This is because of the type used, I just had this problem and solved it by specifying a dtype for my dataframe. In your similarities.info() seaborn wants to see DType:'float64' or another number type.

similarities = pd.DataFrame(..., dtype="float")

As pointed in the comments, using square=False with figsize=(30, 15) fixed the problem.

It is possible to return a value of type None, check the type of X_train in the following lines:

CopyX_train = X_train.resize((32, 32))
type(X_train)    
X_train = X_train.reshape((len(X_train), 3, 32, 32))
type(X_train)

Check this code:

import numpy as np
np.random.seed(0)
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
from scipy.signal import correlate
import seaborn as sns
sns.set()

img = np.load('img.npy')
act = np.load('act.npy')

result = correlate(img, act, mode = 'same')

def updatefig(sl):
    ax.cla()
    print(sl + 1, ' / ', result.shape[2])
    sns.heatmap(result[..., sl], cbar = False)
    ax.set_title("frame {}".format(sl + 1))
    ax.axis('off')

fig, ax = plt.subplots()
ani = FuncAnimation(fig, updatefig, frames = result.shape[2], interval = 5)

plt.show()

which gives me this animation (I halved the animation reported below to reduce the file size under 2 MB, the code above reproduce all 40 frames):

EDIT

In order to add a fixed colorbar to the heatmap, check this code:

import numpy as np
np.random.seed(0)
import matplotlib.pyplot as plt
from matplotlib.animation import FuncAnimation
from scipy.signal import correlate
import seaborn as sns
sns.set()

img = np.load('img.npy')
act = np.load('act.npy')

result = correlate(img, act, mode = 'same')

def updatefig(sl):
    ax.cla()
    print(sl + 1, ' / ', result.shape[2])
    sns.heatmap(result[..., sl],
                ax = ax,
                cbar = True,
                cbar_ax = cbar_ax,
                vmin = result.min(),
                vmax = result.max())
    ax.set_title("frame {}".format(sl + 1))
    ax.axis('off')

grid_kws = {'width_ratios': (0.9, 0.05), 'wspace': 0.2}
fig, (ax, cbar_ax) = plt.subplots(1, 2, gridspec_kw = grid_kws, figsize = (10, 8))
ani = FuncAnimation(fig, updatefig, frames = result.shape[2], interval = 5)

plt.show()

which produces this animation (cut as the previous one):