def step7():
img = imageio.imread("../assets/img/bb.jpg")
red = img[:, :, 0]
green = img[:, :, 1]
blue = img[:, :, 2]
nb_rows, nb_cols = red.shape
row, col = np.ogrid[:nb_rows, :nb_cols]
cnt_row, cnt_col = nb_rows / 2, nb_cols / 2
outer_disk_mask = ((row - cnt_row)**2 + (col - cnt_col)**2 >
(nb_rows / 2)**2)
red[outer_disk_mask] = 0
green[outer_disk_mask] = 0
blue[outer_disk_mask] = 0
img[0:100, 0:50, :] = 0
plt.subplot(2, 2, 1)
plt.imshow(img)
plt.subplot(2, 2, 2)
plt.title("red")
plt.imshow(red)
plt.subplot(2, 2, 3)
plt.title("green")
plt.imshow(green)
plt.subplot(2, 2, 4)
plt.title("blue")
plt.imshow(blue)
plt.show()
"""Effectuer ce travail d'encerclement sur les 3 composantes RGB puis exporter l'image couleur.
Petit défit : vous pouvez le faire sans rajouter de ligne de code
en traitant les 3 composantes en même temps"""
saveRGB(red, green, blue, 'my.png')
def step5():
img = imageio.imread("../assets/img/g2.jpg")
red = (img[:, :, 0] // 10) * 10 #type:np.ndarray
green = (img[:, :, 1] // 10) * 10 #type:np.ndarray
blue = (img[:, :, 2] // 10) * 10 #type:np.ndarray
h_red = histogramme(red)
h_green = histogramme(green)
h_blue = histogramme(blue)
maxi = max([h_red.max(), h_blue.max(), h_blue.max()])
plt.figure(figsize=(8, 6))
plt.plot(h_red, c='red')
plt.plot(h_green, c='green')
plt.plot(h_blue, c='blue')
plt.axis([0, 255, 0, maxi])
plt.xlabel("valeur")
plt.ylabel("Nombre")
saveRGB(red, green, blue, 'babouin_quantize.png')
plt.show()
def step2b():
img = imageio.imread("../assets/img/ernst.jpg")
r = img[:, :, 0]
g = img[:, :, 1]
saveRGB(np.zeros(g.shape), g, r, "ernst_sb.png")
def step2a():
img = imageio.imread("../assets/img/ernst.jpg")
r = img[:, :, 0]
b = img[:, :, 2]
saveRGB(np.zeros(r.shape), r, b, "ernst_sg.png")
def step2():
img = imageio.imread("../assets/img/ernst.jpg")
g = img[:, :, 1]
b = img[:, :, 2]
saveRGB(np.zeros(g.shape), g, b, "ernst_sr.png")
def step2():
img = imageio.imread("../assets/img/shoe.jpg")
g = img[:, :, 1]
b = img[:, :, 2]
saveRGB(np.zeros(g.shape), g, b, "showr.png")