bruh

app.py

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+import os
+import sys
+import gradio as gr
+
+os.system('git clone https://github.com/Rudrabha/Wav2Lip.git')
+os.system('curl -o ./Wav2Lip/face_detection/detection/sfd/s3fd.pth https://www.adrianbulat.com/downloads/python-fan/s3fd-619a316812.pth')
+os.system('mv ./Wav2Lip/* .')
+
+title = "Wav2Lip Huggingface Interface Test"
+description = "A simple demo for Wav2Lip Official Repo"
+article = "Official Repo: https://github.com/Rudrabha/Wav2Lip"
+
+def inference(face, audio):
+    os.system("python inference.py --checkpoint_path ./wav2lip.pth --face {} --audio {}".format(face, audio))
+
+    return "./results/result_voice.mp4"
+
+
+iface = gr.Interface(inference, inputs=[gr.inputs.Video(type="mp4", source="upload", label="Talking Face Video (in mp4 format)", optional=False), gr.inputs.Audio(source="upload", type="filepath", label="Audio", optional=False)], outputs=["video"], title=title, description=description, article=article, examples=[["./examples/w2l_test_f1.mp4", "./examples/w2l_test_a1.wav"]], enable_queue=False)
+iface.launch()

packages.txt

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+ffmpeg

requirements.txt

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+librosa==0.7.0
+numpy>=1.17.3
+torch==1.4.0
+torchvision==0.5.0
+tqdm>=4.45.0
+numba==0.48
+opencv-contrib-python-headless==4.1.2.30
+