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.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+Face[[:space:]]Detector.keras filter=lfs diff=lfs merge=lfs -text

Face Detector.keras

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:370b02eb89ba790cfcd22ca37e0af54e69be109561cb62f76fc59c5e00ad3889
+size 20720065

app.py

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+import streamlit as st
+import numpy as np
+from keras.models import load_model
+from keras.preprocessing import image
+from PIL import Image
+import os
+
+# Load the trained model
+model = load_model("Face Detector.keras")
+
+st.title("😷 Face Mask Detection App")
+st.write("Upload an image and check if the person is wearing a mask.")
+
+# File uploader
+uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
+
+if uploaded_file is not None:
+    # Show uploaded image
+    img = Image.open(uploaded_file)
+    st.image(img, caption="Uploaded Image", use_column_width=True)
+
+    # Preprocess image
+    img = img.resize((200, 200))
+    img = image.img_to_array(img)
+    img = np.expand_dims(img, axis=0)
+    img = img / 255.0
+
+    # Predict
+    prediction = model.predict(img)[0][0]
+
+    # Result
+    if prediction < 0.5:
+        st.success("✅ Mask is Detected")
+    else:
+        st.error("🚫 Mask is NOT Detected")

requirements.txt

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+streamlit
+tensorflow
+keras
+Pillow
+numpy