Update app.py

app.py

@@ -13,15 +13,6 @@ st.markdown(
     <style>
         .stApp { background-color: #050505 !important; color: white !important; }
         [data-testid="stSidebar"] { background-color: #000000 !important; border-right: 1px solid #222; }
-        
-        /* Responsive Image Container */
-        .img-container {
-            display: flex;
-            flex-direction: column;
-            align-items: center;
-        }
-
-        /* Large Download Button for Mobile */
         .stDownloadButton button {
             width: 100%;
             background-color: #007bff !important;
@@ -29,79 +20,81 @@ st.markdown(
             padding: 15px;
             font-weight: bold;
         }
-
-        /* Hide Streamlit elements */
         #MainMenu, footer, .stActionMenu { visibility: hidden !important; }
-        img { pointer-events: none; -webkit-user-drag: none; border-radius: 8px; }
+        img { pointer-events: none; -webkit-user-drag: none; border-radius: 8px; border: 1px solid #333; }
     </style>
     """,
     unsafe_allow_html=True
 )
 
-# --- LOGIC FUNCTIONS (The "Useful Features" Part) ---
+# --- THE "FIX" LOGIC (CLAHE + SMART SHARPEN) ---
 
-def auto_enhance(image):
-    """Automatically adjusts contrast and brightness using Histogram Equalization."""
-    img_array = np.array(image)
-    img_yuv = cv2.cvtColor(img_array, cv2.COLOR_RGB2YUV)
-    # Equalize the histogram of the Y channel (brightness)
-    img_yuv[:,:,0] = cv2.equalizeHist(img_yuv[:,:,0])
-    # Convert back to RGB
-    enhanced_img = cv2.cvtColor(img_yuv, cv2.COLOR_YUV2RGB)
-    return Image.fromarray(enhanced_img)
+def smart_enhance(image):
+    # Convert PIL to OpenCV BGR
+    img_array = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)
+    
+    # 1. CLAHE (Adaptive Equalization) - Fixes the 'blackish' tint issue
+    lab = cv2.cvtColor(img_array, cv2.COLOR_BGR2LAB)
+    l, a, b = cv2.split(lab)
+    
+    # clipLimit 2.0 keeps it natural; tileGridSize 8x8 is standard
+    clahe = cv2.createCLAHE(clipLimit=2.0, tileGridSize=(8,8))
+    cl = clahe.apply(l)
+    
+    limg = cv2.merge((cl,a,b))
+    enhanced_bgr = cv2.cvtColor(limg, cv2.COLOR_LAB2BGR)
+    
+    # 2. Smart Sharpen (Unsharp Mask) - Makes text HD without artifacts
+    # We blur a copy and subtract it from the original to find edges
+    blurred = cv2.GaussianBlur(enhanced_bgr, (0, 0), 3)
+    sharpened = cv2.addWeighted(enhanced_bgr, 1.5, blurred, -0.5, 0)
+    
+    return Image.fromarray(cv2.cvtColor(sharpened, cv2.COLOR_BGR2RGB))
 
 def reduce_noise(image):
-    """Removes grain/noise from photos."""
     img_array = np.array(image)
-    # Fast Non-Local Means Denoising
     denoised = cv2.fastNlMeansDenoisingColored(img_array, None, 10, 10, 7, 21)
     return Image.fromarray(denoised)
 
 # --- MAIN APP ---
 st.title("📸 AI Ultra Enhancer")
-
 uploaded_file = st.file_uploader("Drop an image here", type=["jpg", "png", "jpeg"])
 
 if uploaded_file:
-    # Load and auto-convert
     original = Image.open(uploaded_file).convert("RGB")
     
-    # --- SIDEBAR CONTROLS ---
     st.sidebar.header("🛠️ Magic Tools")
     
-    # Auto-Enhance Toggle
-    do_auto = st.sidebar.toggle("Auto-Fix Lighting", value=True)
+    # Use the new Smart Enhance instead of the old Auto-Fix
+    do_smart = st.sidebar.toggle("Smart HD Enhancement", value=True)
     do_denoise = st.sidebar.toggle("Remove Noise (HD)", value=False)
     
     st.sidebar.divider()
     
-    # Manual Overrides
-    with st.sidebar.expander("Fine-Tune Adjustments"):
+    with st.sidebar.expander("Manual Fine-Tune"):
         br = st.slider("Brightness", 0.5, 2.0, 1.0)
         ct = st.slider("Contrast", 0.5, 2.0, 1.0)
-        sh = st.slider("Sharpness", 0.0, 5.0, 1.0)
+        sh = st.slider("Manual Sharpness", 0.0, 3.0, 1.0)
         sa = st.slider("Color Pop", 0.0, 2.0, 1.0)
 
-    # Filter Presets
-    preset = st.sidebar.radio("Quick Presets", ["Original", "Vibrant", "Cinematic", "B&W", "Sketch"])
+    preset = st.sidebar.radio("Quick Presets", ["Original", "Vibrant", "Document/Text", "B&W", "Sketch"])
 
-    # --- IMAGE PROCESSING PIPELINE ---
+    # --- PIPELINE ---
     processed = original.copy()
 
-    # 1. Automatic Enhancements
-    if do_auto:
-        processed = auto_enhance(processed)
+    # 1. AI Logic
+    if do_smart:
+        processed = smart_enhance(processed)
     if do_denoise:
         processed = reduce_noise(processed)
 
-    # 2. Apply Presets
+    # 2. Preset Logic
     if preset == "Vibrant":
         processed = ImageEnhance.Color(processed).enhance(1.5)
-        processed = ImageEnhance.Contrast(processed).enhance(1.2)
-    elif preset == "Cinematic":
-        processed = ImageEnhance.Brightness(processed).enhance(0.9)
-        processed = ImageEnhance.Contrast(processed).enhance(1.4)
-        processed = ImageEnhance.Color(processed).enhance(0.8)
+    elif preset == "Document/Text":
+        # Specifically for screenshots/Allens students notes!
+        processed = ImageEnhance.Contrast(processed).enhance(1.5)
+        processed = ImageEnhance.Sharpness(processed).enhance(2.0)
     elif preset == "B&W":
         processed = processed.convert("L").convert("RGB")
     elif preset == "Sketch":
@@ -111,7 +104,7 @@ if uploaded_file:
         sketch = cv2.divide(gray, 255 - blur, scale=256)
         processed = Image.fromarray(sketch).convert("RGB")
 
-    # 3. Manual Enhancements
+    # 3. Final Sliders
     processed = ImageEnhance.Brightness(processed).enhance(br)
     processed = ImageEnhance.Contrast(processed).enhance(ct)
     processed = ImageEnhance.Sharpness(processed).enhance(sh)
@@ -130,9 +123,4 @@ if uploaded_file:
     st.divider()
     buf = io.BytesIO()
     processed.save(buf, format="PNG")
-    st.download_button(
-        "✨ Download Enhanced Image",
-        data=buf.getvalue(),
-        file_name="AI_Enhanced.png",
-        mime="image/png"
-    )
+    st.download_button("✨ Download Enhanced Image", data=buf.getvalue(), file_name="AI_Enhanced.png", mime="image/png")