106 lines
2.9 KiB
Python
106 lines
2.9 KiB
Python
import numpy as np
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import cv2
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''' Einlesen des Bildes '''
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img = cv2.imread("data/normal.jpg")
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rows, cols, channels = img.shape
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''' Transformation t1: Implementierung mit OpenCV '''
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t_1 = np.float32(
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[
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[ np.cos(np.pi / 4), np.sin(np.pi / 4), 0],
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[-np.sin(np.pi / 4), np.cos(np.pi / 4), 0]]
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)
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dst = cv2.warpAffine(img, t_1, (cols, rows))
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cv2.imshow('img',dst)
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cv2.waitKey(0)
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''' Transformation t2: Implementierung ohne CV2 '''
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c1, c2, c3, c4 = np.cos(np.pi / 4), np.sin(np.pi / 4), -np.sin(np.pi / 4), np.cos(np.pi / 4)
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c_y, c_x = rows / 2, cols / 2
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def new_pos(x, y):
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new_x = round(c1 * (x - c_x) + c2 * (y - c_y) + c_x)
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new_y = round(c3 * (x - c_x) + c4 * (y - c_y) + c_y)
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return new_x, new_y
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def old_pos(new_x, new_y):
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x = (new_x/c1) - (c_x / c1) + c_x - c3 * c2 * c_x / (c4 * c1) - (c2 * new_y / (c1 * c4)) + (c_y * c2 / (c1 * c4))
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x = x / (1 - c3*c2/(c4*c1))
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y = c_y + (new_y - (c3 * (x - c_x)) - c_y) / c4
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x = round(x)
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y = round(y)
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return x, y
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# Forwardmapping
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new_img = np.zeros_like(img)
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for x in range(cols):
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for y in range(rows):
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new_x, new_y = new_pos(x, y)
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# Überstpringen, wenn ausserhalb des Bildes
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if not 0 <= new_x < cols or not 0 <= new_y < rows:
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continue
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new_img[new_y, new_x] = img[y, x]
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cv2.imshow('img', new_img)
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cv2.waitKey(0)
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# Backwardmapping
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new_img = np.zeros_like(img)
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for x in range(cols):
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for y in range(rows):
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old_x, old_y = old_pos(x, y)
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# Überstpringen, wenn ausserhalb des Bildes
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if not 0 <= old_x < cols or not 0 <= old_y < rows:
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continue
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new_img[y, x] = img[old_y, old_x]
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cv2.imshow('img', new_img)
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cv2.waitKey(0)
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''' Transformation t3: Implementierung ohne CV2 '''
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c1, c2, c3, c4 = 1, 0.8, 0, 1
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c_y, c_x = rows / 2, cols / 2
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def new_pos(x, y):
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new_x = round(c1 * (x - c_x) + c2 * (y - c_y) + c_x)
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new_y = round(c3 * (x - c_x) + c4 * (y - c_y) + c_y)
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return new_x, new_y
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def old_pos(new_x, new_y):
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x = (new_x/c1) - (c_x / c1) + c_x - c3 * c2 * c_x / (c4 * c1) - (c2 * new_y / (c1 * c4)) + (c_y * c2 / (c1 * c4))
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x = x / (1 - c3*c2/(c4*c1))
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y = c_y + (new_y - (c3 * (x - c_x)) - c_y) / c4
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x = round(x)
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y = round(y)
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return x, y
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# Forwardmapping
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new_img = np.zeros_like(img)
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for x in range(cols):
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for y in range(rows):
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new_x, new_y = new_pos(x, y)
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# Überstpringen, wenn ausserhalb des Bildes
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if not 0 <= new_x < cols or not 0 <= new_y < rows:
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continue
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new_img[new_y, new_x] = img[y, x]
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cv2.imshow('img', new_img)
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cv2.waitKey(0)
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# Backwardmapping
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new_img = np.zeros_like(img)
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for x in range(cols):
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for y in range(rows):
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old_x, old_y = old_pos(x, y)
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# Überstpringen, wenn ausserhalb des Bildes
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if not 0 <= old_x < cols or not 0 <= old_y < rows:
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continue
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new_img[y, x] = img[old_y, old_x]
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cv2.imshow('img', new_img)
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cv2.waitKey(0) |