Fix Auto Parse TypeError from invalid OpenCV.js column data (#370)

* Initial plan

* Fix Auto Parse TypeError by adding defensive validation to detectColumns

Added validation checks to prevent "Cannot create property on number" error:
- Validate columns array elements before destructuring
- Add safe handling for malformed column data
- Replace destructuring assignment with explicit variable assignments
- Add validation in reduce operation to handle edge cases

Co-authored-by: cubap <1119165+cubap@users.noreply.github.com>

* Add number type validation to column detection

Improve robustness by validating that column array elements are numbers before performing arithmetic operations. This prevents potential runtime errors from non-numeric values.

Co-authored-by: cubap <1119165+cubap@users.noreply.github.com>

* Refactor: Extract isValidColumn helper function

Reduce code duplication by extracting column validation logic into a reusable helper function. This improves maintainability and makes the code more readable.

Co-authored-by: cubap <1119165+cubap@users.noreply.github.com>

* Add JSDoc documentation to isValidColumn helper

Document the validation helper function with JSDoc comments for better code maintainability and developer experience.

Co-authored-by: cubap <1119165+cubap@users.noreply.github.com>

---------

Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: cubap <1119165+cubap@users.noreply.github.com>

Author: Copilot

components/annotorious-annotator/detect-lines.js

@@ -21,6 +21,16 @@ export function removeOutlierLines(lines, toleranceRatio = 1.5) {
   return lines.filter((_, i) => validIndices.has(i))
 }
 
+/**
+ * Validates that a column element is a properly formatted array with numeric start and end values.
+ * @param {*} col - The column element to validate
+ * @returns {boolean} True if the column is an array with at least 2 numeric elements
+ */
+function isValidColumn(col) {
+  return Array.isArray(col) && col.length >= 2 && 
+         typeof col[0] === 'number' && typeof col[1] === 'number'
+}
+
 export function detectColumns(binary, minColumnWidth = 50, spaceThreshold = 0.1) {
   const verticalProj = new cv.Mat()
   cv.reduce(binary, verticalProj, 0, cv.REDUCE_SUM, cv.CV_32S)
@@ -50,19 +60,40 @@ export function detectColumns(binary, minColumnWidth = 50, spaceThreshold = 0.1)
 
   if (columns.length > 1) {
     const merged = []
-    let [curStart, curEnd] = columns[0]
-    for (const [s, e] of columns.slice(1)) {
-      if (s - curEnd < 3) curEnd = e
-      else {
-        merged.push([curStart, curEnd])
-        [curStart, curEnd] = [s, e]
+    // Ensure columns[0] is a valid array before destructuring
+    if (!isValidColumn(columns[0])) {
+      console.warn("Invalid column format detected, using default column")
+      columns = [[0, binary.cols]]
+    } else {
+      let curStart = columns[0][0]
+      let curEnd = columns[0][1]
+      for (const col of columns.slice(1)) {
+        // Validate each column element
+        if (!isValidColumn(col)) {
+          console.warn("Skipping invalid column element:", col)
+          continue
+        }
+        const [s, e] = col
+        if (s - curEnd < 3) curEnd = e
+        else {
+          merged.push([curStart, curEnd])
+          curStart = s
+          curEnd = e
+        }
       }
+      merged.push([curStart, curEnd])
+      columns = merged
     }
-    merged.push([curStart, curEnd])
-    columns = merged
   }
 
-  const totalWidth = columns.reduce((sum, [s, e]) => sum + (e - s), 0)
+  // Safely calculate total width with validation
+  const totalWidth = columns.reduce((sum, col) => {
+    if (isValidColumn(col)) {
+      return sum + (col[1] - col[0])
+    }
+    return sum
+  }, 0)
+  
   if (columns.length === 0 || totalWidth > 0.85 * binary.cols) {
     columns = [[0, binary.cols]]
   }