Update app.py

app.py

@@ -5,6 +5,8 @@ from flask import Flask, request, send_file, jsonify
 from rembg import remove
 from PIL import Image, ImageEnhance, ImageFilter
 import io
+import cv2
+import numpy as np
 
 # --- Create the Flask App ---
 app = Flask(__name__)
@@ -173,6 +175,70 @@ def enhance_image_api():
 
     return jsonify({"error": "An unknown error occurred"}), 500
 
+# --- POWERFUL AI IMAGE ENHANCER API ENDPOINT ---
+
+@app.route('/auto-enhance-image', methods=['POST'])
+def auto_enhance_image_api():
+    # 1. --- API Key Authentication ---
+    api_key_header = request.headers.get('x-api-key')
+    if not api_key_header or api_key_header != API_KEY:
+        return jsonify({"error": "Unauthorized. Invalid or missing API Key."}), 401
+
+    # 2. --- File Check ---
+    if 'file' not in request.files:
+        return jsonify({"error": "No file part in the request"}), 400
+
+    file = request.files['file']
+    if file.filename == '':
+        return jsonify({"error": "No selected file"}), 400
+
+    # 3. --- Professional Image Enhancement with OpenCV ---
+    if file:
+        try:
+            # Image ko bytes se parh kar ek NumPy array mein convert karna
+            filestr = file.read()
+            npimg = np.frombuffer(filestr, np.uint8)
+            img = cv2.imdecode(npimg, cv2.IMREAD_COLOR)
+
+            # --- Enhancement Step 1: CLAHE for Perfect Contrast ---
+            # Image ko LAB color space mein convert karna
+            lab = cv2.cvtColor(img, cv2.COLOR_BGR2LAB)
+            l, a, b = cv2.split(lab)
+            # Lightness (L) channel per CLAHE apply karna
+            clahe = cv2.createCLAHE(clipLimit=3.0, tileGridSize=(8, 8))
+            cl = clahe.apply(l)
+            # Channels ko wapas milana
+            limg = cv2.merge((cl, a, b))
+            # Image ko wapas BGR color space mein convert karna
+            img_clahe = cv2.cvtColor(limg, cv2.COLOR_LAB2BGR)
+
+            # --- Enhancement Step 2: Unsharp Masking for Natural Sharpness ---
+            # Image ko thoda blur karna
+            gaussian_blur = cv2.GaussianBlur(img_clahe, (0, 0), 3.0)
+            # Original image mein sharpness add karna
+            # Is se details bohot behtar ho jaati hain
+            img_enhanced = cv2.addWeighted(img_clahe, 1.5, gaussian_blur, -0.5, 0)
+
+            # --- Final Result ---
+            # Processed image (NumPy array) ko wapas PNG bytes mein convert karna
+            is_success, buffer = cv2.imencode(".png", img_enhanced)
+            if not is_success:
+                raise Exception("Could not encode enhanced image.")
+            
+            output_image_bytes = buffer.tobytes()
+
+            # 4. --- Send the Response ---
+            return send_file(
+                io.BytesIO(output_image_bytes),
+                mimetype='image/png',
+                as_attachment=True,
+                download_name='auto_enhanced_image.png'
+            )
+        except Exception as e:
+            return jsonify({"error": "Failed to enhance image", "details": str(e)}), 500
+
+    return jsonify({"error": "An unknown error occurred"}), 500
+
 # --- Run the App ---
 if __name__ == '__main__':
     # For local testing, ensure the environment variable is set.