mirror of
https://github.com/MaaAssistantArknights/MaaAssistantArknights.git
synced 2026-07-17 10:00:44 +08:00
424 lines
14 KiB
Python
424 lines
14 KiB
Python
try:
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import cv2
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import numpy as np
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except ImportError:
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print("Please install OpenCV and NumPy to run this script.")
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print("You can install them using:")
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print(" pip install opencv-python numpy")
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exit(1)
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from pathlib import Path
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from typing import Tuple, Optional
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class RoiCropper:
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"""ROI裁剪工具类，支持实时预览和交互式选择"""
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def __init__(self, std_width: int = 1280, std_height: int = 720):
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self.std_width = std_width
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self.std_height = std_height
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self.std_ratio = std_width / std_height
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# ROI选择状态
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self.start_point: Optional[Tuple[int, int]] = None
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self.end_point: Optional[Tuple[int, int]] = None
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self.cropping = False
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self.current_mouse_pos: Optional[Tuple[int, int]] = None
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# 当前处理的图像
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self.original_image: Optional[np.ndarray] = None
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self.display_image: Optional[np.ndarray] = None
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self.current_size: Optional[Tuple[int, int]] = None
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# 扩展参数
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self.horizontal_expansion = 100
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self.vertical_expansion = 100
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# 颜色定义
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self.PREVIEW_COLOR = (255, 255, 0) # 预览
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self.SELECTED_COLOR = (0, 255, 0) # 已选择
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self.EXPANDED_COLOR = (0, 0, 255) # 扩展区域
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self._setup_window()
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def _setup_window(self):
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"""设置OpenCV窗口"""
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cv2.namedWindow("ROI Cropper", cv2.WINDOW_AUTOSIZE)
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cv2.setMouseCallback("ROI Cropper", self._mouse_callback)
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def _mouse_callback(self, event, x, y, flags, param):
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"""鼠标事件回调函数"""
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if event == cv2.EVENT_LBUTTONDOWN:
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self.start_point = (x, y)
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self.end_point = None
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self.cropping = True
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self._update_display()
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elif event == cv2.EVENT_MOUSEMOVE:
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self.current_mouse_pos = (x, y)
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if self.cropping and self.start_point:
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self._update_display()
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elif event == cv2.EVENT_LBUTTONUP:
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if self.start_point:
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self.end_point = (x, y)
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self.cropping = False
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self._update_display()
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def _update_display(self):
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"""更新显示图像"""
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if self.original_image is None:
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return
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display = self.original_image.copy()
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# 显示当前ROI选择
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if self.start_point:
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if self.cropping and self.current_mouse_pos:
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# 实时预览 - 黄色虚线
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end_pos = self.current_mouse_pos
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self._draw_rectangle(
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display,
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self.start_point,
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end_pos,
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self.PREVIEW_COLOR,
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2,
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is_dashed=True,
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)
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elif self.end_point:
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# 最终选择 - 绿色实线
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self._draw_rectangle(
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display, self.start_point, self.end_point, self.SELECTED_COLOR, 2
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)
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# 显示扩展区域 - 红色虚线
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expanded_rect = self._calculate_expanded_rect()
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if expanded_rect:
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self._draw_rectangle(
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display,
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(expanded_rect[0], expanded_rect[1]),
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(
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expanded_rect[0] + expanded_rect[2],
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expanded_rect[1] + expanded_rect[3],
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),
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self.EXPANDED_COLOR,
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1,
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is_dashed=True,
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)
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# 添加操作提示
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#self._draw_instructions(display)
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cv2.imshow("ROI Cropper", display)
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def _draw_rectangle(self, img, pt1, pt2, color, thickness, is_dashed=False):
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"""绘制矩形（支持虚线）"""
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if is_dashed:
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# 绘制虚线矩形
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self._draw_dashed_rectangle(img, pt1, pt2, color, thickness)
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else:
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cv2.rectangle(img, pt1, pt2, color, thickness)
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def _draw_dashed_rectangle(self, img, pt1, pt2, color, thickness):
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"""绘制虚线矩形"""
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x1, y1 = pt1
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x2, y2 = pt2
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# 确保坐标顺序正确
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x1, x2 = min(x1, x2), max(x1, x2)
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y1, y2 = min(y1, y2), max(y1, y2)
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dash_length = 10
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# 绘制四条边的虚线
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self._draw_dashed_line(
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img, (x1, y1), (x2, y1), color, thickness, dash_length
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) # 上边
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self._draw_dashed_line(
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img, (x2, y1), (x2, y2), color, thickness, dash_length
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) # 右边
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self._draw_dashed_line(
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img, (x2, y2), (x1, y2), color, thickness, dash_length
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) # 下边
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self._draw_dashed_line(
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img, (x1, y2), (x1, y1), color, thickness, dash_length
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) # 左边
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def _draw_dashed_line(self, img, pt1, pt2, color, thickness, dash_length):
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"""绘制虚线"""
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x1, y1 = pt1
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x2, y2 = pt2
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dist = int(np.sqrt((x2 - x1) ** 2 + (y2 - y1) ** 2))
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dashes = dist // (dash_length * 2)
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if dashes == 0:
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cv2.line(img, pt1, pt2, color, thickness)
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return
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for i in range(dashes):
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start_ratio = (2 * i * dash_length) / dist
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end_ratio = ((2 * i + 1) * dash_length) / dist
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start_x = int(x1 + (x2 - x1) * start_ratio)
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start_y = int(y1 + (y2 - y1) * start_ratio)
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end_x = int(x1 + (x2 - x1) * end_ratio)
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end_y = int(y1 + (y2 - y1) * end_ratio)
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cv2.line(img, (start_x, start_y), (end_x, end_y), color, thickness)
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def _draw_instructions(self, img):
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"""在图像上绘制操作说明"""
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instructions = [
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"Mouse: Drag to select ROI",
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"S: Save current ROI",
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"R: Reset selection",
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"Q: Next image / Quit",
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"Blue: Preview",
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"Green: Original ORI",
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"Red: Expanded ROI",
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]
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font = cv2.FONT_HERSHEY_SIMPLEX
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font_scale = 0.6
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color = (255, 255, 255)
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thickness = 1
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for i, text in enumerate(instructions):
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y = 25 + i * 25
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# 绘制黑色背景
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(text_width, text_height), _ = cv2.getTextSize(
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text, font, font_scale, thickness
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)
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cv2.rectangle(
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img, (10, y - text_height - 5), (15 + text_width, y + 5), (0, 0, 0), -1
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)
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# 绘制白色文字
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cv2.putText(img, text, (10, y), font, font_scale, color, thickness)
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def _calculate_expanded_rect(self) -> Optional[Tuple[int, int, int, int]]:
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"""计算扩展后的矩形区域"""
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if not (self.start_point and self.end_point and self.current_size):
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return None
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x1, y1 = self.start_point
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x2, y2 = self.end_point
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# 确保坐标顺序正确
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left = min(x1, x2)
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right = max(x1, x2)
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top = min(y1, y2)
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bottom = max(y1, y2)
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# 计算扩展区域
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expand_x = self.horizontal_expansion // 2
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expand_y = self.vertical_expansion // 2
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final_x = max(0, left - expand_x)
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final_y = max(0, top - expand_y)
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final_w = min(
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self.current_size[0] - final_x, (right - left) + self.horizontal_expansion
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)
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final_h = min(
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self.current_size[1] - final_y, (bottom - top) + self.vertical_expansion
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)
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return (final_x, final_y, final_w, final_h)
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def resize_image(self, image: np.ndarray) -> np.ndarray:
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"""调整图像尺寸以符合标准比例"""
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current_ratio = image.shape[1] / image.shape[0]
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if current_ratio >= self.std_ratio:
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# 宽屏或16:9，按高度缩放
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new_height = self.std_height
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new_width = int(current_ratio * self.std_height)
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else:
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# 偏正方形屏幕，按宽度缩放
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new_width = self.std_width
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new_height = int(self.std_width / current_ratio)
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resized = cv2.resize(
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image, (new_width, new_height), interpolation=cv2.INTER_AREA
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)
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self.current_size = (new_width, new_height)
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return resized
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def reset_selection(self):
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"""重置ROI选择"""
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self.start_point = None
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self.end_point = None
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self.cropping = False
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self.current_mouse_pos = None
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self._update_display()
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def has_valid_selection(self) -> bool:
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"""检查是否有有效的ROI选择"""
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return self.start_point is not None and self.end_point is not None
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def get_roi_info(
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self,
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) -> Optional[Tuple[Tuple[int, int, int, int], Tuple[int, int, int, int]]]:
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"""获取ROI信息，返回(原始ROI, 扩展ROI)"""
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if not self.has_valid_selection():
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return None
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x1, y1 = self.start_point
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x2, y2 = self.end_point
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# 原始ROI
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left = min(x1, x2)
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right = max(x1, x2)
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top = min(y1, y2)
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bottom = max(y1, y2)
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original_roi = (left, top, right - left, bottom - top)
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# 扩展ROI
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expanded_rect = self._calculate_expanded_rect()
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if expanded_rect is None:
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return None
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return original_roi, expanded_rect
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def save_roi(self, image: np.ndarray, filename: Path, dst_path: Path) -> bool:
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"""保存ROI图像"""
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roi_info = self.get_roi_info()
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if not roi_info:
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print("No valid ROI selected!")
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return False
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original_roi, expanded_roi = roi_info
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left, top, width, height = original_roi
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# 裁剪ROI区域
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roi_image = image[top : top + height, left : left + width]
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# 生成文件名
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exp_x, exp_y, exp_w, exp_h = expanded_roi
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dst_filename = f"{filename.stem}_{exp_x},{exp_y},{exp_w},{exp_h}.png"
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dst_file_path = dst_path / dst_filename
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# 确保目标目录存在
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dst_path.mkdir(exist_ok=True)
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# 保存图像
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success = cv2.imwrite(str(dst_file_path), roi_image)
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if success:
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print(f"✓ Saved: {dst_filename}")
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print(f" Original ROI: {left}, {top}, {width}, {height}")
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print(f" Expanded ROI: {exp_x}, {exp_y}, {exp_w}, {exp_h}")
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else:
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print(f"✗ Failed to save: {dst_filename}")
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return success
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def process_image(self, image: np.ndarray):
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"""处理单张图像"""
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self.original_image = self.resize_image(image)
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self.reset_selection()
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self._update_display()
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def cleanup(self):
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"""清理资源"""
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cv2.destroyAllWindows()
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def main():
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print("=" * 60)
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print("ROI Cropping Tool")
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print("=" * 60)
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print("Instructions:")
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print("• Put 16:9 images under ./src")
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print("• Drag mouse to select ROI (real-time preview)")
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print("• Press 'S' to save current ROI")
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print("• Press 'R' to reset selection")
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print("• Press 'Q' to go to next image or quit")
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print("• Green: Original ORI, Red: Expanded ROI")
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print("• Cropped images will be saved in ./dst")
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print("=" * 60)
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# 初始化
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cropper = RoiCropper()
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# 设置路径
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base_path = Path(__file__).parent.resolve()
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src_path = base_path / "src"
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dst_path = base_path / "dst"
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# 检查源目录
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if not src_path.exists():
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print(f"❌ Source directory not found: {src_path}")
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print("Please create the 'src' directory and put your images there.")
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return
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# 获取图像文件
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image_files = (
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list(src_path.glob("*.png"))
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+ list(src_path.glob("*.jpg"))
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+ list(src_path.glob("*.jpeg"))
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)
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if not image_files:
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print(f"❌ No image files found in: {src_path}")
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print("Supported formats: PNG, JPG, JPEG")
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return
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print(f"📁 Found {len(image_files)} image(s) to process")
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print()
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try:
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# 处理每张图像
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for i, filename in enumerate(image_files, 1):
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print(f"📸 Processing ({i}/{len(image_files)}): {filename.name}")
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# 读取图像
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image = cv2.imread(str(filename))
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if image is None:
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print(f"❌ Failed to load image: {filename}")
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continue
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# 处理图像
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cropper.process_image(image)
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# 等待用户操作
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while True:
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key = cv2.waitKey(1) & 0xFF
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if key == ord("s") or key == ord("S"):
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# 保存ROI
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if cropper.has_valid_selection():
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if cropper.save_roi(cropper.original_image, filename, dst_path):
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print()
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break
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else:
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print("❌ Failed to save ROI!")
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else:
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print("⚠️ Please select a ROI first!")
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elif key == ord("r") or key == ord("R"):
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# 重置选择
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cropper.reset_selection()
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print("🔄 Selection reset")
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elif key == ord("q") or key == ord("Q"):
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# 下一张图像或退出
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if cropper.has_valid_selection():
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print("⚠️ ROI selected but not saved. Moving to next image...")
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else:
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print("⏭️ Moving to next image...")
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print()
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break
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elif key == 27: # ESC
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print("🛑 Exiting...")
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return
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except KeyboardInterrupt:
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print("\n🛑 Interrupted by user")
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finally:
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cropper.cleanup()
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print("✅ Done!")
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if __name__ == "__main__":
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main()
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