333 lines
10 KiB
Python
333 lines
10 KiB
Python
from google_map import GoogleMap
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from pathlib import Path
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from position import Position
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from simulator import Simulator
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from time import sleep
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from trajectory_drawer import TrajectoryDrawer
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from utility import cv2_to_pil
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from vision_chunk import VisionChunk
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from visualization import VisualizationManager
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from yandex_map import YandexMap
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import argparse
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import autopilot
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import constants
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import cv2
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import matplotlib.pyplot as plt
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import numpy as np
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import pickle
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import random
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import utility
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def get_map(map_name: str = 'google', lat=49.103814, lon=55.794258, zoom=18):
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if map_name == 'google': return GoogleMap(lat, lon, zoom)
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if map_name == 'yandex': return YandexMap(lat, lon, zoom)
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return None
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def make_global_photo(filename, map_name: str = 'google', lat=49.103814, lon=55.794258, zoom=13):
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online_map: YandexMap | GoogleMap = get_map(map_name, lat, lon, zoom)
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online_map.save_photo(filename)
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online_map.destroy()
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def get_trajectory_points(bg_img: str) -> list[(float, float)]:
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trajectoryDrawer = TrajectoryDrawer(bg_img)
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trajectoryDrawer.show()
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trajectoryDrawer.wait()
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points = list(map(lambda p: [p[0] / trajectoryDrawer.img.shape[1], p[1] / trajectoryDrawer.img.shape[0]], trajectoryDrawer.points))
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return points
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def build(name: str, map_name: str, lat: float, lon: float):
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# Создание папки с информацией о маршруте
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dir = Path('trajectories')
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if not dir.exists(): dir.mkdir()
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dir /= name
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assert not dir.exists()
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dir.mkdir()
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dir_chunks = dir / 'chunks'
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dir_chunks.mkdir()
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make_global_photo('map.jpg', map_name, lat, lon, 15)
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points = get_trajectory_points('map.jpg')
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online_map: YandexMap | GoogleMap = get_map(map_name, lat, lon, 15)
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width, height = online_map.get_size()
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points_coords = np.array(list(map(lambda p: [
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(p[0] - points[0][0]) * width, (points[0][1] - p[1]) * height
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], points)))
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points_coords *= online_map.pixel_ratio
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# Начнём симуляцию полёта с первой точки
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online_map.make_as_center(*points[0])
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sleep(3)
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online_map.scroll(0.5, 0.5, 10, True)
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sleep(2)
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geo = online_map.get_geolocation()
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online_map.open(geo['lat'], geo['lon'], 18)
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sleep(5)
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points_coords_pixel = points_coords.copy() / online_map.pixel_ratio
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pilot = autopilot.AutoPilot(points_coords_pixel, pixel_ratio=online_map.pixel_ratio)
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simulator = Simulator(online_map)
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pilot.target_idx = 0
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pilot.pos = simulator.pos.copy()
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command = pilot.make_command()
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positions: list[Position] = []
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print("points_coords_pixel:", points_coords_pixel)
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for i in range(5000):
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if command.stop:
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break
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chunk = simulator.get_chunk()
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pilot.pos = simulator.pos.copy()
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command = pilot.make_command()
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command.velocity /= online_map.pixel_ratio
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print("Position:", simulator.pos)
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# Save Image
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chunk.save_image(dir_chunks / f"chunk_{len(positions)}.png")
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positions.append(simulator.pos.copy() * online_map.pixel_ratio)
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simulator.handle(command.dangle, command.velocity)
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if i == 0 and map_name == 'google':
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simulator.pos.x = 0
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simulator.pos.y = 0
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sleep(1.5)
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data = {
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'points': points_coords,
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'chunk_positions': positions,
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'initial_geolocation': geo
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}
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print(points_coords)
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file_positions = dir / 'positions.pkl'
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with file_positions.open('wb') as file:
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pickle.dump(data, file)
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print("WRITE POINTS:", points)
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sleep(15)
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online_map.destroy()
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def run(name: str, map_name: str, ref_min_distance: float):
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dir = Path('trajectories')
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assert dir.exists()
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dir /= name
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assert dir.exists(), "Укажите корректное название маршрута"
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dir_chunks = dir / 'chunks'
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file_positions = dir / 'positions.pkl'
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with file_positions.open('rb') as file:
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data = pickle.load(file)
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initial_geolocation = data['initial_geolocation']
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lat = initial_geolocation['lat']
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lon = initial_geolocation['lon']
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online_map: YandexMap | GoogleMap = get_map(map_name, lat, lon, 18)
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sleep(2)
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chunks: list[VisionChunk] = []
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for i in range(len(data['chunk_positions'])):
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pos = data['chunk_positions'][i]
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if len(chunks) == 0 or np.hypot(chunks[-1].pos.x - pos.x, chunks[-1].pos.y - pos.y) > ref_min_distance:
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chunk = VisionChunk.load_image(dir_chunks / f"chunk_{i}.png")
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chunk.pos = data['chunk_positions'][i] / online_map.pixel_ratio
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chunks.append(chunk)
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r = 0
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for i in range(len(data['points']) - 1):
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r += np.hypot(
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data['points'][i][0] - data['points'][i+1][0],
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data['points'][i][1] - data['points'][i+1][1]
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)
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print("R: ", r)
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return
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points = data['points'] / online_map.pixel_ratio
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print("READ POINTS:", points)
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vis_manager = VisualizationManager()
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pilot = autopilot.AutoPilot(points, chunks, vis_manager, online_map.pixel_ratio)
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simulator = Simulator(online_map)
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pilot.target_idx = 0
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chunk = simulator.get_chunk()
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command = pilot.handle(chunk)
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vis_manager.update_display()
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vis_manager.pause(1)
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vis_manager.set_target_points(data['points'])
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proc_time = np.array([])
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errors = []
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sleep(1)
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for i in range(10000000000):
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if i > 0:
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simulator.set_pitch(np.sin(i / 10) * 5)
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simulator.set_roll(np.sin(i / 15) * 5)
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simulator.set_zoom(1.0 + np.sin(i / 10) * 0.3)
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if command.stop:
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break
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chunk = simulator.get_chunk()
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command = pilot.handle(chunk)
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command.velocity /= online_map.pixel_ratio
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proc_time = np.append(proc_time, command.proccessing_time)
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# Save Image
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chunk.save_image(Path('images') / f"photo_{i}.png")
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vis_manager.update_display()
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vis_manager.pause(0.2)
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vis_manager.set_target_index(pilot.target_idx)
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vis_manager.update_drone_trajectory(pilot.pos.x * online_map.pixel_ratio, pilot.pos.y * online_map.pixel_ratio)
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vis_manager.update_global_map(simulator.pos.x * online_map.pixel_ratio, simulator.pos.y * online_map.pixel_ratio)
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vis_manager.update_error_plot(i, pilot.pos.x * online_map.pixel_ratio, pilot.pos.y * online_map.pixel_ratio, simulator.pos.x * online_map.pixel_ratio, simulator.pos.y * online_map.pixel_ratio)
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errors.append(np.hypot((pilot.pos.x - simulator.pos.x) * online_map.pixel_ratio, (pilot.pos.y - simulator.pos.y) * online_map.pixel_ratio))
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vis_manager.update_display()
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vis_manager.pause(0.2)
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last_proc_times = proc_time[-30:]
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print(F"\nImage #{i}")
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print("Average FPS:", 1 / last_proc_times.mean())
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print("Pilot coords:", pilot.pos)
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print("Simulator coords:", simulator.pos)
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sleep(0.5)
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simulator.handle(command.dangle, command.velocity)
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if i == 0 and map_name == 'google':
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simulator.pos.x = 0
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simulator.pos.y = 0
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print("Errors:", errors)
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print("MSE:", (np.array(errors) ** 2).mean())
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print("RMSE:", (np.array(errors) ** 2).mean() ** 0.5)
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print("Average FPS:", 1 / proc_time.mean())
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vis_manager.show_final()
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def parse_args():
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"""Парсер аргументов командной строки"""
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parser = argparse.ArgumentParser(description='Обработка траекторий')
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# Добавляем обязательный аргумент --mode
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parser.add_argument(
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'--mode',
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type=str,
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required=True,
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choices=['standalone', 'build', 'run'],
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help='Режим работы: standalone, build или run'
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)
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# Добавляем опциональный аргумент --name
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parser.add_argument(
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'--name',
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type=str,
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default=utility.generate_folder_name(),
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help='Название траектории'
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)
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# Координаты
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parser.add_argument(
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'--lat',
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type=float,
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default=49.103814,
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help='Широта (по умолчанию 49.103814)'
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)
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parser.add_argument(
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'--lon',
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type=float,
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default=55.794258,
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help='Долгота (по умолчанию 55.794258)'
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)
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# Источник эталонных изображений (ориентиров)
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parser.add_argument(
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'--reference',
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type=str,
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default='google',
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choices=['google', 'yandex'],
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help='Откуда берутся эталонные изображения (ориентиры): google или yandex (по умолчанию google)'
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)
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# Место проведения симуляции
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parser.add_argument(
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'--simulation',
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type=str,
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default='yandex',
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choices=['google', 'yandex'],
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help='Где проводится симуляция: google или yandex (по умолчанию yandex)'
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)
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# Место проведения симуляции
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parser.add_argument(
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'--ref-min-distance',
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type=float,
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default=100,
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help='Минимальное расстояние между эталонами'
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)
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# Место проведения симуляции
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parser.add_argument(
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'--debug-fps',
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action='store_true',
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help='Включить отладку FPS'
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)
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# Место проведения симуляции
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parser.add_argument(
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'--debug-landmark',
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action='store_true',
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help='Включить отладку эталонов'
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)
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# Парсим аргументы
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args = parser.parse_args()
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# Проверяем, что для build и run указан --name
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if args.mode in ['build', 'run'] and not args.name:
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parser.error(f"--name обязателен для режима {args.mode}")
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return args
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if __name__ == "__main__":
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args = parse_args()
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name = args.name
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mode = args.mode
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sim: str = args.simulation
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ref: str = args.reference
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lat: float = args.lat
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lon: float = args.lon
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rmd: float = args.ref_min_distance
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constants.DEBUG_FPS = args.debug_fps
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constants.DEBUG_LANDMARK = args.debug_landmark
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if mode == 'build' or mode == 'standalone':
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build(name, ref, lat, lon)
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if mode == 'run' or mode == 'standalone':
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run(name, sim, rmd)
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