Initial commit

.gitattributes

@@ -32,3 +32,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
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+*.mp3 filter=lfs diff=lfs merge=lfs -text
+*.m4a filter=lfs diff=lfs merge=lfs -text
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examples/cmd.txt

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+ffmpeg -ss 1080 -i timbaland.mp3 -t 180 -c copy timbaland_3.wav
+/home/fantasyfish/Desktop/dotdemo/examples/sweet tooth ai.mp3
+sudo lsof -n -i :7865

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inference_server/Dockerfile

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+# syntax=docker/dockerfile:1
+
+FROM python:3.10-bullseye
+
+EXPOSE 8080-8081
+
+WORKDIR /app
+
+COPY . .
+
+RUN pip3 install -r requirements.txt && \
+    pip3 install flask
+RUN apt-get update && \
+    apt-get upgrade && \
+    apt-get install -y ffmpeg
+RUN pip3 install ffmpeg-python
+
+ENV RVCPATH=/third_party/RVC
+ENV PYTHONPATH=$PYTHONPATH:$RVCPATH
+
+CMD ["python3", "/app/server.py"]

inference_server/requirements.txt

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+joblib>=1.1.0
+numba==0.56.4
+numpy==1.23.5
+scipy==1.9.3
+librosa==0.9.2
+llvmlite==0.39.0
+fairseq==0.12.2
+faiss-cpu==1.7.3
+gradio
+Cython
+pydub>=0.25.1
+soundfile>=0.12.1
+ffmpeg-python>=0.2.0
+tensorboardX
+Jinja2>=3.1.2
+json5
+Markdown
+matplotlib>=3.7.0
+matplotlib-inline>=0.1.3
+praat-parselmouth>=0.4.2
+Pillow>=9.1.1
+resampy>=0.4.2
+scikit-learn
+starlette>=0.25.0
+tensorboard
+tqdm>=4.63.1
+tornado>=6.1
+Werkzeug>=2.2.3
+uc-micro-py>=1.0.1
+sympy>=1.11.1
+tabulate>=0.8.10
+PyYAML>=6.0
+pyasn1>=0.4.8
+pyasn1-modules>=0.2.8
+fsspec>=2022.11.0
+absl-py>=1.2.0
+audioread
+uvicorn>=0.21.1
+colorama>=0.4.5
+pyworld>=0.3.2
+flask>=2.3.2

inference_server/server.py

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+'''
+sudo docker run --gpus all --runtime=nvidia --rm \
+    -v /home/fantasyfish/Desktop/dotdemo/third_party:/third_party \
+    -v /home/fantasyfish/Desktop/dotdemo/examples:/inputDir \
+    -v /home/fantasyfish/Desktop/dotdemo/logs:/logs \
+    -v /home/fantasyfish/Desktop/dotdemo/results:/outputDir \
+    -v /home/fantasyfish/Desktop/dotdemo/inference_server:/app \
+    -p 8081:8081 \
+    -it rvc:v0
+curl -X GET http://localhost:8081/inference \
+   -H 'Content-Type: application/json' \
+   -d '{"expName":"drake-200","audioFileName":"radwimps.mp3", "pitchShift": 0}'
+'''
+import json
+import os
+from flask import Flask, request
+from logging import exception
+import time
+from server_utils import model_inference_single
+from glob import glob
+
+print("import successful!")
+
+app = Flask(__name__)
+
+@app.route("/ping")
+def healthcheck():
+    return json.dumps({"code": 200, "message": "responding"}).encode('utf-8')
+
+@app.route("/inference", methods=['GET'])
+def inference():
+    if request.headers['Content-Type'] != 'application/json':
+        exception("Header error")
+        return json.dumps({"message":"Header error"}), 500
+    try:
+        content = request.get_json()
+        exp_name = content['expName']
+        audio_file_name = content['audioFileName']
+        pitch_shift = content['pitchShift']
+
+        model_path = exp_name + '.pth'
+        index_path_list = glob("/third_party/RVC/logs/{}/added_IVF*_Flat_nprobe_1.index".format(exp_name))
+        assert(len(index_path_list) == 1), "Index file not found"
+        index_path = index_path_list[0]
+        audio_path = os.path.join('/inputDir', audio_file_name)
+        save_path = os.path.join('/outputDir', "{}_{}.wav".format(audio_file_name, exp_name))
+        error_log_path = os.path.join("/logs{}.log".format(exp_name))
+
+        if not os.path.exists('/third_party/RVC/weights/{}'.format(model_path)):
+            exception("Model doesn't exist")
+            return json.dumps({"message":"Model doesn't exist"}), 404
+        if not os.path.exists(audio_path):
+            exception("Audio file doesn't exist")
+            return json.dumps({"message":"Audio file doesn't exist"}), 404
+
+        start_time = time.time()
+        model_inference_single(model_path, index_path, audio_path, save_path, error_log_path, pitch_shift)
+        end_time = time.time()
+        return json.dumps({"message": "Inference Completed in {} secs.".format(end_time - start_time)}), 200
+
+    except Exception as e:
+        exception("Training process failed")
+        return json.dumps({"message":"Inference process failed due to {}".format(e)}), 500
+
+if __name__ == "__main__":
+     app.run(host="0.0.0.0", port=8081, debug=True)

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