def mergeColor(color_centre1, color12):
if dist1(color_centre1[0, :], color12) < dist1(color_centre1[1, :],
color12):
if dist1(color_centre1[0, :], color12) < 100:
color_centre1[0, :] = (color_centre1[0, :] + color12[:]) / 2
else:
if dist1(color_centre1[1, :], color12) < 100:
color_centre1[1, :] = (color_centre1[1, :] + color12[:]) / 2
return color_centre1
def model23maker(thresh, model2, color_centre1, img1):
for i in range(0, model2.shape[0]):
for j in range(0, model2.shape[1]):
if model2[i, j] == 0:
temp = thresh + 10
index = 0
for ch in range(0, 2):
if dist1(color_centre1[ch, :], img1[i, j, :]) < temp:
temp = dist1(color_centre1[ch, :], img1[i, j, :])
index = ch + 2
model2[i, j] = index
model3 = enhancing(model2, 4)
return model3
def makeModel(model, ColorCent, img, thresh, num):
for i in range(0, img.shape[0]):
for j in range(0, img.shape[1]):
if dist1(ColorCent, img[i, j, :]) < thresh:
model[i, j] = num
model2 = enhancing(model, num)
return model2
def RGB(x, img, thresh):
color12 = np.zeros([3])
color12[0] = x[1][0]
color12[1] = x[1][1]
color12[2] = x[1][2]
img21 = np.zeros([img.shape[0], img.shape[1]])
#imgH =cv2.cvtColor(img, cv2.COLOR_RGB2HSV)
img1 = np.copy(img)
print('rgb')
for i in range(0, img.shape[0]):
for j in range(0, img.shape[1]):
if dist1(color12, img[i, j, :]) < thresh:
img21[i, j] = 1
model2 = enhancing(img21, 2)
return model2, img1
def colorfindergram(new_im, thresh):
color_group = 4
colorsG = colorgram.extract(new_im, color_group)
color_zero = np.zeros([3])
color_centre1 = np.zeros([2, 3])
for i in range(0, color_group):
a = colorsG[i]
color_centre1[0, 0] = a.rgb.r
color_centre1[0, 1] = a.rgb.g
color_centre1[0, 2] = a.rgb.b
if dist1(color_centre1[0, :], color_zero) > thresh:
print(i)
i = color_group
break
a = colorsG[2]
color_centre1[1, 0] = a.rgb.r
color_centre1[1, 1] = a.rgb.g
color_centre1[1, 2] = a.rgb.b
return color_centre1
def HSV(x, img, thresh):
imgH = cv2.cvtColor(img, cv2.COLOR_RGB2HSV)
im = Image.fromarray(imgH)
img1 = np.copy(imgH)
x = max(im.getcolors(im.size[0] * im.size[1]))
cl = im.getcolors(im.size[0] * im.size[1])
cl1 = sorted(cl, reverse=True)
print('hsv')
color12 = np.zeros([3])
color12[0] = x[1][0]
color12[1] = x[1][1]
color12[2] = x[1][2]
img21 = np.zeros([img.shape[0], img.shape[1]])
for i in range(0, img.shape[0]):
for j in range(0, img.shape[1]):
if dist1(color12, imgH[i, j, :]) < thresh:
img21[i, j] = 1
model2 = enhancing(img21, 2)
return model2, img1
def colorfinderhist(new_im, thresh):
cl2 = new_im.getcolors(new_im.size[0] * new_im.size[1])
cl12 = sorted(cl2, reverse=True)
color_zero = np.zeros([3])
for i in range(1, len(cl12)):
x1 = cl12[i]
if x1[1][1] < 240 and x1[1][0] < 240 and dist1(
x1[1][:], color_zero) > thresh:
print(i)
i = len(cl12)
break
color12 = np.zeros([3])
color12[0] = x1[1][0]
color12[1] = x1[1][1]
color12[2] = x1[1][2]
return color12
def meanColoring(im, thresh):
cl = im.getcolors(im.size[0] * im.size[1])
cl1 = sorted(cl, reverse=True)
x = max(im.getcolors(im.size[0] * im.size[1]))
i = 0
if x[1] == (255, 255, 255):
x = cl1[1]
i = 1
count = 1
color = np.dot(x[1], x[0])
sigma = x[0]
for j in range(i + 1, len(cl1)):
x1 = cl1[j]
if dist1(x1[1][:], x[1][:]) < thresh + 5:
count += 1
color += np.dot(x1[1], x1[0])
sigma += x1[0]
color1 = np.dot(color, 1 / sigma)
return color1
def findDominantColor(img, thresh=32, hsv=0):
if hsv == 1:
new_im = FindColor.make_pil(FindColor.hsvImage(img))
else:
new_im = FindColor.make_pil(img)
cl = new_im.getcolors(new_im.size[0] * new_im.size[1])
cl1 = sorted(cl, reverse=True)
color_zero = np.zeros([3])
for i in range(1, len(cl1)):
x1 = cl1[i]
if x1[1][1] < 240 and x1[1][0] < 240 and x1[1][2] < 240 and dist1(
x1[1][:], color_zero) > thresh:
print(i)
i = len(cl1)
break
colorCent = np.zeros([3])
colorCent[0] = x1[1][0]
colorCent[1] = x1[1][1]
colorCent[2] = x1[1][2]
return colorCent
color1[:, :, 0] = x[1][0]
color1[:, :, 1] = x[1][1]
color1[:, :, 2] = x[1][2]
plt.imshow(color1.astype(int))
plt.show()
print('rgb')
color12 = np.zeros([3])
color12[0] = x[1][0]
color12[1] = x[1][1]
color12[2] = x[1][2]
imgH = cv2.cvtColor(img, cv2.COLOR_RGB2HSV)
img21 = np.zeros([img.shape[0], img.shape[1]])
img1 = np.copy(imgH)
for i in range(0, img.shape[0]):
for j in range(0, img.shape[1]):
if dist1(color12, img[i, j, :]) < thresh:
img21[i, j] = 1
else:
imgH = cv2.cvtColor(img, cv2.COLOR_RGB2HSV)
#cv2.imwrite('hsv/imgh.png',imgH)
#name1 = 'hsv/imgh.png'
im = Image.fromarray(imgH)
imgH1 = cv2.cvtColor(imgH, cv2.COLOR_BGR2RGB)
img1 = np.copy(imgH)
#im = Image.open(name1)
x = max(im.getcolors(im.size[0] * im.size[1]))
cl = im.getcolors(im.size[0] * im.size[1])
cl1 = sorted(cl, reverse=True)
#x = cl1[3]
color1[:, :, 0] = x[1][0]
color1[:, :, 1] = x[1][1]
color1[:, :, 2] = x[1][2]
plt.imshow(color1.astype(int))
plt.show()
print('rgb')
color12 = np.zeros([3])
color12[0] = x[1][0]
color12[1] = x[1][1]
color12[2] = x[1][2]
imgH = cv2.cvtColor(img, cv2.COLOR_RGB2HSV)
img21 = np.zeros([img.shape[0], img.shape[1]])
img1 = np.copy(imgH)
for i in range(0, img.shape[0]):
for j in range(0, img.shape[1]):
if dist1(color12, img[i, j, :]) < thresh:
img21[i, j] = 1
else:
imgH = cv2.cvtColor(img, cv2.COLOR_RGB2HSV)
im = Image.fromarray(imgH)
cv2.imwrite('hsv/imgh.png', imgH)
name1 = 'hsv/imgh.png'
imgH1 = cv2.cvtColor(imgH, cv2.COLOR_BGR2RGB)
img1 = np.copy(imgH)
#im = Image.open(name1)
x = max(im.getcolors(im.size[0] * im.size[1]))
cl = im.getcolors(im.size[0] * im.size[1])
cl1 = sorted(cl, reverse=True)
#x = cl1[3]
color1 = np.zeros([2, 2, 3])
cl = im.getcolors(im.size[0] * im.size[1])
cl1 = sorted(cl, reverse=True)
if x[1] == (255, 255, 255):
x = cl1[1]
thresh = 32
flag = 0
if (x[1][0] < 50 and x[1][1] < 50 and x[1][2] < 50) or flag == 1:
print('rgb')
color12 = meanColoring(im, thresh)
imgH = cv2.cvtColor(img, cv2.COLOR_RGB2HSV)
img21 = np.zeros([img.shape[0], img.shape[1]])
img1 = np.copy(img)
for i in range(0, img.shape[0]):
for j in range(0, img.shape[1]):
if dist1(color12, img[i, j, :]) < thresh:
img21[i, j] = 1
else:
imgH = cv2.cvtColor(img, cv2.COLOR_RGB2HSV)
im = Image.fromarray(imgH)
img1 = np.copy(imgH)
color12 = meanColoring(im, thresh)
img21 = np.zeros([img.shape[0], img.shape[1]])
for i in range(0, img.shape[0]):
for j in range(0, img.shape[1]):
if dist1(color12, imgH[i, j, :]) < thresh:
img21[i, j] = 1
model2 = enhancing(img21, 2)
###########################################Change First Color
for i in range(0, img.shape[0]):
color1[:, :, 0] = x[1][0]
color1[:, :, 1] = x[1][1]
color1[:, :, 2] = x[1][2]
plt.imshow(color1.astype(int))
plt.show()
print('rgb')
color12 = np.zeros([3])
color12[0] = x[1][0]
color12[1] = x[1][1]
color12[2] = x[1][2]
imgH = cv2.cvtColor(img, cv2.COLOR_RGB2HSV)
img21 = np.zeros([img.shape[0], img.shape[1]])
img1 = np.copy(img)
for i in range(0, img.shape[0]):
for j in range(0, img.shape[1]):
if dist1(color12, img[i, j, :]) < thresh:
img21[i, j] = 1
else:
imgH = cv2.cvtColor(img, cv2.COLOR_RGB2HSV)
im = Image.fromarray(imgH)
cv2.imwrite('hsv/imgh.png', imgH)
name1 = 'hsv/imgh.png'
imgH1 = cv2.cvtColor(imgH, cv2.COLOR_BGR2RGB)
img1 = np.copy(imgH)
#im = Image.open(name1)
x = max(im.getcolors(im.size[0] * im.size[1]))
cl = im.getcolors(im.size[0] * im.size[1])
cl1 = sorted(cl, reverse=True)
#x = cl1[3]
color1 = np.zeros([2, 2, 3])
def meaningColor(ColorCent, color_centre1):
if dist1(color_centre1[:], ColorCent[:]) < 50:
ColorCent[:] = (color_centre1[:] + ColorCent[:]) / 2
return ColorCent
