline = []
#match phase, filetr documents withour gcTextReco field - voice not recognized
pipeline.append({"$match": {"$and":[
{"gcTextReco": {"$exists": False}},
{"gcsWav": {"$exists": True}},
{"description.details.Format dźwięku": {"$ne": "brak"}}
]}
}
)
#project phase, show only bucket name: gcsWav.location
pipeline.append({"$project": {
"gcsWawLocation": { "$concat": [ "gs://archspeechreco/","$gcsWav.location" ] }
}
})
#fetch only N documents
pipeline.append({"$limit":limit})
return col.aggregate(pipeline)
if __name__ == '__main__':
parser = argparse.ArgumentParser(description='Google Cloud speech2text API client')
parser.add_argument("--format", default='mp4', help="format to fetch and upload, [mp4, wav]")
args = parser.parse_args()
main(args)
parser = argparse.ArgumentParser(description='Google Cloud speech2text API client')
parser.add_argument("--batch_size", default=512, help="how many waves in the batch")
args = parser.parse_args()
main(args)