Upload 2 files

app.py

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+from fastapi import FastAPI, File, UploadFile
+import uvicorn
+import tensorflow as tf
+import numpy as np
+import cv2
+from io import BytesIO
+from PIL import Image
+
+app = FastAPI()
+
+# Load model
+model = tf.keras.models.load_model("Face_Mask_Model.h5")
+labels = ["Mask", "No Mask"]
+
+@app.post("/predict")
+async def predict(file: UploadFile = File(...)):
+    image = Image.open(BytesIO(await file.read())).convert("RGB")
+    image = image.resize((128, 128))  # match your input shape
+    img_array = np.array(image).astype("float32") / 255.0
+    img_array = np.expand_dims(img_array, axis=0)
+    
+    pred = model.predict(img_array)[0]
+    result = {labels[i]: float(pred[i]) for i in range(len(labels))}
+    
+    return {"prediction": result}
+
+if __name__ == "__main__":
+    uvicorn.run(app, host="0.0.0.0", port=7860)

face_mask_model.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:e58f27a464bbb54f3ab23abd17c846dea867d047d6904ba1df894eacdea0e98a
+size 39704352