获取文本边界框,与后端无关
我想在一个matplotlib图形中获取一些文本周围的边界框(尺寸)。在这篇帖子这里,我了解到可以使用方法text.get_window_extent(renderer)
来获取边界框,但我需要提供正确的渲染器。有些后端没有方法figure.canvas.get_renderer()
,所以我尝试了matplotlib.backend_bases.RendererBase()
来获取渲染器,但结果不太理想。下面是一个简单的例子:
import matplotlib as mpl
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle
fig = plt.figure()
ax = plt.subplot()
txt = fig.text(0.15,0.5,'afdjsklhvvhwd', fontsize = 36)
renderer1 = fig.canvas.get_renderer()
renderer2 = mpl.backend_bases.RendererBase()
bbox1 = txt.get_window_extent(renderer1)
bbox2 = txt.get_window_extent(renderer2)
rect1 = Rectangle([bbox1.x0, bbox1.y0], bbox1.width, bbox1.height, \
color = [0,0,0], fill = False)
rect2 = Rectangle([bbox2.x0, bbox2.y0], bbox2.width, bbox2.height, \
color = [1,0,0], fill = False)
fig.patches.append(rect1)
fig.patches.append(rect2)
plt.draw()
这个例子生成了以下图表:
很明显,红色的框太小了。我觉得Paul的回答这里也发现了同样的问题。黑色的框看起来不错,但我无法使用MacOSX后端,或者其他没有方法figure.canvas.get_renderer()
的后端。
如果这有帮助,我的系统是Mac OS X 10.8.5,Matplotlib 1.3.0,Python 2.7.5。
3 个回答
Figure
对象中的_get_renderer()
方法给我的结果很满意:
from matplotlib.figure import Figure
import matplotlib.pyplot as plt
fig1, ax1 = plt.subplots()
plotted_text = ax1.text(0.5, 0.5, "afdjsklhvvhwd")
renderer1 = fig1.canvas.get_renderer()
bb1 = plotted_text.get_window_extent(renderer=renderer1).transformed(ax1.transData.inverted())
text_width1 = bb1.width
fig2 = Figure()
ax2 = fig2.subplots()
plotted_text2 = ax2.text(0.5, 0.5, "afdjsklhvvhwd")
renderer2 = fig2._get_renderer()
bb2 = plotted_text2.get_window_extent(renderer=renderer2).transformed(ax2.transData.inverted())
text_width2 = bb2.width
如果你想要获取一个旋转文本区域的紧凑边界框,这里有一个可能的解决方案。
# generate text layer
def text_on_canvas(text, myf, ro, margin = 1):
axis_lim = 1
fig = plt.figure(figsize = (5,5), dpi=100)
plt.axis([0, axis_lim, 0, axis_lim])
# place the left bottom corner at (axis_lim/20,axis_lim/20) to avoid clip during rotation
aa = plt.text(axis_lim/20.,axis_lim/20., text, ha='left', va = 'top', fontproperties = myf, rotation = ro, wrap=True)
plt.axis('off')
text_layer = fig2img(fig) # convert to image
plt.close()
we = aa.get_window_extent()
min_x, min_y, max_x, max_y = we.xmin, 500 - we.ymax, we.xmax, 500 - we.ymin
box = (min_x-margin, min_y-margin, max_x+margin, max_y+margin)
# return coordinates to further calculate the bbox of rotated text
return text_layer, min_x, min_y, max_x, max_y
def geneText(text, font_family, font_size, style):
myf = font_manager.FontProperties(fname=font_family, size=font_size)
ro = 0
if style < 8: # rotated text
# no rotation, just to get the minimum bbox
htext_layer, min_x, min_y, max_x, max_y = text_on_canvas(text, myf, 0)
# actual rotated text
ro = random.randint(0, 90)
M = cv2.getRotationMatrix2D((min_x,min_y),ro,1)
# pts is 4x3 matrix
pts = np.array([[min_x, min_y, 1],[max_x, min_y, 1],[max_x, max_y, 1],[min_x, max_y,1]]) # clockwise
affine_pts = np.dot(M, pts.T).T
#print affine_pts
text_layer, _, _, _, _ = text_on_canvas(text, myf, ro)
visualize_points(htext_layer, pts)
visualize_points(text_layer, affine_pts)
return text_layer
else:
raise NotImplementedError
fonts = glob.glob(fonts_path + '/*.ttf')
ret = geneText('aaaaaa', fonts[0], 80, 1)
结果看起来是这样的:第一个是没有旋转的,第二个是旋转后的文本区域。完整的代码片段可以在这里找到。
这是我的解决方案/小技巧。@tcaswell建议我看看matplotlib是如何处理保存图形的,特别是紧凑的边界框。我在Github上找到了backend_bases.py的代码,它是通过将图形保存到一个临时文件对象来获取缓存中的渲染器。我把这个小技巧变成了一个小函数,如果后端支持,就使用内置的方法get_renderer()
,否则就使用保存方法。
def find_renderer(fig):
if hasattr(fig.canvas, "get_renderer"):
#Some backends, such as TkAgg, have the get_renderer method, which
#makes this easy.
renderer = fig.canvas.get_renderer()
else:
#Other backends do not have the get_renderer method, so we have a work
#around to find the renderer. Print the figure to a temporary file
#object, and then grab the renderer that was used.
#(I stole this trick from the matplotlib backend_bases.py
#print_figure() method.)
import io
fig.canvas.print_pdf(io.BytesIO())
renderer = fig._cachedRenderer
return(renderer)
这是使用find_renderer()
和我原始示例中稍微修改过的代码得到的结果。使用支持get_renderer()
方法的TkAgg后端,我得到了:
而使用不支持get_renderer()
方法的MacOSX后端,我得到了:
显然,使用MacOSX后端的边界框并不是完美的,但比我最初问题中的红框要好得多。