Create app.py

app.py

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+import streamlit as st
+import cv2
+import numpy as np
+from PIL import Image
+
+st.title("🖼️ Image Quality Enhancer")
+
+# Upload image
+uploaded_file = st.file_uploader("Upload an image", type=["jpg", "png", "jpeg"])
+
+def enhance_image(image):
+    # Convert to OpenCV format
+    img = np.array(image)
+
+    # Convert to BGR (for OpenCV)
+    img = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)
+
+    # 1. Denoising
+    denoised = cv2.fastNlMeansDenoisingColored(img, None, 10, 10, 7, 21)
+
+    # 2. Sharpening
+    kernel = np.array([[0, -1, 0],
+                       [-1, 5,-1],
+                       [0, -1, 0]])
+    sharpened = cv2.filter2D(denoised, -1, kernel)
+
+    # 3. Convert back to RGB
+    final = cv2.cvtColor(sharpened, cv2.COLOR_BGR2RGB)
+
+    return final
+
+if uploaded_file is not None:
+    image = Image.open(uploaded_file)
+
+    st.subheader("Original Image")
+    st.image(image, use_column_width=True)
+
+    if st.button("Enhance Image"):
+        enhanced = enhance_image(image)
+
+        st.subheader("Enhanced Image")
+        st.image(enhanced, use_column_width=True)
+
+        # Download option
+        result = Image.fromarray(enhanced)
+        st.download_button(
+            label="Download Enhanced Image",
+            data=result.tobytes(),
+            file_name="enhanced.png",
+            mime="image/png"
+        )