hehe

app/ocr_engine.py

@@ -20,41 +20,20 @@ class OCREngine:
         if img is None:
             return []
 
-        img = cv2.resize(img, None, fx=0.7, fy=0.7)
-
-        result = self.ocr.predict(img)
+        # Do NOT resize aggressively
+        result = self.ocr.ocr(img)
 
         lines = []
 
-        if isinstance(result, list):
-            for item in result:
-
-                # Case 1: nested dict with "res"
-                if isinstance(item, dict) and "res" in item:
-                    for sub in item["res"]:
-                        text = sub.get("text", "")
-                        score = sub.get("score", 0.0)
-                        if text:
-                            lines.append({
-                                "text": text,
-                                "confidence": float(score)
-                            })
-
-                # Case 2: flat dict
-                elif isinstance(item, dict) and "text" in item:
+        if result and isinstance(result, list) and len(result) > 0:
+            for line in result[0]:
+                text = line[1][0]
+                score = float(line[1][1])
+
+                if text.strip():
                     lines.append({
-                        "text": item["text"],
-                        "confidence": float(item.get("score", 0.0))
+                        "text": text,
+                        "confidence": score
                     })
 
-                # Case 3: old tuple format
-                elif isinstance(item, list):
-                    for sub in item:
-                        if isinstance(sub, list) and len(sub) == 2:
-                            text, score = sub[1]
-                            lines.append({
-                                "text": text,
-                                "confidence": float(score)
-                            })
-
         return lines