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Enhancement: Add Support for Loading Audio from Local Files or URLs #29

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Enhancement: Add Support for Loading Audio from Local Files or URLs #29

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72 changes: 53 additions & 19 deletions README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -96,19 +96,27 @@ conversation = [
]},
{"role": "assistant", "content": "Yes, the speaker is female and in her twenties."},
{"role": "user", "content": [
{"type": "audio", "audio_url": "https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen2-Audio/audio/translate_to_chinese.wav"},
{"type": "audio", "audio_file": "path/to/local/translate_to_chinese.wav"},
]},
]

text = processor.apply_chat_template(conversation, add_generation_prompt=True, tokenize=False)

audios = []
for message in conversation:
if isinstance(message["content"], list):
for ele in message["content"]:
if ele["type"] == "audio":
audios.append(librosa.load(
BytesIO(urlopen(ele['audio_url']).read()),
sr=processor.feature_extractor.sampling_rate)[0]
)
if "audio_url" in ele:
audios.append(librosa.load(
BytesIO(urlopen(ele['audio_url']).read()),
sr=processor.feature_extractor.sampling_rate)[0]
)
elif "audio_file" in ele:
audios.append(librosa.load(
ele['audio_file'],
sr=processor.feature_extractor.sampling_rate)[0]
)

inputs = processor(text=text, audios=audios, return_tensors="pt", padding=True)
inputs.input_ids = inputs.input_ids.to("cuda")
Expand All @@ -117,6 +125,8 @@ generate_ids = model.generate(**inputs, max_length=256)
generate_ids = generate_ids[:, inputs.input_ids.size(1):]

response = processor.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]

print(response)
```

##### Audio Analysis Inference
Expand All @@ -142,21 +152,30 @@ conversation = [
]},
{"role": "assistant", "content": "Stay alert and cautious, and check if anyone is hurt or if there is any damage to property."},
{"role": "user", "content": [
{"type": "audio", "audio_url": "https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen2-Audio/audio/1272-128104-0000.flac"},
{"type": "audio", "audio_file": "path/to/local/1272-128104-0000.flac"},
{"type": "text", "text": "What does the person say?"},
]},
]

text = processor.apply_chat_template(conversation, add_generation_prompt=True, tokenize=False)

audios = []
for message in conversation:
if isinstance(message["content"], list):
for ele in message["content"]:
if ele["type"] == "audio":
audios.append(
librosa.load(
BytesIO(urlopen(ele['audio_url']).read()),
sr=processor.feature_extractor.sampling_rate)[0]
)
if "audio_url" in ele:
audios.append(
librosa.load(
BytesIO(urlopen(ele['audio_url']).read()),
sr=processor.feature_extractor.sampling_rate)[0]
)
elif "audio_file" in ele:
audios.append(
librosa.load(
ele['audio_file'],
sr=processor.feature_extractor.sampling_rate)[0]
)

inputs = processor(text=text, audios=audios, return_tensors="pt", padding=True)
inputs.input_ids = inputs.input_ids.to("cuda")
Expand All @@ -165,6 +184,8 @@ generate_ids = model.generate(**inputs, max_length=256)
generate_ids = generate_ids[:, inputs.input_ids.size(1):]

response = processor.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]

print(response)
```

##### Batch Inference
Expand Down Expand Up @@ -192,7 +213,7 @@ conversation1 = [

conversation2 = [
{"role": "user", "content": [
{"type": "audio", "audio_url": "https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen2-Audio/audio/1272-128104-0000.flac"},
{"type": "audio", "audio_file": "path/to/local/1272-128104-0000.flac"},
{"type": "text", "text": "What does the person say?"},
]},
]
Expand All @@ -207,11 +228,19 @@ for conversation in conversations:
if isinstance(message["content"], list):
for ele in message["content"]:
if ele["type"] == "audio":
audios.append(
librosa.load(
BytesIO(urlopen(ele['audio_url']).read()),
sr=processor.feature_extractor.sampling_rate)[0]
)
if "audio_url" in ele:
audios.append(
librosa.load(
BytesIO(urlopen(ele['audio_url']).read()),
sr=processor.feature_extractor.sampling_rate)[0]
)
elif "audio_file" in ele:
audios.append(
librosa.load(
ele['audio_file'],
sr=processor.feature_extractor.sampling_rate)[0]
)


inputs = processor(text=text, audios=audios, return_tensors="pt", padding=True)
inputs['input_ids'] = inputs['input_ids'].to("cuda")
Expand All @@ -233,8 +262,13 @@ model = Qwen2AudioForConditionalGeneration.from_pretrained("Qwen/Qwen2-Audio-7B"
processor = AutoProcessor.from_pretrained("Qwen/Qwen2-Audio-7B" ,trust_remote_code=True)

prompt = "<|audio_bos|><|AUDIO|><|audio_eos|>Generate the caption in English:"
url = "https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Audio/glass-breaking-151256.mp3"
audio, sr = librosa.load(BytesIO(urlopen(url).read()), sr=processor.feature_extractor.sampling_rate)
audio_source = {"audio_url": "https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen-Audio/glass-breaking-151256.mp3"} # you can replace with local file path, eg: {"audio_file": "path/to/local/file.wav"}

if "audio_url" in audio_source:
audio, sr = librosa.load(BytesIO(urlopen(audio_source["audio_url"]).read()), sr=processor.feature_extractor.sampling_rate)
elif "audio_file" in audio_source:
audio, sr = librosa.load(audio_source["audio_file"], sr=processor.feature_extractor.sampling_rate)

inputs = processor(text=prompt, audios=audio, return_tensors="pt")

generated_ids = model.generate(**inputs, max_length=256)
Expand Down