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Browse files- Dockerfile +19 -21
- app.py +100 -0
- requirements.txt +80 -3
Dockerfile
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ENTRYPOINT ["streamlit", "run", "src/streamlit_app.py", "--server.port=8501", "--server.address=0.0.0.0"]
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# Use official Python slim image
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FROM python:3.10-slim
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# Set working directory
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WORKDIR /app
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# Copy requirements and install
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COPY requirements.txt .
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RUN pip install --upgrade pip
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RUN pip install -r requirements.txt
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# Copy app files
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COPY . .
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# Expose port Streamlit uses
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EXPOSE 8501
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# Run Streamlit app
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CMD ["streamlit", "run", "app.py", "--server.port=8501", "--server.address=0.0.0.0"]
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app.py
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import os
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import requests
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import tempfile
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import streamlit as st
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from moviepy.editor import VideoFileClip
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from speechbrain.inference.classifiers import EncoderClassifier
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st.set_page_config(page_title="Accent Classifier", page_icon="π£οΈ", layout="centered")
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# Custom CSS to change background color and style input box
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st.markdown(
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"""
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<style>
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.stApp {
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background-color: #f0f0f0;
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}
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input[type="text"] {
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background-color: white;
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color: black;
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border: 1px solid #ccc;
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padding: 0.5rem;
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border-radius: 5px;
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}
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.stTextInput > div > div > input {
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background-color: white !important;
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color: black !important;
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border: 1px solid #ccc !important;
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}
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</style>
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""",
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unsafe_allow_html=True
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)
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MODEL_ID = "Jzuluaga/accent-id-commonaccent_ecapa"
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def download_video(url, output_path):
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response = requests.get(url, stream=True)
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if response.status_code == 200:
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with open(output_path, "wb") as f:
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for chunk in response.iter_content(1024):
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f.write(chunk)
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if not os.path.exists(output_path) or os.path.getsize(output_path) < 1024:
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raise Exception("β Video download failed or file too small.")
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else:
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raise Exception("β Failed to download video.")
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def extract_audio(video_path, audio_path):
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clip = VideoFileClip(video_path)
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audio = clip.audio
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audio.write_audiofile(audio_path, fps=16000, nbytes=2, codec='pcm_s16le', ffmpeg_params=["-ac", "1"])
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clip.close()
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audio.close()
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@st.cache_resource(show_spinner="Loading model...")
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def load_model():
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classifier = EncoderClassifier.from_hparams(
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source=MODEL_ID,
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savedir=os.path.join(os.getcwd(), "accent-id-model")
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)
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return classifier
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def classify_accent(audio_path, classifier):
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audio_path_clean = os.path.abspath(audio_path).replace('\\', '/')
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if not os.path.exists(audio_path_clean):
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raise FileNotFoundError(f"Audio file not found: {audio_path_clean}")
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out_prob, score, index, label = classifier.classify_file(audio_path_clean)
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return label, round(score.item() * 100, 2)
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# ---------------- UI ----------------
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st.title("π£οΈ Accent Classifier from Video")
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st.markdown("Paste a direct **video URL (MP4)** and then press **Enter** or click **Identify the Accent**.")
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with st.form("url_form", clear_on_submit=False):
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video_url = st.text_input("π Video URL", placeholder="https://...")
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submitted = st.form_submit_button("π£οΈ Identify the Accent")
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if submitted:
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if not video_url:
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st.warning("β οΈ Please enter a video URL.")
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else:
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try:
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if "dropbox.com" in video_url and "raw=1" not in video_url:
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video_url = video_url.replace("dl=0", "raw=1").replace("?dl=0", "?raw=1")
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with st.spinner("π Downloading and processing video..."):
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with tempfile.TemporaryDirectory() as tmpdir:
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video_path = os.path.join(tmpdir, "input_video.mp4")
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audio_path = os.path.join(tmpdir, "output_audio.wav")
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download_video(video_url, video_path)
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extract_audio(video_path, audio_path)
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classifier = load_model()
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label, confidence = classify_accent(audio_path, classifier)
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st.success("β
Accent classified successfully!")
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st.markdown(f"### π― Prediction: **{label}**")
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st.markdown(f"π§ Confidence: **{confidence}%**")
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st.info(f"The speaker's accent is predicted to be **{label}** with **{confidence}%** confidence.")
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except Exception as e:
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st.error(f"β Error: {e}")
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requirements.txt
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altair
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altair==5.5.0
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attrs==25.3.0
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audioread==3.0.1
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blinker==1.9.0
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cachetools==5.5.2
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certifi==2025.4.26
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cffi==1.17.1
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charset-normalizer==3.4.2
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click==8.2.1
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colorama==0.4.6
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decorator==4.4.2
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filelock==3.18.0
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fsspec==2025.5.1
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gitdb==4.0.12
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GitPython==3.1.44
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huggingface-hub==0.32.2
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HyperPyYAML==1.2.2
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idna==3.10
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imageio==2.37.0
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imageio-ffmpeg==0.6.0
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Jinja2==3.1.6
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joblib==1.5.1
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jsonschema==4.24.0
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jsonschema-specifications==2025.4.1
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lazy_loader==0.4
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librosa==0.11.0
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llvmlite==0.44.0
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MarkupSafe==3.0.2
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moviepy==1.0.3
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mpmath==1.3.0
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msgpack==1.1.0
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narwhals==1.41.0
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networkx==3.4.2
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numba==0.61.2
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numpy==2.2.6
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packaging==24.2
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pandas==2.2.3
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pillow==11.2.1
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platformdirs==4.3.8
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pooch==1.8.2
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proglog==0.1.12
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protobuf==6.31.1
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pyarrow==20.0.0
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pycparser==2.22
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pydeck==0.9.1
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pydub==0.25.1
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python-dateutil==2.9.0.post0
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python-dotenv==1.1.0
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pytz==2025.2
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PyYAML==6.0.2
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referencing==0.36.2
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regex==2024.11.6
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requests==2.32.3
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rpds-py==0.25.1
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ruamel.yaml==0.18.11
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ruamel.yaml.clib==0.2.12
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safetensors==0.5.3
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scikit-learn==1.6.1
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scipy==1.15.3
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sentencepiece==0.1.99
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six==1.17.0
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smmap==5.0.2
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soundfile==0.13.1
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soxr==0.5.0.post1
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speechbrain==1.0.3
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streamlit==1.45.1
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sympy==1.14.0
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tenacity==9.1.2
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threadpoolctl==3.6.0
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tokenizers==0.21.1
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toml==0.10.2
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torch==2.7.0
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torchaudio==2.7.0
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tornado==6.5.1
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tqdm==4.67.1
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transformers==4.52.3
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typing_extensions==4.13.2
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tzdata==2025.2
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urllib3==2.4.0
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watchdog==6.0.0
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