Initial commit

04extract_borders.py

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+import os
+from PIL import Image
+import numpy as np
+
+
+def get_edge_opaque_pixels_with_limit(image_path):
+    """
+    提取图片中每一行和每一列最左、最右、最上、最下的完全不透明像素（alpha == 255），
+    并根据位置限制过滤。
+
+    Args:
+        image_path (str): 图片文件路径。
+
+    Returns:
+        dict: 包含四个边的像素信息列表。
+    """
+    with Image.open(image_path).convert("RGBA") as img:
+        width, height = img.size
+        pixels = img.load()
+        limit_left = width / 3
+        limit_right = 2 * width / 3
+        limit_top = height / 3
+        limit_bottom = 2 * height / 3
+
+        left_pixels = []
+        right_pixels = []
+        top_pixels = []
+        bottom_pixels = []
+
+        # 左边
+        for y in range(height):
+            for x in range(width):
+                r, g, b, a = pixels[x, y]
+                if a == 255 and x <= limit_left:
+                    left_pixels.append({
+                        "position": (x, y),
+                        "color": (r, g, b, a)
+                    })
+                    break
+
+        # 右边
+        for y in range(height):
+            for x in range(width - 1, -1, -1):
+                r, g, b, a = pixels[x, y]
+                if a == 255 and x >= limit_right:
+                    right_pixels.append({
+                        "position": (x, y),
+                        "color": (r, g, b, a)
+                    })
+                    break
+
+        # 上边
+        for x in range(width):
+            for y in range(height):
+                r, g, b, a = pixels[x, y]
+                if a == 255 and y <= limit_top:
+                    top_pixels.append({
+                        "position": (x, y),
+                        "color": (r, g, b, a)
+                    })
+                    break
+
+        # 下边
+        for x in range(width):
+            for y in range(height - 1, -1, -1):
+                r, g, b, a = pixels[x, y]
+                if a == 255 and y >= limit_bottom:
+                    bottom_pixels.append({
+                        "position": (x, y),
+                        "color": (r, g, b, a)
+                    })
+                    break
+
+    return {
+        "left": left_pixels,
+        "right": right_pixels,
+        "top": top_pixels,
+        "bottom": bottom_pixels
+    }
+
+
+def get_edge_opaque_pixels_with_limit_numpy(image_path):
+    """
+    使用NumPy提取图片中每一行和每一列最左、最右、最上、最下的完全不透明像素（alpha == 255），
+    并根据位置限制过滤。
+
+    Args:
+        image_path (str): 图片文件路径。
+
+    Returns:
+        dict: 包含四个边的像素信息列表。
+    """
+    with Image.open(image_path).convert("RGBA") as img:
+        data = np.array(img)
+        height, width, _ = data.shape
+        limit_left = width / 3
+        limit_right = 2 * width / 3
+        limit_top = height / 3
+        limit_bottom = 2 * height / 3
+
+        left_pixels = []
+        right_pixels = []
+        top_pixels = []
+        bottom_pixels = []
+
+        # 左边
+        for y in range(height):
+            row = data[y, :, :]
+            opaque_indices = np.where(row[:, 3] == 255)[0]
+            valid_indices = opaque_indices[opaque_indices <= limit_left]
+            if valid_indices.size > 0:
+                x = valid_indices[0]
+                r, g, b, a = row[x]
+                left_pixels.append({
+                    "position": (int(x), y),
+                    "color": (int(r), int(g), int(b), int(a))
+                })
+
+        # 右边
+        for y in range(height):
+            row = data[y, :, :]
+            opaque_indices = np.where(row[:, 3] == 255)[0]
+            valid_indices = opaque_indices[opaque_indices >= limit_right]
+            if valid_indices.size > 0:
+                x = valid_indices[-1]  # 最右边的第一个满足条件的像素
+                r, g, b, a = row[x]
+                right_pixels.append({
+                    "position": (int(x), y),
+                    "color": (int(r), int(g), int(b), int(a))
+                })
+
+        # 上边
+        for x in range(width):
+            column = data[:, x, :]
+            opaque_indices = np.where(column[:, 3] == 255)[0]
+            valid_indices = opaque_indices[opaque_indices <= limit_top]
+            if valid_indices.size > 0:
+                y = valid_indices[0]
+                r, g, b, a = column[y]
+                top_pixels.append({
+                    "position": (x, int(y)),
+                    "color": (int(r), int(g), int(b), int(a))
+                })
+
+        # 下边
+        for x in range(width):
+            column = data[:, x, :]
+            opaque_indices = np.where(column[:, 3] == 255)[0]
+            valid_indices = opaque_indices[opaque_indices >= limit_bottom]
+            if valid_indices.size > 0:
+                y = valid_indices[-1]  # 最下边的第一个满足条件的像素
+                r, g, b, a = column[y]
+                bottom_pixels.append({
+                    "position": (x, int(y)),
+                    "color": (int(r), int(g), int(b), int(a))
+                })
+
+    return {
+        "left": left_pixels,
+        "right": right_pixels,
+        "top": top_pixels,
+        "bottom": bottom_pixels
+    }
+
+
+def process_directory(directory_path, use_numpy=False):
+    """
+    遍历指定文件夹下所有图片文件，提取每张图片的边缘不透明像素信息。
+
+    Args:
+        directory_path (str): 文件夹路径。
+        use_numpy (bool): 是否使用NumPy加速处理。
+
+    Returns:
+        dict: 每个文件对应的四个方向的像素信息。
+    """
+    supported_extensions = ('.png', '.jpg', '.jpeg', '.bmp', '.gif', '.tiff')
+    result_map = {}
+
+    for filename in os.listdir(directory_path):
+        if filename.lower().endswith(supported_extensions):
+            file_path = os.path.join(directory_path, filename)
+            if use_numpy:
+                edge_pixels = get_edge_opaque_pixels_with_limit_numpy(file_path)
+            else:
+                edge_pixels = get_edge_opaque_pixels_with_limit(file_path)
+            result_map[filename] = edge_pixels
+
+    return result_map
+
+
+if __name__ == "__main__":
+    directory_path = "output4"  # 替换为你的文件夹路径
+    use_numpy = True  # 设置为True使用NumPy优化，False使用PIL
+    result = process_directory(directory_path, use_numpy)
+