2-4 さざなみのようなゆれエフェクト「正接波揺らぎ」
img_src = cv2.imread("data/Mandrill.png")
img_gray = cv2.cvtColor(img_src,cv2.COLOR_RGB2GRAY)
#周波数
f = 7.0
#振幅
A = 0.3
#画面の横方向座標
#x
#width
#X
img_dst = np.zeros_like(img_gray)
Y = img_gray.shape[0]
X = img_gray.shape[1]
for y in range(Y):
for x in range(X):
p = (A * np.tan((f * 2.0 * np.pi * x)/X) + 2 * A ) * img_gray[y,x]
if p > 255:
p = 255
elif p < 0:
p = 0
img_dst[y,x] = p
#描画する
cv2.imshow("img_src",img_src)
cv2.imshow("img_dst",img_dst)
cv2.waitKey(0)
cv2.destroyAllWindows()
#ヒストグラム
fig = plt.figure()
ax1 = fig.add_subplot(311) #総行数,総列数、サブプロット番号
ax2 = fig.add_subplot(312)
ax3 = fig.add_subplot(313)
color_list = ["blue","green","red"]
for i,j in enumerate(color_list):
hist = cv2.calcHist([img_src],[i],None,[256],[0,256])
ax1.plot(hist,color = j)
color_list = ["gray"]
for i,j in enumerate(color_list):
hist = cv2.calcHist([img_dst],[i],None,[256],[0,256])
ax2.plot(hist,color = j)
x=np.linspace(0,X,num=X - 1)
p = (A * np.tan((f * 2.0 * np.pi * x)/X) + 2 * A)
ax3.plot(x,p)