Update app/main.py
Browse files- app/main.py +10 -5
app/main.py
CHANGED
@@ -14,7 +14,6 @@ dataset=None
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trained_model=None
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encoder=None
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transform=None
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step=0
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class Item(BaseModel):
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Torque:float=Field(gt=0,default=24.25)
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@@ -32,19 +31,25 @@ def home():
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@app.post("/upload/")
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def upload_csv(file:UploadFile=File(...)):
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dataset=pd.read_csv(file.file)
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file.file.close()
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return {"filename": file.filename}
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@app.post("/train/")
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def training():
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if
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step=2
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results=train(dataset)
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trained_model=results["model"]
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encoder=results["encoder"]
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transform=results["transform"]
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return {"Accuracy":results["Accuracy"],
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"F1_Score":results["F1_Score"]}
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else:
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@@ -52,7 +57,7 @@ def training():
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@app.post("/predict/")
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def prediction(item:Item):
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if
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arr=[[item.Torque,item.Hydraulic_Pressure,item.Cutting,item.Coolant_Pressure,item.Spindle_Speed,item.Coolant_Temperature]]
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results=predict(trained_model,encoder,transform,arr)
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return results
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trained_model=None
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encoder=None
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transform=None
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class Item(BaseModel):
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Torque:float=Field(gt=0,default=24.25)
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@app.post("/upload/")
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def upload_csv(file:UploadFile=File(...)):
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global dataset
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dataset=pd.read_csv(file.file)
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file.file.close()
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return {"filename": file.filename}
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@app.post("/train/")
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def training():
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if dataset is not None:
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results=train(dataset)
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global trained_model
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trained_model=results["model"]
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global encoder
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encoder=results["encoder"]
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global transform
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transform=results["transform"]
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return {"Accuracy":results["Accuracy"],
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"F1_Score":results["F1_Score"]}
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else:
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@app.post("/predict/")
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def prediction(item:Item):
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if trained_model is not None:
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arr=[[item.Torque,item.Hydraulic_Pressure,item.Cutting,item.Coolant_Pressure,item.Spindle_Speed,item.Coolant_Temperature]]
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results=predict(trained_model,encoder,transform,arr)
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return results
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