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solved path issues

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This commit is contained in:
Jaikinator
2023-06-30 18:41:43 +02:00
parent 11fce3abef
commit cd35ad8903
1 changed files with 23 additions and 26 deletions
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autotranscript/misc.py
+23 -26
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@@ -1,4 +1,3 @@
from pyannote.audio import Pipeline
from whisper import Whisper, load_model
import os
@@ -6,15 +5,18 @@ import glob
from warnings import warn
import yaml
WHISPER_DEFAULT_PATH = os.path.relpath(os.path.join(os.path.dirname(__file__),
"models", "whisper"))
CACHE_DIR = os.getenv(
"AUTOT_CACHE",
os.path.expanduser("~/.cache/torch/models"),
)
PYANNOTE_DEFAULT_PATH = os.path.relpath(os.path.join(os.path.dirname(__file__),
"models", "pyannote",
"speaker_diarization", "config.yaml"))
WHISPER_DEFAULT_PATH = os.path.join(CACHE_DIR, "whisper")
PYANNOTE_DEFAULT_PATH = os.path.join(CACHE_DIR, "pyannote")
def config_diarization_yaml(file, path_to_segmentation = None, path_to_embedding = None):
PYANNOTE_DEFAULT_CONFIG = os.path.join(PYANNOTE_DEFAULT_PATH, "config.yaml")
def config_diarization_yaml(file, path_to_segmentation = None):
"""
Configure diarization pipeline from yaml file to use the model offline
and avoid manuel file manipulation.
@@ -28,30 +30,25 @@ def config_diarization_yaml(file, path_to_segmentation = None, path_to_embedding
if path_to_segmentation:
yml["pipeline"]["params"]["segmentation"] = path_to_segmentation
else:
yml["pipeline"]["params"]["segmentation"] = os.path.relpath(os.path.join(
os.path.dirname(__file__),
"models", "pyannote",
"segmentation",
"pytorch_model.bin"))
yml["pipeline"]["params"]["segmentation"] = os.path.join(PYANNOTE_DEFAULT_PATH, "pytorch_model.bin")
if path_to_embedding:
yml["pipeline"]["params"]["embedding"] = path_to_embedding
else:
yml["pipeline"]["params"]["embedding"] = os.path.relpath(
os.path.join(
os.path.dirname(__file__),
"models", "pyannote",
"speechbrain",
"spkrec-ecapa-voxceleb",
"embedding_model.ckpt"))
# if path_to_embedding:
# yml["pipeline"]["params"]["embedding"] = path_to_embedding
# else:
# yml["pipeline"]["params"]["embedding"] = os.path.relpath(
# os.path.join(
# os.path.dirname(__file__),
# "models", "pyannote",
# "speechbrain",
# "spkrec-ecapa-voxceleb",
# "embedding_model.ckpt"))
if not os.path.exists(yml["pipeline"]["params"]["segmentation"]):
raise FileNotFoundError(f"Segmentation model not found at {yml['pipeline']['params']['segmentation']}")
if not os.path.exists(yml["pipeline"]["params"]["embedding"]):
raise FileNotFoundError(f"Embedding model not found at {yml['pipeline']['params']['embedding']}")
# if not os.path.exists(yml["pipeline"]["params"]["embedding"]):
# raise FileNotFoundError(f"Embedding model not found at {yml['pipeline']['params']['embedding']}")
with open(file, "w") as stream:
yaml.dump(yml, stream)
stream.close()
stream.close()