removed var annotations

solutions/silver/usaco-740.mdx

@@ -282,112 +282,112 @@ MAX_N = 20
 
 
 class PCL:
-	def __init__(self, i1: int, j1: int, i2: int, j2: int):
-		self.i1 = i1
-		self.j1 = j1
-		self.i2 = i2
-		self.j2 = j2
+    def __init__(self, i1: int, j1: int, i2: int, j2: int):
+        self.i1 = i1
+        self.j1 = j1
+        self.i2 = i2
+        self.j2 = j2
 
-	def is_inside(self, other: "PCL") -> bool:
-		return (
-			self.i1 >= other.i1
-			and self.i2 <= other.i2
-			and self.j1 >= other.j1
-			and self.j2 <= other.j2
-		)
+    def is_inside(self, other: "PCL") -> bool:
+        return (
+            self.i1 >= other.i1
+            and self.i2 <= other.i2
+            and self.j1 >= other.j1
+            and self.j2 <= other.j2
+        )
 
 
-image: List[List[str]] = [[""] * MAX_N for _ in range(MAX_N)]
-visited: List[List[bool]] = [[False] * MAX_N for _ in range(MAX_N)]
+image = [[""] * MAX_N for _ in range(MAX_N)]
+visited = [[False] * MAX_N for _ in range(MAX_N)]
 
 
 # Floodfill to find connected regions (iterative implementation)
 def floodfill(i: int, j: int, color: str) -> None:
-	stack: List[tuple[int, int]] = [(i, j)]
-	visited[i][j] = True
-	while stack:
-		cur_i, cur_j = stack.pop()
-		for di, dj in [(1, 0), (-1, 0), (0, 1), (0, -1)]:
-			new_i, new_j = cur_i + di, cur_j + dj
-			if (
-				i_min <= new_i <= i_max
-				and j_min <= new_j <= j_max
-				and not visited[new_i][new_j]
-				and image[new_i][new_j] == color
-			):
-				visited[new_i][new_j] = True
-				stack.append((new_i, new_j))
+    stack = [(i, j)]
+    visited[i][j] = True
+    while stack:
+        cur_i, cur_j = stack.pop()
+        for di, dj in [(1, 0), (-1, 0), (0, 1), (0, -1)]:
+            new_i, new_j = cur_i + di, cur_j + dj
+            if (
+                i_min <= new_i <= i_max
+                and j_min <= new_j <= j_max
+                and not visited[new_i][new_j]
+                and image[new_i][new_j] == color
+            ):
+                visited[new_i][new_j] = True
+                stack.append((new_i, new_j))
 
 
 # Check whether a given rectangle forms a PCL
 def is_pcl(i1: int, j1: int, i2: int, j2: int) -> bool:
-	global i_min, i_max, j_min, j_max
-	# Keep track of number of regions for each color
-	region_count: List[int] = [0] * 26
-
-	# Set bounds for floodfill
-	i_min, i_max, j_min, j_max = i1, i2, j1, j2
-
-	# Count connected regions for each color within the rectangle bounds
-	for i in range(i1, i2 + 1):
-		for j in range(j1, j2 + 1):
-			if not visited[i][j]:
-				curr_color = image[i][j]
-				region_count[ord(curr_color) - ord("A")] += 1
-				floodfill(i, j, curr_color)
-
-	# Reset visited array for the current rectangle
-	for i in range(i1, i2 + 1):
-		for j in range(j1, j2 + 1):
-			visited[i][j] = False
-
-	# Verify PCL conditions
-	color_count: int = 0
-	color_with_one_region: bool = False
-	color_with_more_regions: bool = False
-	for count in region_count:
-		if count != 0:
-			color_count += 1
-		if count == 1:
-			color_with_one_region = True
-		if count > 1:
-			color_with_more_regions = True
-
-	return color_count == 2 and color_with_one_region and color_with_more_regions
+    global i_min, i_max, j_min, j_max
+    # Keep track of number of regions for each color
+    region_count = [0] * 26
+
+    # Set bounds for floodfill
+    i_min, i_max, j_min, j_max = i1, i2, j1, j2
+
+    # Count connected regions for each color within the rectangle bounds
+    for i in range(i1, i2 + 1):
+        for j in range(j1, j2 + 1):
+            if not visited[i][j]:
+                curr_color = image[i][j]
+                region_count[ord(curr_color) - ord("A")] += 1
+                floodfill(i, j, curr_color)
+
+    # Reset visited array for the current rectangle
+    for i in range(i1, i2 + 1):
+        for j in range(j1, j2 + 1):
+            visited[i][j] = False
+
+    # Verify PCL conditions
+    color_count = 0
+    color_with_one_region = False
+    color_with_more_regions = False
+    for count in region_count:
+        if count != 0:
+            color_count += 1
+        if count == 1:
+            color_with_one_region = True
+        if count > 1:
+            color_with_more_regions = True
+
+    return color_count == 2 and color_with_one_region and color_with_more_regions
 
 
 # Driver code
 with open("where.in", "r") as fin:
-	n: int = int(fin.readline().strip())
-	image = [list(fin.readline().strip()) for _ in range(n)]
+    n = int(fin.readline().strip())
+    image = [list(fin.readline().strip()) for _ in range(n)]
 
-pcl_list: List[PCL] = []
+pcl_list = []
 
 # Brute force every rectangle to find PCLs
 for i1 in range(n):
-	for j1 in range(n):
-		for i2 in range(i1, n):
-			for j2 in range(j1, n):
-				if (i2 - i1 + 1) * (j2 - j1 + 1) < 2:
-					continue
-				if is_pcl(i1, j1, i2, j2):
-					pcl_list.append(PCL(i1, j1, i2, j2))
+    for j1 in range(n):
+        for i2 in range(i1, n):
+            for j2 in range(j1, n):
+                if (i2 - i1 + 1) * (j2 - j1 + 1) < 2:
+                    continue
+                if is_pcl(i1, j1, i2, j2):
+                    pcl_list.append(PCL(i1, j1, i2, j2))
 
-pcl_count: int = 0
+pcl_count = 0
 
 # Check each PCL and ensure it is not inside another PCL
 for i in range(len(pcl_list)):
-	valid_pcl: bool = True
-	for j in range(len(pcl_list)):
-		if i == j:
-			continue
-		if pcl_list[i].is_inside(pcl_list[j]):
-			valid_pcl = False
-			break
-	pcl_count += valid_pcl
+    valid_pcl = True
+    for j in range(len(pcl_list)):
+        if i == j:
+            continue
+        if pcl_list[i].is_inside(pcl_list[j]):
+            valid_pcl = False
+            break
+    pcl_count += valid_pcl
 
 with open("where.out", "w") as fout:
-	fout.write(f"{pcl_count}\n")
+    fout.write(f"{pcl_count}\n")
 ```
 
 </PySection>