Vector field color coding

Demonstration of colormap application to a vector field.

Pyimof provides the pyimof.display.plot() that displays a color mapping applyed to a dense vector field according to its orientation and magnitude. Any circular colormap can be applyed. Matplotlib provides some of them by default: hsv, twilight, twilight_shifted, hsv_r, twilight_r, twilight_shifted_r.

If no colormap is provided to the pyimof.display.plot() function, the fector field color coding is made by constructing a HSV image in which the hue is the orientation of the vector flow and the value is its magnitude. The saturation is set to 1.

Pyimof defines the middlebury matplotlib colormap that is inspired by the color coding introduced by the Middlebury optical flow evaluation website for displaying algorithms results. Its reverse version middlebury_r is also provided.

import matplotlib.pyplot as plt
import pyimof

# --- Load the Hydrangea sequence

I0, I1 = pyimof.data.dogdance()

# --- Estimate the optical flow

u, v = pyimof.solvers.ilk(I0, I1)

# --- Display it with different colormaps

fig = plt.figure(figsize=((9, 10)))
ax_arr = fig.subplots(3, 2, True, True)
fig.tight_layout()

ax0, ax1 = ax_arr[0, :]

ax0.imshow(I0, cmap='gray')
ax0.set_axis_off()
ax0.set_title("Reference image")

pyimof.display.plot(u, v, ax=ax1, cmap=None)
ax1.set_title("Vector field to HSV image")

cmap_list = ['middlebury', 'hsv', 'twilight', 'twilight_shifted']

for ax, cm in zip(ax_arr[1:, :].ravel(), cmap_list):
    pyimof.display.plot(u, v, ax=ax, cmap=cm)
    ax.set_title(f"'{cm}' colormap")

plt.show()