File size: 6,585 Bytes
3afd6d6 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 | import importlib.util
import sys
import types
from pathlib import Path
class _Port:
def __init__(self, name=None, **kwargs):
self.name = name
self.kwargs = kwargs
class _PortType:
@staticmethod
def Input(name, **kwargs):
return _Port(name, **kwargs)
@staticmethod
def Output(name=None, **kwargs):
return _Port(name, **kwargs)
class _NodeOutput:
def __init__(self, *values):
self.values = values
class _Schema:
def __init__(self, **kwargs):
self.__dict__.update(kwargs)
def _load_node_module():
io = types.SimpleNamespace(
Audio=_PortType,
Boolean=_PortType,
Combo=_PortType,
ComfyNode=object,
Int=_PortType,
NodeOutput=_NodeOutput,
Schema=_Schema,
String=_PortType,
Video=_PortType,
)
comfy_api = types.ModuleType("comfy_api")
comfy_api_latest = types.ModuleType("comfy_api.latest")
comfy_api_latest.io = io
comfy_api_latest.Types = types.SimpleNamespace(
VideoContainer=types.SimpleNamespace(AUTO="auto"),
VideoCodec=types.SimpleNamespace(AUTO="auto"),
)
comfy_api.latest = comfy_api_latest
package = types.ModuleType("easy_media")
package.__path__ = []
nodes_package = types.ModuleType("easy_media.nodes")
nodes_package.__path__ = []
modules_package = types.ModuleType("easy_media.modules")
modules_package.__path__ = []
asr_package = types.ModuleType("easy_media.modules.asr")
asr_package.__path__ = []
recognition_module = types.ModuleType("easy_media.modules.asr.subtitle_recognition")
recognition_module.SUBTITLE_RECOGNITION_METHODS = ["qwen3-asr", "whisper-large-v3"]
recognition_module.recognize_audio_subtitles = lambda *args: []
utils_module = types.ModuleType("easy_media.utils")
utils_module.extract_video_audio_to_temp = lambda *args, **kwargs: None
utils_module.save_audio_to_temp_wav = lambda *args, **kwargs: None
utils_module.subtitle_segments_to_srt = lambda segments: ""
utils_module.subtitle_segments_to_timestamp_text = lambda segments: ""
utils_module.video_input_to_local_file = lambda *args, **kwargs: ("", [])
sys.modules.update({
"comfy_api": comfy_api,
"comfy_api.latest": comfy_api_latest,
"easy_media": package,
"easy_media.nodes": nodes_package,
"easy_media.modules": modules_package,
"easy_media.modules.asr": asr_package,
"easy_media.modules.asr.subtitle_recognition": recognition_module,
"easy_media.utils": utils_module,
})
path = Path(__file__).parents[1] / "nodes" / "subtitle.py"
spec = importlib.util.spec_from_file_location("easy_media.nodes.subtitle", path)
module = importlib.util.module_from_spec(spec)
sys.modules[spec.name] = module
spec.loader.exec_module(module)
return module
def test_recognize_subtitle_schema_supports_two_models_and_audio_or_video():
module = _load_node_module()
schema = module.RecognizeSubtitle.define_schema()
assert schema.node_id == "easy recognizeSubtitle"
assert [item.name for item in schema.inputs] == [
"audio",
"video",
"model_type",
"output_format",
"max_sentence_length",
"unload_model",
]
assert schema.inputs[0].kwargs["optional"] is True
assert schema.inputs[1].kwargs["optional"] is True
assert schema.inputs[2].kwargs["options"] == ["qwen3-asr", "whisper-large-v3"]
assert schema.inputs[3].kwargs["options"] == ["srt", "timestamp"]
assert schema.inputs[4].kwargs["default"] == 20
assert schema.inputs[5].kwargs["default"] is True
assert [item.name for item in schema.outputs] == ["SUBTITLE_TEXT"]
def test_recognize_subtitle_uses_audio_and_returns_srt(monkeypatch, tmp_path):
module = _load_node_module()
audio_path = tmp_path / "audio.wav"
audio_path.write_bytes(b"wav")
calls = {}
monkeypatch.setattr(module, "save_audio_to_temp_wav", lambda audio: audio_path)
def fake_recognize(path, model, max_sentence_length, unload_model):
calls["recognize"] = (path, model, max_sentence_length, unload_model)
return [{"start": 0.0, "end": 1.0, "text": "hello"}]
monkeypatch.setattr(module, "recognize_audio_subtitles", fake_recognize)
monkeypatch.setattr(
module,
"subtitle_segments_to_srt",
lambda segments: "1\n00:00:00,000 --> 00:00:01,000\nhello\n",
)
result = module.RecognizeSubtitle.execute(
{"waveform": object(), "sample_rate": 16000},
None,
"whisper-large-v3",
"srt",
24,
False,
)
assert calls["recognize"] == (audio_path, "whisper-large-v3", 24, False)
assert result.values == ("1\n00:00:00,000 --> 00:00:01,000\nhello\n",)
assert not audio_path.exists()
def test_recognize_subtitle_extracts_video_audio_and_cleans_temp_files(monkeypatch, tmp_path):
module = _load_node_module()
video_path = tmp_path / "video.mp4"
copied_video_path = tmp_path / "copied.mp4"
audio_path = tmp_path / "audio.wav"
copied_video_path.write_bytes(b"video")
audio_path.write_bytes(b"wav")
monkeypatch.setattr(
module,
"video_input_to_local_file",
lambda video, **kwargs: (str(video_path), [str(copied_video_path)]),
)
monkeypatch.setattr(module, "extract_video_audio_to_temp", lambda path: audio_path)
monkeypatch.setattr(module, "recognize_audio_subtitles", lambda path, model, maximum, unload: [])
result = module.RecognizeSubtitle.execute(None, object(), "qwen3-asr", "srt", 48, True)
assert result.values == ("",)
assert not copied_video_path.exists()
assert not audio_path.exists()
def test_recognize_subtitle_returns_timestamp_format(monkeypatch, tmp_path):
module = _load_node_module()
audio_path = tmp_path / "audio.wav"
audio_path.write_bytes(b"wav")
monkeypatch.setattr(module, "save_audio_to_temp_wav", lambda audio: audio_path)
monkeypatch.setattr(
module,
"recognize_audio_subtitles",
lambda path, model, maximum, unload: [{"start": 0.42, "end": 1.4, "text": "hello"}],
)
monkeypatch.setattr(
module,
"subtitle_segments_to_timestamp_text",
lambda segments: "(0.42, 1.4) hello",
)
result = module.RecognizeSubtitle.execute(
{"waveform": object(), "sample_rate": 16000},
None,
"qwen3-asr",
"timestamp",
48,
True,
)
assert result.values == ("(0.42, 1.4) hello",)
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