spacje

src/reco.py

@@ -8,35 +8,42 @@ from mongo.helpers import get_mongo_collection
 import datetime
 import time
 import concurrent.futures
+import logging
 
 
 def main(args):
-    mongoUri = "mongodb://speechRecoUser:speech!reco@localhost/archSpeechReco"
-    dbName = "archSpeechReco"
-    colName = "moviesMeta"
+    loglevel = args.loglevel
+    numeric_level = getattr(logging, loglevel.upper(), 10)
+    logging.basicConfig(filename='reco.log', format='%(asctime)s [%(levelname)s] - %(message)s', level=numeric_level)
+
+    mongo_uri = "mongodb://speechRecoUser:speech!reco@localhost/archSpeechReco"
+    db_name = "archSpeechReco"
+    col_name = "moviesMeta"
     global col
-    col = get_mongo_collection(colName, dbName, mongoUri)
+    col = get_mongo_collection(col_name, db_name, mongo_uri)
     batch_size = int(args.batch_size)
-    waves = getWavList(col, batch_size)
+    source = args.source
+    channels = args.channels
+    waves = get_wav_list(col, batch_size, source)
     uris = [w for w in waves]
-    print(uris)
+    uris = list(map(lambda x: dict(x, **{'channels': channels}), uris))
 
     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')
+    logging.info(f'Finished in {round(stop - start, 2)} seconds')
 
 
 def run_reco(uri):
-    reco = recognize(uri['gcsWawLocation'])
-    recoDict = MessageToDict(reco)
+    reco = recognize(uri['gcsWawLocation'], uri['channels'])
+    reco_dict = 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:
+    if len(reco_dict) != 0:
+        words = reco_dict["results"][-1]["alternatives"][0]["words"]
+        transcript = " ".join([trans["alternatives"][0]["transcript"] for trans in reco_dict["results"][:-1]])
+    elif len(reco_dict) == 0:
         words = {}
         transcript = "film niemy"
 
@@ -49,12 +56,13 @@ def run_reco(uri):
                       "gcTextReco.transcripted": now.strftime("%Y-%m-%d %H:%M:%S")}}
         )
     except Exception as e:
-        print(e)
+        logging.error(e)
     else:
-        print(f"mongo update OK {uri.split('/')[4].split('.')[0]}")
+        logging.info(f"mongo update OK {uri['_id']}")
+        logging.debug(f"transcript for {uri['gcsWawLocation']}: {transcript}")
 
 
-def recognize(storage_uri):
+def recognize(storage_uri, channels):
     """
     Transcribe long audio file from Cloud Storage using asynchronous speech
     recognition
@@ -73,50 +81,50 @@ def recognize(storage_uri):
         sample_rate_hertz=44100,
         language_code="pl-PL",
         diarization_config=d_config,
-        audio_channel_count=2
+        audio_channel_count=channels
     )
 
     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...")
+    logging.info(f'{storage_uri} has been sent to reco')
+    logging.info(u"Waiting for operation to complete...")
     response = operation.result()
 
     return response
 
 
-def getMongoCollection(colName, dbName, uri):
+def get_mongo_collection(col_name, db_name, uri):
     client = MongoClient(uri, maxPoolSize=512)
-    db = client[dbName]
-    col = db[colName]
+    db = client[db_name]
+    col = db[col_name]
 
     return col
 
 
-def getWavList(col, limit=32):
-    pipeline = []
-    # match phase, filter documents without gcTextReco field - voice not recognized
-    pipeline.append({"$match": {"$and": [
+def get_wav_list(col, source, limit=32):
+    pipeline = [{"$match": {"$and": [
+        {"source": source},
         {"gcTextReco": {"$exists": False}},
         {"gcsWav": {"$exists": True}},
         {"description.details.Format dźwięku": {"$ne": "brak"}}
     ]}
-    }
-    )
-    # project phase, show only bucket name: gcsWav.location
-    pipeline.append({"$project": {
+    }, {"$project": {
         "_id": 1,
         "gcsWawLocation": {"$concat": ["gs://archspeechreco/", "$gcsWav.location"]}
     }
-    })
+    }, {"$limit": limit}]
+    # match phase, filter documents without gcTextReco field - voice not recognized
+    # project phase, show only bucket name: 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("--batch_size", default=512, help="how many waves in the batch")
+    parser.add_argument("--source", help="source of media [dtv, filmoteka, kronikiprl, sonda]")
+    parser.add_argument("--channels", help="quantity of audio channels")
+    parser.add_argument("--loglevel", help="log level: DEBUG INFO WARNING ERROR")
     args = parser.parse_args()
     main(args)