Upload 4 files

Dockerfile

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+FROM python:3.9.13
+
+WORKDIR /code
+
+COPY ./requirements.txt /code/requirements.txt
+
+RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
+
+COPY . .
+
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]

app.py

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+from fastapi import FastAPI, UploadFile, File
+from fastapi.middleware.cors import CORSMiddleware
+import numpy as np
+from keras.models import load_model
+from keras.utils import load_img, img_to_array
+from io import BytesIO
+from keras.applications.resnet import preprocess_input
+
+
+app = FastAPI()
+origins = ["*"]
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=origins,
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+model = load_model('./vgg19_model.h5')
+class_names = ['glioma', 'meningioma', 'no tumor', 'pituitary']
+@app.get('/')
+def welcome():
+    return {
+        'success': True,
+        'message': 'server of "brain tumor classification using 4 classes" is up and running successfully.'
+    }
+@app.post('/predict')
+async def predict_disease(fileUploadedByUser: UploadFile = File(...)):
+
+    contents = await fileUploadedByUser.read()
+    imageOfUser = load_img(BytesIO(contents), target_size=(224, 224, 3))
+    image_to_arr = img_to_array(imageOfUser)
+    image_to_arr_preprocess_input = preprocess_input(image_to_arr)
+    image_to_arr_preprocess_input_expand_dims = np.expand_dims(image_to_arr_preprocess_input, axis=0)
+    prediction = model.predict(image_to_arr_preprocess_input_expand_dims)[0]
+    prediction_argmax = np.argmax(prediction)
+    prediction_final_result = class_names[prediction_argmax]
+    confidence = np.max(prediction) * 100
+    return {
+        'success': True,
+        'predicted_result': prediction_final_result,
+        'confidence': f'{confidence:.2f}%',
+        'message': f'Status of the Brain Image: {prediction_final_result} with a confidence of {confidence:.2f}%'
+    }

requirements.txt

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+fastapi==0.110.1
+numpy==1.26.4
+uvicorn==0.29.0
+tensorflow==2.10.0
+python-multipart==0.0.9
+Pillow==10.3.0

vgg19_model.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:aeef7aafeebb64bac69e9a3e509fd7573d034f8f1b3f18ace5bcf355d0227f96
+size 119606704