如何基于类上的grabcut面膜中的颜色更改颜色

发布于 2025-01-30 05:00:14 字数 804 浏览 1 评论 0原文

这是我的图像：

“在此处输入图像说明”

我有2类狗和卡车，我也有他们的bbox坐标，所以我想创建此图像的掩码，所以我应用了grapcut算法，这是我的代码

img=cv2.imread('dog.jpg')
mask=np.zeros(img.shape[:2],np.uint8)

bgModel=np.zeros((1,65),np.float64)
fgModel=np.zeros((1,65),np.float64)
tmpimage=image
masks=[]
for i in recs:
    cv2.grabCut(img,mask,i,bgModel,fgModel,10,cv2.GC_INIT_WITH_RECT)
    mask2=np.where((mask==2)|(mask==0),0,1).astype('uint8')
    masks.append(mask2)
    #img=image*mask2[:,:,np.newaxis]
finalmask=np.zeros(img.shape[:2],np.uint8)
for i in range(len(masks)):
   finalmask=finalmask+masks[i]
plt.imshow(finalmask)
# plt.colorbar()
#plt.xticks([]),plt.yticks([])
plt.show()

这是最终掩码：

，做我希望狗的区域具有与卡车区域不同的颜色，这两个图像都具有相同的黄色

原文

here's my image:

enter image description here

i have 2 classes dog and truck i also have their bbox coordinates so i want to create a mask for this image so i applied grapcut algorithm here's my code

img=cv2.imread('dog.jpg')
mask=np.zeros(img.shape[:2],np.uint8)

bgModel=np.zeros((1,65),np.float64)
fgModel=np.zeros((1,65),np.float64)
tmpimage=image
masks=[]
for i in recs:
    cv2.grabCut(img,mask,i,bgModel,fgModel,10,cv2.GC_INIT_WITH_RECT)
    mask2=np.where((mask==2)|(mask==0),0,1).astype('uint8')
    masks.append(mask2)
    #img=image*mask2[:,:,np.newaxis]
finalmask=np.zeros(img.shape[:2],np.uint8)
for i in range(len(masks)):
   finalmask=finalmask+masks[i]
plt.imshow(finalmask)
# plt.colorbar()
#plt.xticks([]),plt.yticks([])
plt.show()

here's the final mask:

enter image description here

what i want to do is i want the area of the dog to have different color than area of the truck in this image both are having the same yellow color

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妖妓 2025-02-06 05:00:14

在您的情况下，finalmask是一个2通道图像。您从plt.imshow（finalMask）获得的输出是二进制图像，其中黄色 - ＆gt; 255和紫色 - ＆gt; 0。

我为每个掩码创建了一个带有3通道的掩码，并为每个掩码分配了随机颜色。

代码：

# creating 3-channel mask:
finalmask = np.zeros(img.shape, np.uint8)

for i in range(len(masks)):
    # generating random color 
    # plucked from: https://stackoverflow.com/questions/28999287/generate-random-colors-rgb
    color = tuple(np.random.choice(range(256), size=3))

    # create another mask to place color in white regions
    im = np.zeros(img.shape, np.uint8)
    im[masks[i] == 255] = color

    # add with final mask
    finalmask = finalmask + im

结果：

在这里我创建的样品掩码：

＆amp;

最终结果：

注意： 如果要为每个蒙版标签进行固定颜色，则可以创建一个字典并从中参考。

In your case finalmask is a 2-channel image. The output you get from plt.imshow(finalmask) is a binary image where yellow -> 255 and purple -> 0.

I have created a mask with 3-channels and assigned random colors for each mask.

Code:

# creating 3-channel mask:
finalmask = np.zeros(img.shape, np.uint8)

for i in range(len(masks)):
    # generating random color 
    # plucked from: https://stackoverflow.com/questions/28999287/generate-random-colors-rgb
    color = tuple(np.random.choice(range(256), size=3))

    # create another mask to place color in white regions
    im = np.zeros(img.shape, np.uint8)
    im[masks[i] == 255] = color

    # add with final mask
    finalmask = finalmask + im

Results:

Here sample masks I created: