ver0.1

.gitignore

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+__pycache__

Dockerfile

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+# read the doc: https://huggingface.co/docs/hub/spaces-sdks-docker
+# you will also find guides on how best to write your Dockerfile
+
+FROM python:3.11
+
+WORKDIR /code
+
+RUN apt-get update && apt-get install -y \
+    ffmpeg 
+
+COPY ./requirements.txt /code/requirements.txt
+
+RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
+
+COPY . .
+
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

app.py

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+import gradio as gr
+import os
+import zipfile
+import tempfile
+import subprocess
+from transformers import pipeline
+import torch
+from zipfile import ZipFile
+
+from fastapi import FastAPI
+
+app = FastAPI()
+
+device = "cuda:0" if torch.cuda.is_available() else "cpu"
+
+model_id = "openai/whisper-medium.en"
+
+pipe = pipeline(
+    "automatic-speech-recognition",
+    model=model_id,
+    chunk_length_s=30,
+    device=device,
+)
+
+
+def support_gbk(zip_file: ZipFile):
+    name_to_info = zip_file.NameToInfo
+    # copy map first
+    for name, info in name_to_info.copy().items():
+        real_name = name.encode("cp437").decode("gbk")
+        if real_name != name:
+            info.filename = real_name
+            del name_to_info[name]
+            name_to_info[real_name] = info
+    return zip_file
+
+
+def handel(f):
+    if not f:
+        raise gr.Error("请上传文件")
+    if f.name.endswith(".zip"):
+        with support_gbk(ZipFile(f.name, "r")) as z:
+            dir = tempfile.TemporaryDirectory()
+            z.extractall(path=dir.name)
+            return handel_files(
+                [
+                    os.path.join(filepath, filename)
+                    for filepath, _, filenames in os.walk(dir.name)
+                    for filename in filenames
+                ]
+            )
+    else:
+        return handel_files([f.name])
+
+
+def ffmpeg_convert(file_input, file_output):
+    if subprocess.run(["ffmpeg", "-y", "-i", file_input, file_output]).returncode:
+        raise gr.Error("ffmpeg_convert 失败, 请检查文件格式是否正确")
+
+
+def handel_files(f_ls):
+    files = []
+    for file in f_ls:
+        if file.endswith(".m4a"):
+            file_output = file.replace(".m4a", ".wav")
+            ffmpeg_convert(file, file_output)
+        elif file.endswith(".mp3"):
+            file_output = file.replace(".mp3", ".wav")
+            ffmpeg_convert(file, file_output)
+        elif file.endswith(".wav"):
+            file_output = file
+            ffmpeg_convert(file, file_output)
+        else:
+            gr.Warning(f"存在不合法文件{file_name},已跳过处理")
+        files.append(file_output)
+    ret = []
+    for file in files:
+        ret.append(whisper_handler(file))
+
+    return "\n\n".join(ret)
+
+
+def whisper_handler(file):
+    file_name = os.path.basename(file)
+    gr.Info(f"处理文件 - {file_name}")
+    return pipe(file)["text"]
+
+
+with gr.Blocks() as blocks:
+    f = gr.File(file_types=[".zip", ".mp3", ".wav", ".m4a"])
+    b = gr.Button(value="提交")
+    t = gr.Textbox(label="结果")
+
+    b.click(handel, inputs=f, outputs=t)
+
+app = gr.mount_gradio_app(app, blocks, path="/")

requirements.txt

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+gradio
+transformers
+torch
+fastapi
+uvicorn[standard]