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本博客所包含的大致内容: 图片某一局部放大并置于图形内部;图片多个局部放大并拼接在原图侧面。
为什么要局部放大?无论的图像生成、修复、去污等等,如生成对抗方法;亦或是图像分割,如unet。对于方法的结果都需要进行有效的展示,凸显方法的优越性能,往往细节的部分才是我们所更加关注的。但往往在图像本身很难观察到这些细节,因此有意识的将需要的局部放大是展示效果的有效方法。
思路也简单,首先获取到需要关注的部分,然后在将其进行插值放大,最后放在原图的某一位置即可。
本函数参数传入图像,需要目标区域的指标,其次放在的位置,支持四个角以及中心,以及放大的倍数。
目标区域为矩形,长宽比任意。
def Partial_magnification(pic, target, location='lower_right', ratio=1):
'''
:param pic: input pic
:param target: Intercept area, for example [target_x, target_y, target_w, target_h]
:param location: lower_right,lower_left,top_right,top_left,center
:param ratio: gain
:return: oringal pic, pic
'''
img = copy.copy(pic)
w, h = pic.shape[1], pic.shape[0],
target_x, target_y = target[0], target[1]
target_w, target_h = target[2], target[3]
cv2.rectangle(pic, (target_x, target_y), (target_x + target_w, target_y + target_h), (255, 255, 0), 2)
new_pic = pic[target_y:target_y + target_h, target_x:target_x + target_w]
new_pic = cv2.resize(new_pic, (target_w*ratio, target_h*ratio), interpolation=cv2.INTER_CUBIC)
if location == 'lower_right':
pic[h-1-target_h*ratio:h-1, w-1-target_w*ratio:w-1] = new_pic
cv2.line(pic, (target_x + target_w, target_y + target_h), (w-1-target_w*ratio, h-1-target_h*ratio), (255, 0, 0),2)
elif location == 'lower_left':
pic[h-1-target_h*ratio:h-1, 0:target_w*ratio] = new_pic
elif location == 'top_right':
pic[0:target_h*ratio, w-1-target_w*ratio:w-1] = new_pic
elif location == 'top_left':
pic[0:target_h*ratio, 0:target_w*ratio] = new_pic
elif location == 'center':
pic[int(h/2-target_h*ratio/2):int(h/2+target_h*ratio/2),
int(w/2-target_w*ratio/2):int(w/2+target_w*ratio/2)] = new_pic
return img, pic
当存在多个局部需要放大时,若都置于原图内部,遮挡图片内容的可能性较大,因此将其置于图像侧面。
本函数仅支持两个局部区域放大。和第一个函数不同的是两个局部放大的区域长宽比需要一致,为了方便拼接。没有设置放大倍数,默认局部放大后拼接图片与原图等高。
def Partial_magnification_2(pic, target1, target2, *args):
'''
:param pic: input pic
:param target: Intercept area, for example [target_x, target_y, target_w, target_w]
:param location: lower_right,lower_left,top_right,top_left,center
:param ratio: gain
:return: oringal pic, pic
'''
# imgg = copy.copy(pic)
w, h = pic.shape[1], pic.shape[0],
assert target1[0]+target1[2] < w and target1[1]+target1[3] < h,\
'The target1 area is too large and exceeds the image size'
assert target2[0]+target2[2] < w and target2[1]+target2[3] < h,\
'The target2 area is too large and exceeds the image size'
assert target1[2] > 10 or target1[3] > 10, \
'The target1 area is too small, not recommended'
assert target2[2] > 10 or target2[3] > 10, \
'The target2 area is too small, not recommended'
assert target1[0] > 0 and target1[0] < w, \
'The starting point of the target1 area is beyond the scope of the image'
assert target2[0] > 0 and target2[0] < w, \
'The starting point of the target2 area is beyond the scope of the image'
if target2[2] / target2[3] == target1[2] / target1[3]: #
R = target2[2]/target2[3]
if target1[1] > target2[1]:
target1_x, target1_y = target2[0], target2[1]
target1_w, target1_h = target2[2], target2[3]
target2_x, target2_y = target1[0], target1[1]
target2_w, target2_h = target1[2], target1[3]
else:
target1_x, target1_y = target1[0], target1[1]
target1_w, target1_h = target1[2], target1[3]
target2_x, target2_y = target2[0], target2[1]
target2_w, target2_h = target2[2], target2[3]
cv2.rectangle(pic, (target1_x, target1_y), (target1_x + target1_w, target1_y + target1_h), (255, 250, 255), 2)
cv2.rectangle(pic, (target2_x, target2_y), (target2_x + target2_w, target2_y + target2_h), (255, 252, 255), 2)
new_pic1 = pic[target1_y:target1_y + target1_h, target1_x:target1_x + target1_w]
new_pic1 = cv2.resize(new_pic1, (int(h//2 * R), h//2), cv2.INTER_CUBIC)
new_pic2 = pic[target2_y:target2_y + target2_h, target2_x:target2_x + target2_w]
new_pic2 = cv2.resize(new_pic2, (int(h//2 * R), h//2))
img = np.zeros((h, int(h//2 * R), 3), np.uint8)
img[0:h//2, 0:int(h//2 * R)] = new_pic1
img[h//2:h, 0:int(h//2 * R)] = new_pic2
hmerge = np.hstack((pic, img))
cv2.line(hmerge, (target1_x + target1_w, target1_y), (w, 0), (255, 255, 255), 2)
cv2.line(hmerge, (target2_x + target2_w, target2_y + target2_h), (w, h), (255, 255, 255), 2)
return hmerge
else:
raise ValueError('Make sure the aspect ratio of target is consistent !')
为方便复现提供了参考的主程序,如果需要批量放大,添加循环即可。
if __name__ == '__main__':
img = cv2.imread(r'./test/Image_11L.jpg')
target1 = [250, 250, 100, 100]
pic, pic1 = Partial_magnification(img, target1, location='lower_right', ratio=4)
target2 = [180, 400, 100, 50]
pic, pic2 = Partial_magnification(pic, target2, location='lower_left', ratio=2)
hmerge = np.hstack((pic1, pic2))
if max(hmerge.shape[0], hmerge.shape[1]) > 1000:
# cv2.namedWindow('merge', 0)
# cv2.resizeWindow('merge', 1000, int(1000*hmerge.shape[0]/hmerge.shape[1]))
# cv2.imshow('merge', hmerge)
# cv2.waitKey(0)
# cv2.destroyAllWindows()
hmerge = cv2.cvtColor(hmerge, cv2.COLOR_BGR2RGB)
fig = plt.figure(figsize=(40, 20)) # figsize 尺寸
plt.imshow(hmerge)
plt.savefig('aaa_bbb.png', dpi=200) # dpi分辨率
plt.show()
else:
plt.imshow(hmerge)
plt.show()
if __name__ == '__main__':
img = cv2.imread(r'./test/Image_11L.jpg')
target1 = [250, 650, 100, 100]
target2 = [450, 400, 100, 100]
pic1 = Partial_magnification_2(img, target1, target2)
hmerge = cv2.cvtColor(pic1, cv2.COLOR_BGR2RGB)
fig = plt.figure(figsize=(30, 20))
fig.patch.set_facecolor('gray')
plt.imshow(hmerge)
plt.savefig('aaa_bbb.png', dpi=300, bbox_inches='tight')
plt.show()
以下是两个函数的测试结果,主程序如上。
上述的目标的指定放大的区域全靠大致位置加不断调整,使得绘图不够直观的准确,今添加选取指定区域的方法,利用opencv 直接直观的选取指定区域。
def on_EVENT_change(event, x, y, flags, param):
if event == cv2.EVENT_LBUTTONDOWN:
point.append((x, y))
target.append((x, y))
xy = "%d,%d" % (x, y)
cv2.circle(copyImg, (x, y), 1, (255, 0, 0), thickness=-1)
cv2.putText(copyImg, xy, (x, y), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1.0, (0, 0, 0), thickness=1)
cv2.imshow("image", copyImg)
elif event == cv2.EVENT_LBUTTONUP:
point.append((x, y))
target.append((x, y))
xy = "%d,%d" % (x, y)
cv2.rectangle(copyImg, point[0], point[1], (0, 255, 0), thickness=1, lineType=8, shift=0)
cv2.circle(copyImg, (x, y), 1, (255, 0, 0), thickness=-1)
cv2.putText(copyImg, xy, (x, y), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1.0, (255, 0, 0), thickness=1)
cv2.imshow("image", copyImg)
point.clear()
elif event == cv2.EVENT_RBUTTONDOWN:
cv2.imshow("image", img)
cv2.setMouseCallback("image", on_EVENT_LBUTTONDOWN)
def on_EVENT_LBUTTONDOWN(event, x, y, flags, param):
if event == cv2.EVENT_LBUTTONDOWN:
point.append((x, y))
target.append((x, y))
xy = "%d,%d" % (x, y)
cv2.circle(img, (x, y), 1, (255, 0, 0), thickness=-1)
cv2.putText(img, xy, (x, y), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1.0, (0, 0, 0), thickness=1)
cv2.imshow("image", img)
elif event == cv2.EVENT_LBUTTONUP:
point.append((x, y))
target.append((x, y))
xy = "%d,%d" % (x, y)
cv2.rectangle(img, point[0], point[1], (0, 255, 0), thickness=1, lineType=8, shift=0)
cv2.circle(img, (x, y), 1, (255, 0, 0), thickness=-1)
cv2.putText(img, xy, (x, y), cv2.FONT_HERSHEY_COMPLEX_SMALL, 1.0, (255, 0, 0), thickness=1)
cv2.imshow("image", img)
point.clear()
elif event == cv2.EVENT_RBUTTONDOWN:
cv2.imshow("image", copyImg)
cv2.setMouseCallback("image", on_EVENT_change)
if __name__ == '__main__': #Partial_magnification
# point、target、img、"image"不能修改,和前文定义函数绑定
point = []
target = []
path = "xxx.jpg"
img = cv2.imread(path)
copyImg = copy.deepcopy(img)
cv2.namedWindow("image")
cv2.setMouseCallback("image", on_EVENT_LBUTTONDOWN)
cv2.imshow("image", img)
cv2.waitKey(0)
cv2.destroyAllWindows()
location = ['top_left', 'top_right', 'lower_right', 'lower_left', 'center']
img = cv2.imread(path) # C:\Users\Administrator\Desktop\dd.jpg
for i in range(len(target)//2):
if target[2*i+1][0]-target[2*i][0]>0:
target1 = [target[2*i][0], target[2*i][1], target[2*i+1][0]-target[2*i][0], target[2*i+1][1]-target[2*i][1]]
else:
raise ValueError('请从左往右,从下往上 框取区域')
if i == 0:
pic, pic1 = Partial_magnification(img, target1, location=location[i], ratio=2)
else:
pic, pic1 = Partial_magnification(pic, target1, location=location[i], ratio=2)
fig = plt.figure(figsize=(20, 20)) # figsize 尺寸
plt.imshow(cv2.cvtColor(pic, cv2.COLOR_BGR2RGB))
plt.savefig('xxx.png', dpi=300, bbox_inches='tight') # dpi 分辨率
plt.show()
cv2上选取区域需要从左往右,从下往上 框取区域(局部放大函数的限制),最多五个区域(放大后的区域选项决定。如果选取区域在一个图相交,影响选取时右键使用备份绘制。
以上就是本文的主要内容,都是OpenCV和plt的基本使用上实现图像的局部放大。
2022.10.17 : 添加目标区域选取的方法
欲尽善本文,因所视短浅,怎奈所书皆是瞽言蒭议。行文至此,诚向予助与余者致以谢意。