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| from itertools import count
import cv2
import numpy as np
import matplotlib.pyplot as plt
from scipy import ndimage as ndi
from skimage.util import random_noise
from skimage import feature
class SkyLeftAirplaneChallenger:
"""A fast solution for identifying vertical rivers"""
def __init__(self):
self.flag = "skyleftairplane_model"
self.sky_threshold = 1800
self.left_threshold = 30
self.debug = True
@staticmethod
def _remove_border(img):
img[:, 1] = 0
img[:, -2] = 0
img[1, :] = 0
img[-2, :] = 0
return img
def solution(self, img_stream, **kwargs) -> bool: # noqa
"""Implementation process of solution"""
img_arr = np.frombuffer(img_stream, np.uint8)
img = cv2.imdecode(img_arr, flags=1)
img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# cv2.imshow("img", img)
# cv2.waitKey(0)
edges1 = feature.canny(img)
edges1 = self._remove_border(edges1)
edges2 = feature.canny(img, sigma=3)
edges2 = self._remove_border(edges2)
# display results
# fig, ax = plt.subplots(nrows=1, ncols=3, figsize=(8, 3))
# ax[0].imshow(img, cmap='gray')
# ax[0].set_title('noisy image', fontsize=20)
# ax[1].imshow(edges1, cmap='gray')
# ax[1].set_title(r'Canny filter, $\sigma=1$', fontsize=20)
# ax[2].imshow(edges2, cmap='gray')
# ax[2].set_title(r'Canny filter, $\sigma=3$', fontsize=20)
# for a in ax:
# a.axis('off')
# fig.tight_layout()
# plt.show()
# fill_plane = ndi.binary_fill_holes(edges1)
# fig, ax = plt.subplots(figsize=(4, 3))
# ax.imshow(fill_plane, cmap=plt.cm.gray)
# ax.set_title('filling the holes')
# ax.axis('off')
# plt.show()
# print(np.count_nonzero(edges1))
# print(np.count_nonzero(edges2))
if np.count_nonzero(edges1) > self.sky_threshold:
if self.debug:
print('[not in sky] ', end='')
return False
# get avg coordinate of edges where edges are not zero
# avg_point = np.average(np.nonzero(edges1), axis=1)
# print(avg_point)
min_x = np.min(np.nonzero(edges1), axis=1)[1]
max_x = np.max(np.nonzero(edges1), axis=1)[1]
left_nonzero = np.count_nonzero(edges1[:, min_x:min(max_x, min_x + self.left_threshold)])
right_nonzero = np.count_nonzero(edges1[:, max(min_x, max_x - self.left_threshold):max_x])
# print(left_nonzero, right_nonzero)
if left_nonzero > right_nonzero:
if self.debug:
print('[not turn left] ', end='')
return False
# mid_x = (min_x + max_x) / 2
# print(min_x, max_x, mid_x, avg_point[0] < mid_x)
# if avg_point[0] >= mid_x:
# return False
# plt.show()
return True
if __name__ == '__main__':
import os
import sys
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
result_path = 'result.txt'
if os.path.exists(result_path):
os.remove(result_path)
# result_file = open(result_path, 'w')
result_file = sys.stdout
base_path = os.path.join('..', 'database', 'airplane_in_the_sky_flying_left')
image_list = os.listdir(base_path)
# image_list.sort()
for image_name in image_list:
image_path = os.path.join(base_path, image_name)
with open(image_path, "rb") as file:
data = file.read()
solution = SkyLeftAirplaneChallenger().solution(data)
result_file.write(f'{image_name}: {solution}\n')
result_file.flush()
result_file.close()
|
