position overlay precisely in matplotlib-CodePudding

I am trying to overlay precisely one image patch to a larger patch of the image I have the coordinates where I'd like to put the patch and overlay the image but I don't know how to do with matplotlib.

I know it's possible with PILLOW (as explained

For this example it would be moving the 'red patch' into the rectangle where 'it's supposed' to be.

Here is the code that I used for that:

temp_k = img_arr[0][
    np.min(kernel[:, 1]) : np.max(kernel[:, 1]),
    np.min(kernel[:, 0]) : np.max(kernel[:, 0]),
]
temp_w = img_arr[1][
    np.min(window[:, 1]) : np.max(window[:, 1]),
    np.min(window[:, 0]) : np.max(window[:, 0]),
]
w, h = temp_k.shape[::-1]
res = cv2.matchTemplate(temp_w, temp_k, cv2.TM_CCORR_NORMED)
min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)
cv2.rectangle(temp_w, top_left, bottom_right, 255, 1)
plt.imshow(temp_w, cmap="bone")
plt.imshow(temp_k, cmap="magma", alpha=0.6)
plt.plot(max_loc[0], max_loc[1], "yo")
plt.savefig("../images/test.png")
plt.tight_layout()

Does anyone has an idea how to do that ?

Thanks in advance.

CodePudding user response：

Just as with Pillow, you need to tell Matplotlib where to place data. If you omit that, it will assume a default extent of [0,xs,ys,0], basically plotting it in the top-left corner as shown on your image.

Generating some example data:

import matplotlib.pyplot as plt
import numpy as np

n = 32
m = n // 2
o = n // 4

a = np.random.randn(n,n)
b = np.random.randn(m,m)

a_extent = [0,n,n,0]
b_extent = [o, o m, o m, o]

# a_extent = [0, 32, 32, 0]
# b_extent = [8, 24, 24, 8]

Plotting with:

fig, ax = plt.subplots(figsize=(5,5), constrained_layout=False, dpi=86, facecolor="w")

ax.imshow(a, cmap="bone", extent=a_extent)
ax.autoscale(False)

ax.imshow(b, cmap="magma", extent=b_extent)

Will result in: