Upload app.py

app.py

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+from fastai.vision import *
+from starlette.applications import Starlette
+from starlette.responses import JSONResponse
+from starlette.middleware.cors import CORSMiddleware
+import uvicorn
+import aiohttp
+import asyncio
+import keras
+import numpy as np
+from tensorflow.keras.preprocessing import image
+
+app = Starlette()
+app.add_middleware(CORSMiddleware, allow_origins=["*"], allow_headers=["*"], allow_methods=["*"])
+
+model = keras.models.load_model("Detection_Covid_19.h5")
+
+async def save_file(request):
+    try:
+        form = await request.form()
+        file = form['file']
+        file_bytes = await file.read()
+        file_name = "test.jpg"
+        with open(file_name, 'wb') as f:
+            f.write(file_bytes)
+        
+        # Preprocess the image before feeding it to the model
+        img = image.load_img(file_name, target_size=(224, 224))
+        img = image.img_to_array(img)
+        img = np.expand_dims(img, axis=0)
+        img = img / 255.0  # Normalize the pixel values
+
+        pred = model.predict(img)
+        prediction = "1" if pred[0][0] <= 0.5 else "0"
+        
+        return JSONResponse({"prediction": prediction})
+    
+    except Exception as e:
+        return JSONResponse(content={"error": str(e)}, status_code=500)
+
+app.add_route("/", save_file, methods=['POST'])