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Parent(s):
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Browse files- app.py +30 -48
- requirements.txt +3 -3
- utils.py +4 -10
app.py
CHANGED
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@@ -18,25 +18,25 @@ from PIL import Image
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TRANSLATE = {
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"Symphony": "
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"Opera": "
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"Solo": "
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"Chamber": "
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"Pop_vocal_ballad": "
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"Adult_contemporary": "
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"Teen_pop": "
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"Contemporary_dance_pop": "
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"Dance_pop": "
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"Classic_indie_pop": "
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"Chamber_cabaret_and_art_pop": "
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"Soul_or_r_and_b": "
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"Adult_alternative_rock": "
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"Uplifting_anthemic_rock": "
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"Soft_rock": "
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"Acoustic_pop": "
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}
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-
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CLASSES = list(TRANSLATE.keys())
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def most_common_element(input_list):
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@@ -46,7 +46,7 @@ def most_common_element(input_list):
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def mp3_to_mel(audio_path: str, width=11.4):
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os.makedirs(
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try:
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y, sr = librosa.load(audio_path)
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mel_spec = librosa.feature.melspectrogram(y=y, sr=sr)
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@@ -61,7 +61,7 @@ def mp3_to_mel(audio_path: str, width=11.4):
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librosa.display.specshow(log_mel_spec[:, i : i + step])
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plt.axis("off")
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plt.savefig(
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f"
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bbox_inches="tight",
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pad_inches=0.0,
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)
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@@ -72,7 +72,7 @@ def mp3_to_mel(audio_path: str, width=11.4):
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def mp3_to_cqt(audio_path: str, width=11.4):
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os.makedirs(
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try:
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y, sr = librosa.load(audio_path)
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cqt_spec = librosa.cqt(y=y, sr=sr)
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@@ -87,7 +87,7 @@ def mp3_to_cqt(audio_path: str, width=11.4):
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librosa.display.specshow(log_cqt_spec[:, i : i + step])
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plt.axis("off")
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plt.savefig(
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f"
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bbox_inches="tight",
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pad_inches=0.0,
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)
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@@ -98,7 +98,7 @@ def mp3_to_cqt(audio_path: str, width=11.4):
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def mp3_to_chroma(audio_path: str, width=11.4):
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os.makedirs(
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try:
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y, sr = librosa.load(audio_path)
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chroma_spec = librosa.feature.chroma_stft(y=y, sr=sr)
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@@ -113,7 +113,7 @@ def mp3_to_chroma(audio_path: str, width=11.4):
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librosa.display.specshow(log_chroma_spec[:, i : i + step])
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plt.axis("off")
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plt.savefig(
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f"
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bbox_inches="tight",
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pad_inches=0.0,
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)
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@@ -135,12 +135,12 @@ def embed_img(img_path, input_size=224):
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return transform(img).unsqueeze(0)
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def inference(mp3_path, log_name: str, folder_path=
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if os.path.exists(folder_path):
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shutil.rmtree(folder_path)
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if not mp3_path:
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return None, "
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network = EvalNet(log_name)
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spec = log_name.split("_")[-1]
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@@ -186,35 +186,17 @@ if __name__ == "__main__":
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gr.Interface(
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fn=inference,
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inputs=[
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gr.Audio(label="
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gr.Dropdown(
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choices=models, label="选择模型 Select a model", value=models[6]
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),
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],
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outputs=[
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gr.Textbox(label="
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gr.Textbox(label="
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],
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examples=examples,
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cache_examples=False,
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allow_flagging="never",
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title="
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)
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gr.Markdown(
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"""
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# 引用 Cite
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```bibtex
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@dataset{zhaorui_liu_2021_5676893,
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author = {Monan Zhou, Shenyang Xu, Zhaorui Liu, Zhaowen Wang, Feng Yu, Wei Li and Baoqiang Han},
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title = {CCMusic: an Open and Diverse Database for Chinese and General Music Information Retrieval Research},
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month = {mar},
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year = {2024},
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publisher = {HuggingFace},
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version = {1.2},
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url = {https://huggingface.co/ccmusic-database}
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}
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```"""
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)
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demo.launch()
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TRANSLATE = {
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"Symphony": "Symphony",
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"Opera": "Opera",
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"Solo": "Solo",
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"Chamber": "Chamber",
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"Pop_vocal_ballad": "Pop vocal ballad",
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"Adult_contemporary": "Adult contemporary",
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"Teen_pop": "Teen pop",
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"Contemporary_dance_pop": "Contemporary dance pop",
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"Dance_pop": "Dance pop",
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"Classic_indie_pop": "Classic indie pop",
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"Chamber_cabaret_and_art_pop": "Chamber cabaret & art pop",
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"Soul_or_r_and_b": "Soul / R&B",
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"Adult_alternative_rock": "Adult alternative rock",
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"Uplifting_anthemic_rock": "Uplifting anthemic rock",
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"Soft_rock": "Soft rock",
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"Acoustic_pop": "Acoustic pop",
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}
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CLASSES = list(TRANSLATE.keys())
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CACHE_DIR = "__pycache__"
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def most_common_element(input_list):
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def mp3_to_mel(audio_path: str, width=11.4):
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os.makedirs(CACHE_DIR, exist_ok=True)
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try:
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y, sr = librosa.load(audio_path)
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mel_spec = librosa.feature.melspectrogram(y=y, sr=sr)
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librosa.display.specshow(log_mel_spec[:, i : i + step])
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plt.axis("off")
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plt.savefig(
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f"{CACHE_DIR}/mel_{round(dur, 2)}_{i}.jpg",
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bbox_inches="tight",
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pad_inches=0.0,
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)
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def mp3_to_cqt(audio_path: str, width=11.4):
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os.makedirs(CACHE_DIR, exist_ok=True)
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try:
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y, sr = librosa.load(audio_path)
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cqt_spec = librosa.cqt(y=y, sr=sr)
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librosa.display.specshow(log_cqt_spec[:, i : i + step])
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plt.axis("off")
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plt.savefig(
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f"{CACHE_DIR}/cqt_{round(dur, 2)}_{i}.jpg",
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bbox_inches="tight",
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pad_inches=0.0,
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)
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def mp3_to_chroma(audio_path: str, width=11.4):
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os.makedirs(CACHE_DIR, exist_ok=True)
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try:
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y, sr = librosa.load(audio_path)
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chroma_spec = librosa.feature.chroma_stft(y=y, sr=sr)
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librosa.display.specshow(log_chroma_spec[:, i : i + step])
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plt.axis("off")
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plt.savefig(
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f"{CACHE_DIR}/chroma_{round(dur, 2)}_{i}.jpg",
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bbox_inches="tight",
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pad_inches=0.0,
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)
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return transform(img).unsqueeze(0)
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def inference(mp3_path, log_name: str, folder_path=CACHE_DIR):
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if os.path.exists(folder_path):
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shutil.rmtree(folder_path)
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if not mp3_path:
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return None, "Please input an audio!"
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network = EvalNet(log_name)
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spec = log_name.split("_")[-1]
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gr.Interface(
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fn=inference,
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inputs=[
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gr.Audio(label="Upload MP3", type="filepath"),
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gr.Dropdown(choices=models, label="Select a model", value=models[6]),
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],
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outputs=[
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gr.Textbox(label="Audio filename", show_copy_button=True),
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gr.Textbox(label="Genre recognition", show_copy_button=True),
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],
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examples=examples,
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cache_examples=False,
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allow_flagging="never",
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title="It is recommended to keep the duration of recording within 15s, too long will affect the recognition efficiency.",
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)
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demo.launch()
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requirements.txt
CHANGED
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@@ -1,6 +1,6 @@
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librosa
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torch
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matplotlib
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torchvision
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modelscope==1.15
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torch
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pillow
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librosa
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matplotlib
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torchvision
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modelscope[framework]==1.18
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utils.py
CHANGED
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@@ -32,23 +32,17 @@ def get_modelist(model_dir=MODEL_DIR):
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try:
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entries = os.listdir(model_dir)
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except OSError as e:
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print(f"
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return
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# 遍历所有条目
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output = []
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for entry in entries:
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# 获取完整路径
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full_path = os.path.join(model_dir, entry)
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# 跳过'.git'文件夹
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if entry == ".git" or entry == "examples":
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print(f"
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continue
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# 检查条目是文件还是目录
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if os.path.isdir(full_path):
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# 打印目录路径
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output.append(os.path.basename(full_path))
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return output
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@@ -62,6 +56,6 @@ def download(url: str):
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for chunk in response.iter_content(chunk_size=8192):
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f.write(chunk)
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print(f"
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else:
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print(f"
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try:
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entries = os.listdir(model_dir)
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except OSError as e:
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print(f"Cannot access {model_dir}: {e}")
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return
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output = []
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for entry in entries:
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full_path = os.path.join(model_dir, entry)
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if entry == ".git" or entry == "examples":
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print(f"Skip .git / examples dir: {full_path}")
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continue
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if os.path.isdir(full_path):
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output.append(os.path.basename(full_path))
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return output
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for chunk in response.iter_content(chunk_size=8192):
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f.write(chunk)
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print(f"The file has been downloaded to {os.getcwd()}/{filename}")
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else:
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print(f"Failed to download, status code: {response.status_code}")
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