Update main.py

main.py

@@ -1,63 +1,58 @@
-# Import key libraries and packages
-from fastapi import FastAPI
-import pickle
-import uvicorn
-import pandas as pd
-import sklearn
+from fastapi import FastAPI, File, UploadFile, Request
+from fastapi.templating import Jinja2Templates
+from fastapi.staticfiles import StaticFiles
+from PIL import Image
 import os
-import sys
+import uuid
+import logging
+import shutil
 
-DIRPATH = os.path.dirname(os.path.realpath(__file__))
-ml_component= "./ml_sepsis.pkl"
+# Configure logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
 
-# Function to load pickle file
-def load_pickle(filename):
-    with open(filename, 'rb') as file:
-        data = pickle.load(file)
-        return data
-
-# Load pickle file
-ml_components = load_pickle(ml_component) 
-
-# Components in the pickle file
-ml_model = ml_components['model']
-pipeline_processing = ml_components['pipeline']
-
-# API base configuration
 app = FastAPI()
 
-# Endpoints
-
-@app.get('/Predict_Sepsis')
-async def predict(Plasma_glucose: int, Blood_Work_Result_1: int,
-                  Blood_Pressure: int, Blood_Work_Result_2: int,
-                    Blood_Work_Result_3: int, Body_mass_index: float, 
-                    Blood_Work_Result_4: float,Age: int, Insurance:float):
-    
-    data = pd.DataFrame({'Plasma glucose': [Plasma_glucose], 'Blood Work Result-1': [Blood_Work_Result_1],
-                         'Blood Pressure': [Blood_Pressure], 'Blood Work Result-2': [Blood_Work_Result_2],
-                        'Blood Work Result-3': [Blood_Work_Result_3], 'Body mass index': [Body_mass_index],
-                        'Blood Work Result-4': [Blood_Work_Result_4], 'Age': [Age], 'Insurance':[Insurance]})
-    
-    data_prepared = pipeline_processing.transform(data)
-
-    model_output = ml_model.predict(data_prepared).tolist()
-
-    prediction = make_prediction(model_output)
+# Mount static files
+app.mount("/static", StaticFiles(directory="static"), name="static")
 
-    return prediction
+# Set up templates
+templates = Jinja2Templates(directory="templates")
 
-#Prediction endpoints
-def make_prediction(data_prepared):
+# Set upload folder
+UPLOAD_FOLDER = "static/uploads"
+os.makedirs(UPLOAD_FOLDER, exist_ok=True)
 
-    output_pred = data_prepared
+@app.get("/")
+async def index(request: Request):
+    return templates.TemplateResponse("index.html", {"request": request})
 
-    if output_pred == 0:
-        output_pred = "Sepsis status is Negative"
-    else:
-        output_pred = "Sepsis status is Positive"
+@app.post("/upload")
+async def upload_file(request: Request, file: UploadFile = File(...)):
+    try:
+        # Save uploaded file
+        filename = f"{uuid.uuid4()}{os.path.splitext(file.filename)[1]}"
+        filepath = os.path.join(UPLOAD_FOLDER, filename)
         
-    return output_pred
-
-if __name__=='__main__':
-    uvicorn.run('main:app', reload=True)
+        # Write file content
+        with open(filepath, "wb") as f:
+            shutil.copyfileobj(file.file, f)
+        logger.info(f"File saved: {filename}")
+
+        # Verify and resize image
+        image = Image.open(filepath).convert("RGB")
+        image = image.resize((800, 600))  # Resize for consistent display
+        image.save(filepath)
+        logger.info(f"Image resized and saved: {filename}")
+
+        return templates.TemplateResponse(
+            "results.html",
+            {"request": request, "image": f"/static/uploads/{filename}"}
+        )
+    
+    except Exception as e:
+        logger.error(f"Error processing file: {str(e)}")
+        return templates.TemplateResponse(
+            "index.html",
+            {"request": request, "error": f"Error processing file: {str(e)}"}
+        )