def main():
s = seg.Thresholding()
m = mp.Morphology()
### questão 1
img1a = s.otsu(im.Image("Image_(1a).png"))
img1b = s.otsu(im.Image("Image_(1b).png"))
imgOR = m.logicalOperator(img1a, img1b, "OR")
imgOR.save()
imgAND = m.logicalOperator(img1a, img1b, "AND")
imgAND.save()
imgXOR = m.logicalOperator(img1a, img1b, "XOR")
imgXOR.save()
imgNAND = m.logicalOperator(img1a, img1b, "NAND")
imgNAND.save()
## questão 2
img2a = s.otsu(im.Image("Image_(2a).jpg"))
d_img2a = m.erode(m.erode(m.dilate(img2a)))
d_img2a.save()
### questão 3
img3a = s.otsu(im.Image("Image_(3a).jpg"))
d_img3a = m.floodFill(img3a, (0, 0), 1)
d_img3a.save(extension="floodFill")
d_img3a.setImg(np.logical_not(d_img3a.arr))
d_img3a.save(extension="floodFill_inverse")
img = m.logicalOperator(img3a, d_img3a, "OR")
img.save(extension="floodFill")
### questão 4
img4a = s.otsu(im.Image("Image_(4a).jpg"))
d_img4a = m.floodFill(img4a, (0, 0), 1)
d_img4a = m.dilate(d_img4a)
d_img4a.setImg(np.logical_not(d_img4a.arr))
img = m.logicalOperator(img4a, d_img4a, "OR")
img = m.skeleton(img)
img.save(extension="skeleton")
def preProcess(imgs, arr_y=None, norm=True, gray=True, seg=True):
seg = sg.Thresholding()
arr = []
for y, img in enumerate(imgs):
i = im.Image(img, normalize=norm, gray=gray)
if norm:
i = seg.otsu(i)
bbox = i.bbox()
i.setImg(i.arr[bbox[0]:bbox[1], bbox[2]:bbox[3]])
fe = list(i.features())
if arr_y is not None:
fe.append(arr_y[y])
arr.append(fe)
return arr
def main():
### questão 1
e = seg.Edge()
img = im.Image("Image_(1).jpg", noise=1, median=True, gauss=True)
e_img = e.laplaceofGaussian(img, line=False)
e_img.save(extension="edge")
img = im.Image("Image_(1a).jpg", noise=2, median=True)
e_img = e.laplaceofGaussian(img, line=False)
e_img.save(extension="edge")
img = im.Image("Image_(2a).jpg", noise=21, median=True, gauss=True)
e_img = e.laplaceofGaussian(img, line=False)
e_img.save(extension="edge_21x")
### questão 2
s = seg.Thresholding()
img = im.Image("Image_(3a).jpg", noise=2, median=True)
s_img = s.otsu(img)
s_img.save(extension="thresholding")
img = im.Image("Image_(3a).jpg", noise=5, gauss=True)
s_img = s.otsu(img, edge=True)
s_img.save(extension="edge_thresholding")
img = im.Image("Image_(3b).jpg", noise=3, median=True, gauss=True)
s_img = s.otsu(img)
s_img.save(extension="thresholding")
img = im.Image("Image_(3b).jpg", noise=41, median=True, gauss=True)
s_img = s.otsu(img, edge=True)
s_img.save(extension="edge_thresholding")
img1 = s.otsu(im.Image("Image_(3b).jpg", noise=41, median=True,
gauss=True),
edge=True)
img2 = s.otsu(im.Image("Image_(3b).jpg", noise=3, median=True, gauss=True))
img1.setImg(np.multiply(img1.arr, img2.arr))
img1.save(extension="thresholding_mescle")
