74 lines
2.6 KiB
Python
74 lines
2.6 KiB
Python
#!/usr/bin/env python3
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import math
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import cv2 as cv
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import pyskyline
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import numpy as np
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import argparse
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import matplotlib.pyplot as plt
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from matplotlib.widgets import Slider
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def show_result(terrain, skyline, coord, scoremap):
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fig = plt.figure()
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gs = fig.add_gridspec(2,3)
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fig.suptitle("Mosse correlation", fontsize=16)
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ax1 = fig.add_subplot(gs[0, 0])
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ax2 = fig.add_subplot(gs[0, 1])
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ax3 = fig.add_subplot(gs[0, 2])
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ax4 = fig.add_subplot(gs[1, :])
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im1 = ax1.imshow(scoremap, cmap='hot', interpolation='nearest')
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ax1.set_title('Correlation map')
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cbar1 = ax1.figure.colorbar(im1)
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cbar1.ax.set_ylabel("Correlation score", rotation=-90, va="bottom")
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rgb = cv.cvtColor(terrain.rgb(), cv.COLOR_BGR2RGB)
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rgb = cv.circle(rgb, coord, 2, (255,0,0), -1)
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ax2.imshow(rgb)
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ax2.set_title('Colored terrain')
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im2 = ax3.imshow((terrain.grayscale().astype(float) - 135) * (40.0/120.0))
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ax3.set_title('DEM')
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cbar = ax1.figure.colorbar(im2)
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cbar.ax.set_ylabel("Altitude", rotation=-90, va="bottom")
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x = np.linspace(-180,180,skyline.shape[0])
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ax4.plot(x,skyline,label="Agent vision")
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ax4.plot(x,terrain.get_skyline(coord[0], coord[1]), label="DEM data")
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ax4.legend()
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plt.show()
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def eval_score(correlation_map, coord, scale, alpha=10):
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alpha = alpha / scale
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score = 0
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h,w = correlation_map.shape
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x,y = coord
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for j in range(h):
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for i in range(w):
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dist = math.sqrt((x-i)**2+(y-j)**2)
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score += correlation_map[j,i] * 1 #(math.pow(0.5,math.pow(dist/alpha,2)-1)-1)
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return score
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if __name__ == '__main__':
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parser = argparse.ArgumentParser()
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parser.add_argument("--size", help="Terrain size (default=128)", type=int, default=128)
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parser.add_argument("--seed", help="Terrain seed (If not set seed is random)", type=int)
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args = parser.parse_args()
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seed = np.random.randint(0,1024) if args.seed is None else args.seed
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terrain = pyskyline.Terrain.generate(size=args.size,seed=seed,scale=8.0,max_altitude=40.0)
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terrain.precompute_all_skylines()
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x, y = terrain.get_random_water_coordinate()
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skyline = terrain.get_skyline(x, y)
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angle = np.random.randint(1,40)
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skyline = np.roll(skyline, angle)
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correlation_map = pyskyline.MosseCorrelation.process(terrain, skyline)
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score = eval_score(correlation_map,(x,y), terrain._scale,100)
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score = score / (2 * terrain.water_tile_count()) + 0.5
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print(f"{score:0.2f} with angle of {angle}")
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show_result(terrain, skyline, (x,y), correlation_map)
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