Skimage斑点检测文本

Question

I am following this tutorial of Blob Detection for Text purpose and facing some issues, please check if anyone could help.

How to extract each detected blob in form of image. How i can draw a rectangle instead of circle.

from math import sqrt
from skimage import data
from skimage.feature import blob_dog, blob_log, blob_doh
from skimage.color import rgb2gray
import skimage.io as io
import matplotlib.pyplot as plt
import matplotlib.patches as patches
#from imread import imread_from_blob

image = io.imread('5.png')

#image = (data.hubble_deep_field()[0:500, 0:500])
image_gray = rgb2gray(image)

#blobs_log = blob_log(image_gray, max_sigma=30, num_sigma=10, threshold=.1)

# Compute radii in the 3rd column.
#blobs_log[:, 2] = blobs_log[:, 2] * sqrt(2)

blobs_dog = blob_dog(image_gray, max_sigma=30, threshold=.1)
#blobs_dog[:, 2] = blobs_dog[:, 2] * sqrt(2)

#blobs_doh = blob_doh(image_gray, max_sigma=30, threshold=.01)

blobs_list = [ blobs_dog]

colors = ['yellow']
titles = [ 'Difference of Gaussian']
sequence = zip(blobs_list, colors, titles)

fig, axes = plt.subplots(1, 3, figsize=(9, 3), sharex=True, sharey=True,
                         subplot_kw={'adjustable': 'box-forced'})
ax = axes.ravel()

for idx, (blobs, color, title) in enumerate(sequence):
    ax[idx].set_title(title)
    ax[idx].imshow(image, interpolation='nearest')
    for blob in blobs:
        y, x, r = blob
        c = patches.Rectangle((int(x - r),int(y - r)), int(2*r), int(2*r),linewidth=2,edgecolor=color,facecolor='none')

        ax[idx].add_patch(c)
    ax[idx].set_axis_off()
    croppedImage = image[int(x-r):int(x+r),int(y-r):int(y+r)]
    if croppedImage.shape[0] > 0 and croppedImage.shape[1] > 0:
        io.imsave('C:/Users/A/Projects/Image/Test/test.png', croppedImage)
plt.tight_layout()
plt.show()

http://scikit-image.org/docs/dev/auto_examples/features_detection/plot_blob.html

Answer 1

First, to draw a rectangle you need to put the following import statement on top:

import matplotlib.patches as patches
from skimage import io

next change the line that draws the circles:

c = plt.Circle((x, y), r, color=color, linewidth=2, fill=False)

to a line drawing rectangles:

c = patches.Rectangle((int(x - r),int(y - r)), int(2*r), int(2*r),linewidth=2,edgecolor=color,facecolor='none')

This will create a rectangle (actually a square) with top left vertex at (x - r,y - r) and of width and height of 2*r. here r is the standard deviation of the blur used while detecting the blob.

Now to extract the image within the blob:

croppedImage = image[int(x-r):int(x+r),int(y-r):int(y+r)]
if croppedImage.shape[0] > 0 and croppedImage.shape[1] > 0:
    io.imsave('letter_image.png', croppedImage)

Change first argument as any path (including desired image name).

• Note I have not tested the above code so the crop could have reverse coordinates, also check the coordinates of the rectangle.

Full working code looks like below:

from math import sqrt
from skimage import data
from skimage.feature import blob_dog, blob_log, blob_doh
from skimage.color import rgb2gray
import skimage.io as io
import matplotlib.pyplot as plt
import matplotlib.patches as patches
#from imread import imread_from_blob

image = io.imread('5.png')

# image = (data.hubble_deep_field()[0:500, 0:500])
image_gray = rgb2gray(image)

# blobs_log = blob_log(image_gray, max_sigma=30, num_sigma=10, threshold=.1)

# Compute radii in the 3rd column.
#blobs_log[:, 2] = blobs_log[:, 2] * sqrt(2)

blobs_dog = blob_dog(image_gray, max_sigma=30, threshold=.1)
#blobs_dog[:, 2] = blobs_dog[:, 2] * sqrt(2)

#blobs_doh = blob_doh(image_gray, max_sigma=30, threshold=.01)

blobs_list = [ blobs_dog]

colors = ['yellow']
titles = [ 'Difference of Gaussian']
sequence = zip(blobs_list, colors, titles)

fig, axes = plt.subplots(1, 3, figsize=(9, 3), sharex=True, sharey=True,
                         subplot_kw={'adjustable': 'box-forced'})
ax = axes.ravel()

for idx, (blobs, color, title) in enumerate(sequence):
    ax[idx].set_title(title)
    ax[idx].imshow(image, interpolation='nearest')
    for i,blob in enumerate(blobs):
        y, x, r = blob
        c = patches.Rectangle((int(x - r),int(y - r)), int(2*r), int(2*r),linewidth=2,edgecolor=color,facecolor='none')
        croppedImage = image[int(x-r):int(x+r),int(y-r):int(y+r)]
        if croppedImage.shape[0] > 0 and croppedImage.shape[1] > 0:
            io.imsave('C:/Users/A/Projects/Image/Test/test'+str(i)+'.png', croppedImage)

Answer 2

Instead of

c = plt.Circle((x, y), r, color=color, linewidth=2, fill=False)

You will need to do a little more complicated routine using patches, here is a complete example of drawing a rectangle on an image. The specific line in here you are interested in is:

rect = patches.Rectangle((50,100),40,30,linewidth=1,edgecolor='r',facecolor='none')

Complete Example, taken from here :

import matplotlib.pyplot as plt
import matplotlib.patches as patches
from PIL import Image
import numpy as np

im = np.array(Image.open('stinkbug.png'), dtype=np.uint8)

# Create figure and axes
fig,ax = plt.subplots(1)

# Display the image
ax.imshow(im)

# Create a Rectangle patch
rect = patches.Rectangle((50,100),40,30,linewidth=1,edgecolor='r',facecolor='none')

# Add the patch to the Axes
ax.add_patch(rect)

plt.show()