120 lines
3.4 KiB
Python
120 lines
3.4 KiB
Python
import pygame
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from numpy import array as a
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import numpy as np
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from PIL import Image
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im = Image.open("debug.bmp")
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gray = im.convert('LA')
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asnumpy_gray = np.asarray(gray)
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image = np.asarray(im)
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bnsdfcnsd = np.asarray(im)
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sobel_0 = [
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[-0.125, 0, 0.125],
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[-0.25, 0, 0.25],
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[-0.125, 0, 0.125]
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]
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sobel_1 = [
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[-0.125, -0.25, -0.125],
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[0, 0, 0],
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[0.125, 0.25, 0.125]
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]
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edge_values = a([
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a([0, 1, 0.5, 0.8]),
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a([0.5, 0.2, 0.3, 0.4]),
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a([1, 0.5, 0.6, 0.7]),
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a([0.2, 0.1, 0.1, 0.1])
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])
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asnumpy_gray = a([a([pixel[0] for pixel in row]) for row in asnumpy_gray])
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image = [row.tolist() for row in image]
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def get_minimal_energy_map_vertical(edge_values_):
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minimal_energy_map = np.zeros(shape=edge_values_.shape)
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minimal_energy_map[-1] = edge_values_[-1]
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for i in range(-2, -len(edge_values_) - 1, -1):
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for j in range(len(edge_values_[0])):
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if j == 0:
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minimal_energy_map[i][j] = edge_values_[i][j] + min(minimal_energy_map[i + 1][j:j + 2])
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elif j == len(edge_values_[0]) - 1:
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minimal_energy_map[i][j] = edge_values_[i][j] + min(minimal_energy_map[i + 1][j - 1:j + 1])
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else:
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minimal_energy_map[i][j] = edge_values_[i][j] + min(minimal_energy_map[i + 1][j - 1:j + 2])
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return minimal_energy_map
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def seam_carve_vertical(image, minimal_energy_map):
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seam = np.zeros(len(minimal_energy_map), dtype=np.int32)
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seam[0] = (minimal_energy_map[0].tolist()).index(min(minimal_energy_map[0]))
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for i in range(len(minimal_energy_map) - 1):
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j = seam[i]
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if j == 0:
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sub_array = minimal_energy_map[i + 1][:2].tolist()
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seam[i + 1] = sub_array.index(min(sub_array))
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elif j == len(minimal_energy_map[0]) - 1:
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sub_array = minimal_energy_map[i + 1][-2:].tolist()
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seam[i + 1] = j + sub_array.index(min(sub_array)) - 1
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else:
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sub_array = minimal_energy_map[i + 1][j - 1:j + 2].tolist()
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seam[i + 1] = j + sub_array.index(min(sub_array)) - 1
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for i in range(len(seam)):
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#image[i] = image[i][:seam[i]] + image[i][seam[i] + 1:]
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image[i][seam[i]] = [255, 0, 0]
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return a([a(row, dtype=np.uint8) for row in image], dtype=np.uint8)
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def get_edges_values(input):
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img1 = np.zeros(shape=asnumpy_gray.shape)
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for y in range(1, len(img1) - 1):
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for x in range(1, len(img1[y]) - 1):
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inx = 0.
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for ax in range(-1, 2):
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for b in range(-1, 2):
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try:
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inx += asnumpy_gray[y + ax][x + b] * sobel_0[ax + 1][b + 1] + asnumpy_gray[y + ax][x + b] * sobel_1[ax + 1][b + 1]
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except:
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pass
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img1[y][x] = inx
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return img1
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def dostuff(input):
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for y in range(len(input)):
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for x in range(len(input[y])):
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input[y][x] = (((input[y][x] - -9635.0) * (255 - 0)) / (255 - -9635.0)) + 0
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return input
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for i in range(1):
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print(i)
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#tmp = get_minimal_energy_map_vertical(get_edges_values(asnumpy_gray))
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tmp = get_edges_values(asnumpy_gray)
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tmp = dostuff(tmp)
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image = seam_carve_vertical(image, tmp)
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out = Image.fromarray(tmp)
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image = [row.tolist() for row in image]
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gray = out.convert('LA')
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asnumpy_gray = np.asarray(gray)
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asnumpy_gray = a([a([pixel[0] for pixel in row]) for row in asnumpy_gray])
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print("done!")
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out.show()
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