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patches.Scatter() and patches.Plot() should be added. #29318
Description
Problem
Only using patches.Rectangle() of plt.subplots() works properly as shown below:
from torchvision.datasets import CelebA
my_data = CelebA(
root="data",
split="all",
target_type=["bbox", "landmarks"]
)
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle
fig, axes = plt.subplots(nrows=2, ncols=5, figsize=(12, 6))
for (im, ((x, y, w, h), lm)), axis in zip(my_data, axes.ravel()):
axis.imshow(X=im)
rect = Rectangle(xy=(x, y), width=w, height=h, linewidth=3, edgecolor='r', facecolor='none', clip_on=True) # Here
axis.add_patch(p=rect) # Here
And only using axes.Axes.scatter() of plt.subplots() works properly as shown below:
from torchvision.datasets import CelebA
import torchvision
my_data = CelebA(
root="data",
split="all",
target_type=["bbox", "landmarks"]
)
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle
from matplotlib.patches import Circle
fig, axes = plt.subplots(nrows=2, ncols=5, figsize=(12, 6))
for (im, ((x, y, w, h), lm)), axis in zip(my_data, axes.ravel()):
axis.imshow(X=im)
for px, py in lm.split(2): # Here
axis.scatter(x=px, y=py, c='#1f77b4') # Here
And only using axes.Axes.plot() of plt.subplots() works properly as shown below:
from torchvision.datasets import CelebA
import torchvision
my_data = CelebA(
root="data",
split="all",
target_type=["bbox", "landmarks"]
)
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle
from matplotlib.patches import Circle
fig, axes = plt.subplots(nrows=2, ncols=5, figsize=(12, 6))
for (im, ((x, y, w, h), lm)), axis in zip(my_data, axes.ravel()):
axis.imshow(X=im)
px = [] # Here
py = [] # Here
for j, v in enumerate(lm): # Here
if j%2 == 0: # Here
px.append(v) # Here
else: # Here
py.append(v) # Here
axis.plot(px, py) # Here
But using patches.Rectangle() of plt.subplots() with axes.Axes.scatter() of plt.subplots() doesn't work properly as shown below:
from torchvision.datasets import CelebA
my_data = CelebA(
root="data",
split="all",
target_type=["bbox", "landmarks"]
)
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle
fig, axes = plt.subplots(nrows=2, ncols=5, figsize=(12, 6))
for (im, ((x, y, w, h), lm)), axis in zip(my_data, axes.ravel()):
axis.imshow(X=im)
rect = Rectangle(xy=(x, y), width=w, height=h, linewidth=3, edgecolor='r', facecolor='none', clip_on=True) # Here
axis.add_patch(p=rect) # Here
for px, py in lm.split(2): # Here
axis.scatter(x=px, y=py, c='#1f77b4') # Here
And using patches.Rectangle() of plt.subplots() with axes.Axes.plot() of plt.subplots() doesn't work properly as shown below:
from torchvision.datasets import CelebA
my_data = CelebA(
root="data",
split="all",
target_type=["bbox", "landmarks"]
)
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle
fig, axes = plt.subplots(nrows=2, ncols=5, figsize=(12, 6))
for (im, ((x, y, w, h), lm)), axis in zip(my_data, axes.ravel()):
axis.imshow(X=im)
rect = Rectangle(xy=(x, y), width=w, height=h, linewidth=3, edgecolor='r', facecolor='none', clip_on=True) # Here
axis.add_patch(p=rect) # Here
px = [] # Here
py = [] # Here
for j, v in enumerate(lm): # Here
if j%2 == 0: # Here
px.append(v) # Here
else: # Here
py.append(v) # Here
axis.plot(px, py) # Here
So instead, I used patches.Rectangle() of plt.subplots() with patches.Circle() of plt.subplots(), then they properly work as shown below:
from torchvision.datasets import CelebA
my_data = CelebA(
root="data",
split="all",
target_type=["bbox", "landmarks"]
)
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle
from matplotlib.patches import Circle
fig, axes = plt.subplots(nrows=2, ncols=5, figsize=(12, 6))
for (im, ((x, y, w, h), lm)), axis in zip(my_data, axes.ravel()):
axis.imshow(X=im)
rect = Rectangle(xy=(x, y), width=w, height=h, linewidth=3, edgecolor='r', facecolor='none', clip_on=True) # Here
axis.add_patch(p=rect) # Here
for px, py in lm.split(2): # Here
axis.add_patch(p=Circle(xy=(px, py))) # Here
Proposed solution
So, it seems like matplotlib.patches works with matplotlib.patches so patches.Scatter() and patches.Plot() should be added.
Activity
jklymak commentedon Dec 15, 2024
They are all working the same, just scatter is calling autolim, and add_patch is not.
timhoffm commentedon Dec 17, 2024
What is happening:
Axes.dataLim) to include the Patch, but doesn't touch the view limits (Axes.viewLim).scatter()is a high-level function that additionally updates the view limits based on the data limits (essentially through a lazyautoscale_view()), which then picks up the rectangle limits as well.If you want to have limits exactly on the image, no matter what you plot afterwards you should call
ax.autoscale(False)afterax.imshow().timhoffm commentedon Dec 17, 2024
I'm closing as the solution for the present case is to deactivate autoscaling.
Independent of this, there are some ideas how to change/improve autoscaling. These are independently tracked, e.g. in