Spaces:
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adding dir via dockerfile
Browse files- Dockerfile +3 -2
- app.py +6 -3
Dockerfile
CHANGED
@@ -1,7 +1,7 @@
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FROM python:3.8.1-slim
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RUN apt-get update
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RUN apt-get install build-essential -y
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# create a new user
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# RUN useradd -m -u 1000 user
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@@ -41,4 +41,5 @@ RUN pip install protobuf==3.20.* --no-cache-dir
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# COPY --chown=user . $HOME/code
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# RUN ls -la $HOME/code
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# RUN chown -r 777:777 /code
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CMD ["python3", "app.py"]
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FROM python:3.8.1-slim
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RUN apt-get update
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RUN apt-get install ffmpeg build-essential -y
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# create a new user
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# RUN useradd -m -u 1000 user
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# COPY --chown=user . $HOME/code
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# RUN ls -la $HOME/code
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# RUN chown -r 777:777 /code
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RUN mkdir flagged
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CMD ["python3", "app.py"]
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app.py
CHANGED
@@ -33,15 +33,18 @@ class DFSeparationApp:
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def predict(self, audio_file):
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# Load the audio file
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with torch.no_grad():
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# Make prediction
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output = self.model(audio_tensor)
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preds = output.argmax(dim=-1)
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probs = output.softmax(dim=-1)
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print(f"[LOG] Prediction: {preds.item()}")
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print(f"[LOG] Probability: {probs.max().item()}")
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def run(self):
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print(f"[LOG] Running the app...")
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def predict(self, audio_file):
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# Load the audio file
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print(f"[LOG] Audio file: {audio_file}")
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audio_tensor = torch.tensor(audio_file[1],dtype=torch.float).unsqueeze(0)
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print(f"[LOG] Audio tensor shape: {audio_tensor.shape}")
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with torch.no_grad():
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# Make prediction
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output = self.model(audio_tensor)
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probs = output.softmax(dim=-1)
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preds = probs.argmax(dim=-1)
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print(f"[LOG] Prediction: {preds.item()}")
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print(f"[LOG] Probability: {probs.max().item()}")
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pred_str = "Fake" if preds.item() == 1 else "Real"
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return pred_str, probs.max().item()
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def run(self):
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print(f"[LOG] Running the app...")
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