def cor(imagem):
ImgOriginal = utils.LerImage('Image_(3a)')
img = colori.color(ImgOriginal)
fig, [ax1, ax2] = plt.subplots(1, 2)
ax1.imshow(ImgOriginal, cmap='gray')
ax2.imshow(img)
plt.show()
def filterRGB(imagem, m=3, n=3):
ImgOriginal = utils.LerImage(imagem)
# imagem = np.uint8(ruido.average(ImgOriginal,m,n))
# imagem = np.uint8(ruido.Median(imagem,m,n))
imagem = np.uint8(ruido.Median(ImgOriginal, m, n))
# imagem = np.uint8(ruido.min_max(imagem,m,n))
imagem = np.uint8(ruido.midpoint(imagem, m, n))
fig, [ax1, ax2] = plt.subplots(1, 2)
ax1.imshow(ImgOriginal)
ax2.imshow(imagem)
plt.show()
def filterHSI(imagem, m=3, n=3):
ImgOriginal = utils.LerImage(imagem)
img = utils.rgb2hsi(ImgOriginal)
# img = ruido.average(img,m,n)
# img = ruido.Median(img,m,n)
# img = ruido.Median(img,m,n)
img = ruido.midpoint(img, m, n)
img = utils.hsi2rgb(img)
fig, [ax1, ax2] = plt.subplots(1, 2)
ax1.imshow(ImgOriginal)
ax2.imshow(img)
plt.show()
def Quant(imagem, bit):
ImgOriginal = utils.LerImage(imagem)
aux = np.shape(ImgOriginal)
img = np.zeros(aux)
norma = (255 - ImgOriginal) / 255
img = np.floor(bit - (bit * norma))
img = img.astype(int)
plt.imsave('../Resultados/{}_{}'.format(imagem, bit),
img,
cmap='gray',
vmin=0,
vmax=bit)
return img
def Huffman(imagem):
img = utils.LerImage(imagem)
p = utils.Probabilidade(img)
mem = np.zeros(256)
count = 0
for i in range(256):
for j in range(i, 256):
if p[i] < p[j]:
mem[i] = i
aux = p[i]
p[i] = p[j]
p[j] = aux
new_p = []
new_p.append(p)
while np.size(new_p[-1]) > 2:
huff = np.zeros(np.size(new_p[-1]) - 1)
for t in range(np.size(new_p[-1]) - 2):
huff[t] = new_p[-1][t]
huff[-1] = new_p[-1][-1] + new_p[-1][-2]
new_p.append(huff)
for i in range(np.size(new_p[-1])):
for t in range(i, np.size(new_p[-1])):
if new_p[-1][i] < new_p[-1][t]:
aux = new_p[-1][i]
new_p[-1][i] = new_p[-1][t]
new_p[-1][t] = aux
# for h in range(np.shape(new_p)[0]-1,-1,-1):
# if h == np.shape(new_p)[0]-1:
huffcode = new_p
return huffcode
def clarear(imagem, m):
ImgOriginal = utils.LerImage(imagem)
fig, [ax1, ax2] = plt.subplots(1, 2)
ax1.imshow(ImgOriginal)
ax2.imshow(iluminacao.clarear(ImgOriginal, m))
plt.show()
def escurecer(imagem, m):
ImgOriginal = utils.LerImage('Image_(1b)')
fig, [ax1, ax2] = plt.subplots(1, 2)
ax1.imshow(ImgOriginal)
ax2.imshow(iluminacao.escurecer(ImgOriginal, m))
plt.show()
ax2.imshow(img, cmap='gray')
ax3.imshow(a,cmap='gray')
plt.show()
def test(img):
teste = project.TCC(img)
fig, [ax1,ax2] = plt.subplots(1,2,figsize=(20,10))
ax1.imshow(img)
ax2.imshow(teste,cmap='gray')
plt.show()
if __name__ == '__main__':
for i in range(1,68):
img = utils.LerImage(str(i))
# img = utils.rgb2gray(img)
# print(img)
# sobel(img)
# canny_banda(img)
# r(img)
# aryell(img)
aryell2(img)
# test(img)
# plt.imshow(result,cmap='gray')