graduation-project/test.py

290 lines
11 KiB
Python
Raw Normal View History

2025-05-05 16:55:41 +08:00
import tkinter as tk
from tkinter import messagebox
import random
import heapq
import os
import cv2
import numpy as np
# 停车场布局数据
left_side = list(range(119, 132))
right_side = list(range(99, 87, -1))
# 将右侧车位编号转换为三位数格式例如099, 098, ...
right_side = [str(number).zfill(3) for number in right_side]
entry_left = [117, 115, 113]
entry_right = [108, 106, 104, 102, 101, 100]
p_row1 = [118, 116, 114, 112, 111, 110, None, 109, 107, 105, 103]
middle_bottom_row1 = [292, 290, 288, 286, 284, 282, 280, 278, 276, 274, 272]
middle_top_row2 = [293, 291, 289, 287, 285, 283, 281, 279, 277, 275, 273, 271]
middle_bottom_row2 = list(range(259, 271))
middle_top_row3 = [None] * 10 + [00] + [None]
middle_bottom_row3 = [258, 257, 256, None, None, None, None, None, None, 255, 254, None]
# 样式参数
car_space_width = 50
car_space_height = 80
road_width = 40
canvas_width = 1200
canvas_height = 900
middle_area_offset_y = 100 # 中间区域整体下移
# 车位状态对应颜色
status_color = {
'free': 'lightgreen',
'occupied': 'tomato',
}
default_color = 'white'
selected_color = 'cyan' # 搜索高亮颜色
# 设置 YOLO 检测结果路径
detection_folder = r"D:\car2\parking_folders"
# A*算法的启发式函数
def heuristic(a, b):
return abs(a[0] - b[0]) + abs(a[1] - b[1]) # 曼哈顿距离
class ParkingLot(tk.Tk):
def __init__(self):
super().__init__()
self.title("停车场平面图 🚗")
self.geometry(f"{canvas_width}x{canvas_height}")
self.canvas = tk.Canvas(self, width=canvas_width, height=canvas_height, bg='#CCCCCC')
self.canvas.pack()
# 搜索部分
self.search_entry = tk.Entry(self)
self.search_entry.pack(pady=5)
self.search_button = tk.Button(self, text="搜索车位", command=self.search_spot)
self.search_button.pack(pady=5)
self.spots = {} # 存储车位信息
self.path = [] # 存储路径
self.obstacles = [] # 存储障碍物坐标
self.draw_parking_lot()
def draw_parking_lot(self):
# 入口灰色路
self.canvas.create_rectangle(400, 0, 800, road_width, fill='gray')
self.canvas.create_text(750, 20, text="入口", fill="red", font=('Arial', 16))
# 入口两边车位
for idx, number in enumerate(entry_left):
x = 400 - (idx + 1) * (car_space_width + 5)
y = 0
self.draw_parking_spot(x, y, number, direction='down')
for idx, number in enumerate(entry_right):
x = 800 + idx * (car_space_width + 5)
y = 0
self.draw_parking_spot(x, y, number, direction='down')
# 左右两列
for idx, number in enumerate(left_side):
x = 0
y = road_width + idx * (car_space_height + 5)
self.draw_parking_spot(x, y, number, direction='right')
for idx, number in enumerate(right_side):
x = canvas_width - 50
y = road_width + idx * (car_space_height + 5)
self.draw_parking_spot(x, y, number, direction='left')
# 中间区域
start_y = road_width + 20 + middle_area_offset_y
self.draw_middle_row(start_y, p_row1, up=True)
self.draw_middle_row(start_y + car_space_height + 5, middle_bottom_row1, up=False)
start_y += (car_space_height + 5) * 2 + road_width
self.draw_middle_row(start_y, middle_top_row2, up=True)
self.draw_middle_row(start_y + car_space_height + 5, middle_bottom_row2, up=False)
start_y += (car_space_height + 5) * 2 + road_width
self.draw_middle_row(start_y, middle_top_row3, up=True)
self.draw_middle_row(start_y + car_space_height + 5, middle_bottom_row3, up=False)
def draw_middle_row(self, start_y, row_data, up=True):
total_spots = len(row_data)
row_width = total_spots * (car_space_width + 5) - 5
start_x = (canvas_width - row_width) / 2
current_x = start_x
for number in row_data:
rect = self.canvas.create_rectangle(
current_x, start_y,
current_x + car_space_width,
start_y + car_space_height,
fill=default_color,
outline='black'
)
if number is not None:
# 初始随机给状态
status = random.choice(['free', 'occupied'])
self.spots[rect] = {'number': number, 'status': status}
self.draw_arrow(current_x, start_y, 'up' if up else 'down')
self.canvas.create_text(current_x + car_space_width / 2, start_y + car_space_height / 2,
text=str(number), font=('Arial', 8))
self.canvas.tag_bind(rect, '<Button-1>', self.toggle_spot)
# 按状态上色
fill_color = status_color.get(status, default_color)
self.canvas.itemconfig(rect, fill=fill_color)
# 添加障碍物坐标
self.obstacles.append((current_x, start_y))
current_x += car_space_width + 5
def draw_arrow(self, x, y, direction):
if direction == 'up':
points = [x + car_space_width / 2, y + 10, x + 10, y + 30, x + car_space_width - 10, y + 30]
elif direction == 'down':
points = [x + car_space_width / 2, y + car_space_height - 10, x + 10, y + car_space_height - 30,
x + car_space_width - 10, y + car_space_height - 30]
elif direction == 'left':
points = [x + 10, y + car_space_height / 2, x + 30, y + 10, x + 30, y + car_space_height - 10]
else:
points = [x + car_space_width - 10, y + car_space_height / 2, x + car_space_width - 30, y + 10,
x + car_space_width - 30, y + car_space_height - 10]
self.canvas.create_polygon(points, fill='black')
def draw_parking_spot(self, x, y, number, direction='up'):
rect = self.canvas.create_rectangle(x, y, x + car_space_width, y + car_space_height, fill=default_color,
outline='black')
# 获取车位编号对应的YOLO检测结果图像路径
detection_image_path = os.path.join(detection_folder, f"{number}.jpg") # 假设图像以车位编号命名
# 检查文件是否存在
if os.path.exists(detection_image_path):
# 读取 YOLO 检测结果图像(假设是红绿图像,红色表示有车,绿色表示空位)
detection_image = cv2.imread(detection_image_path)
# 检查图片是否为空
if detection_image is not None:
# 假设检测图像中左上角是车位的检测状态,我们可以检查该区域的颜色
# 获取车位区域的颜色
region_color = detection_image[10, 10] # 假设检测图像左上角有车位状态信息
# 判断颜色,红色表示有车,绿色表示空位
if np.array_equal(region_color, [0, 0, 255]): # 红色
status = 'occupied'
elif np.array_equal(region_color, [0, 255, 0]): # 绿色
status = 'free'
else:
status = 'free' # 默认状态为免费
else:
status = 'free' # 默认状态为免费,如果读取失败
else:
status = 'free' # 默认状态为免费,如果没有检测结果
self.spots[rect] = {'number': number, 'status': status}
# 绘制箭头
self.draw_arrow(x, y, direction)
# 绘制车位编号
self.canvas.create_text(x + car_space_width / 2, y + car_space_height / 2, text=str(number), font=('Arial', 8))
# 绑定点击事件
self.canvas.tag_bind(rect, '<Button-1>', self.toggle_spot)
# 按状态设置颜色
fill_color = status_color.get(status, default_color)
self.canvas.itemconfig(rect, fill=fill_color)
def toggle_spot(self, event):
clicked = event.widget.find_withtag('current')[0]
spot = self.spots.get(clicked)
if spot:
messagebox.showinfo("车位信息", f"车位编号: {spot['number']}\n状态: {spot['status']}")
def search_spot(self):
query = self.search_entry.get()
found = False
for rect, spot in self.spots.items():
if str(spot['number']) == query:
self.canvas.itemconfig(rect, fill=selected_color)
self.find_path(rect)
found = True
else:
# 恢复成状态颜色
self.canvas.itemconfig(rect, fill=status_color.get(spot['status'], default_color))
if not found:
messagebox.showwarning("提示", "未找到该车位编号!")
def find_path(self, target_rect):
target_coords = self.canvas.coords(target_rect)
start_coords = (canvas_width // 2, 0) # 入口位置
# A*路径规划的实现,避免车位区域
path = self.a_star(start_coords, target_coords)
# 绘制路径
for i in range(len(path) - 1):
self.canvas.create_line(path[i][0], path[i][1], path[i + 1][0], path[i + 1][1], fill="blue", width=4,
arrow=tk.LAST)
def a_star(self, start, end):
open_list = []
closed_list = set()
came_from = {}
start_node = (start[0], start[1])
end_node = (end[0], end[1])
# 计算G、H、F值
def g_cost(node):
return abs(node[0] - start[0]) + abs(node[1] - start[1])
def h_cost(node):
return heuristic(node, end_node)
def f_cost(node):
return g_cost(node) + h_cost(node)
heapq.heappush(open_list, (f_cost(start_node), start_node))
came_from[start_node] = None
while open_list:
current_f, current_node = heapq.heappop(open_list)
if current_node == end_node:
path = []
while current_node:
path.append(current_node)
current_node = came_from[current_node]
return path[::-1]
closed_list.add(current_node)
for direction in [(0, -car_space_height - 5), (0, car_space_height + 5), (-car_space_width - 5, 0),
(car_space_width + 5, 0)]:
neighbor = (current_node[0] + direction[0], current_node[1] + direction[1])
# Check if the neighbor is within bounds and not an obstacle
if 0 <= neighbor[0] < canvas_width and 0 <= neighbor[1] < canvas_height:
if self.is_obstacle(neighbor) or neighbor in closed_list:
continue
heapq.heappush(open_list, (f_cost(neighbor), neighbor))
came_from[neighbor] = current_node
return [] # No path found
def is_obstacle(self, coords):
# 判断当前位置是否为车位(障碍物)
for (x, y) in self.obstacles:
if x <= coords[0] <= x + car_space_width and y <= coords[1] <= y + car_space_height:
return True
return False
if __name__ == "__main__":
app = ParkingLot()
app.mainloop()