| | |
| | | import argparse |
| | | import logging |
| | | import os |
| | | import sys |
| | | import json |
| | | from pathlib import Path |
| | |
| | | # do vad segment |
| | | _, results = speech2vadsegment(**batch) |
| | | for i, _ in enumerate(keys): |
| | | # results[i] = json.dumps(results[i]) |
| | | if "MODELSCOPE_ENVIRONMENT" in os.environ and os.environ["MODELSCOPE_ENVIRONMENT"] == "eas": |
| | | results[i] = json.dumps(results[i]) |
| | | item = {'key': keys[i], 'value': results[i]} |
| | | vad_results.append(item) |
| | | if writer is not None: |
| | |
| | | import argparse |
| | | import logging |
| | | import os |
| | | import sys |
| | | import json |
| | | from pathlib import Path |
| | |
| | | if results: |
| | | for i, _ in enumerate(keys): |
| | | if results[i]: |
| | | # results[i] = json.dumps(results[i]) |
| | | if "MODELSCOPE_ENVIRONMENT" in os.environ and os.environ["MODELSCOPE_ENVIRONMENT"] == "eas": |
| | | results[i] = json.dumps(results[i]) |
| | | item = {'key': keys[i], 'value': results[i]} |
| | | vad_results.append(item) |
| | | if writer is not None: |