adding qr code scann -- before was working

app.py

@@ -11,6 +11,7 @@ import pandas as pd
 import io
 import re
 import traceback
+import zxingcpp  # Added zxingcpp for QR decoding
 
 # Configure logging
 logging.basicConfig(level=logging.INFO)
@@ -29,14 +30,59 @@ except Exception as e:
 
 # Get a random color (used for drawing bounding boxes, if needed)
 def get_random_color():
-    return tuple(np.random.randint(0, 256, 3).tolist())  # Fixed line
-    
+    return tuple(np.random.randint(0, 256, 3).tolist())
+
 def scan_qr_code(image):
+    """
+    Attempts to scan a QR code from the given PIL image using zxingcpp.
+    The image is first saved to a temporary file to be read by zxingcpp.
+    If the direct decoding fails, the function tries a fallback
+    where the image is converted based on a default QR color (black) and tolerance.
+    """
     try:
-        image_np = np.array(image)
-        qr_detector = cv2.QRCodeDetector()
-        data, _, _ = qr_detector.detectAndDecode(image_np)
-        return data.strip() if data else None
+        # Save the PIL image to a temporary file
+        with tempfile.NamedTemporaryFile(suffix=".png", delete=False) as tmp:
+            image.save(tmp, format="PNG")
+            tmp_path = tmp.name
+        
+        # Convert the saved image to a CV2 image
+        img_cv = cv2.imread(tmp_path)
+        # First attempt: direct decoding with zxingcpp
+        try:
+            results = zxingcpp.read_barcodes(img_cv)
+            if results and results[0].text:
+                return results[0].text.strip()
+        except Exception as e:
+            logger.warning(f"Direct zxingcpp decoding failed: {e}")
+        
+        # Fallback: Process image by converting specific QR colors with default parameters.
+        default_color = "#000000"  # Default QR color assumed (black)
+        tolerance = 50  # Fixed tolerance value
+        qr_img = image.convert("RGB")
+        datas = list(qr_img.getdata())
+        newData = []
+        # Convert hex default color to an RGB tuple
+        h1 = default_color.strip("#")
+        rgb_tup = tuple(int(h1[i:i+2], 16) for i in (0, 2, 4))
+        for item in datas:
+            # Check if the pixel is within the tolerance of the default color
+            if (item[0] in range(rgb_tup[0]-tolerance, rgb_tup[0]+tolerance) and
+                item[1] in range(rgb_tup[1]-tolerance, rgb_tup[1]+tolerance) and
+                item[2] in range(rgb_tup[2]-tolerance, rgb_tup[2]+tolerance)):
+                newData.append((0, 0, 0))
+            else:
+                newData.append((255, 255, 255))
+        qr_img.putdata(newData)
+        fallback_path = tmp_path + "_converted.png"
+        qr_img.save(fallback_path)
+        img_cv = cv2.imread(fallback_path)
+        try:
+            results = zxingcpp.read_barcodes(img_cv)
+            if results and results[0].text:
+                return results[0].text.strip()
+        except Exception as e:
+            logger.error(f"Fallback decoding failed: {e}")
+        return None
     except Exception as e:
         logger.error(f"QR scan failed: {str(e)}")
         return None
@@ -83,8 +129,8 @@ def inference(img: Image.Image, confidence):
         ocr_text = " ".join(ocr_texts)
 
         labels = ["person name", "company name", "job title", 
-                "phone number", "email address", "address", 
-                "website"]
+                  "phone number", "email address", "address", 
+                  "website"]
         entities = gliner_model.predict_entities(ocr_text, labels, threshold=confidence, flat_ner=True)
         
         results = {
@@ -162,11 +208,11 @@ def inference(img: Image.Image, confidence):
                     results["Person Name"].append(text)
                     break
 
-        # QR Code
+        # QR Code scanning using the new zxingcpp-based function
         if (qr_data := scan_qr_code(img)):
             results["QR Code"].append(qr_data)
 
-        # Create CSV
+        # Create CSV file containing the results
         csv_data = {k: "; ".join(v) for k, v in results.items() if v}
         with tempfile.NamedTemporaryFile(suffix=".csv", delete=False, mode="w") as tmp_file:
             pd.DataFrame([csv_data]).to_csv(tmp_file, index=False)
@@ -195,4 +241,4 @@ if __name__ == '__main__':
         description=description,
         css=".gr-interface {max-width: 800px !important;}"
     )
-    demo.launch()
+    demo.launch()