def animate(i):
print(i)
try:
cent, img, msk = next(data)
image_ax.set_data(img)
mask_ax.set_data(msk)
x_coord, y_coord = parse_centroid_coords(cent)
if len(cent) > 1:
single_droplet_1.set_data([], [])
single_droplet_2.set_data([], [])
multi_droplet_1.set_data(x_coord, y_coord)
multi_droplet_2.set_data(x_coord, y_coord)
elif len(cent) == 1:
single_droplet_1.set_data(x_coord, y_coord)
single_droplet_2.set_data(x_coord, y_coord)
multi_droplet_1.set_data([], [])
multi_droplet_2.set_data([], [])
else:
single_droplet_1.set_data([], [])
single_droplet_2.set_data([], [])
multi_droplet_1.set_data([], [])
multi_droplet_2.set_data([], [])
plt.title(f'Frame {i}')
return image_ax, mask_ax, single_droplet_1, multi_droplet_1, single_droplet_2, multi_droplet_2,
except StopIteration as error:
print(error)
def animate_centroids(save=False):
'''
Saves animation of original image with markers for the centroids of each droplet.
Kwargs:
save {bool} -- wether to save the animation as a .mp4 or show it using plt.show().
'''
def centroid_img_generator():
for cent, image in zip(CENTROIDS, IMAGES):
yield cent, image
data = centroid_img_generator()
cent, img = next(data)
x_coord, y_coord = parse_centroid_coords(cent)
fig = plt.figure()
with sns.axes_style('dark'):
axes = plt.axes()
image_ax = axes.imshow(img)
if len(cent) > 1:
single_droplet, = axes.plot([], [], 'k.')
multi_droplet, = axes.plot(x_coord, y_coord, 'rx')
elif len(cent) == 1:
single_droplet, = axes.plot(x_coord, y_coord, 'k.')
multi_droplet, = axes.plot([], [], 'rx')
else:
single_droplet, = axes.plot([], [], 'k.')
multi_droplet, = axes.plot([], [], 'rx')
plt.show()
def animate(i):
try:
cent, img = next(data)
image_ax.set_data(img)
x_coord, y_coord = parse_centroid_coords(cent)
if len(cent) > 1:
single_droplet.set_data([], [])
multi_droplet.set_data(x_coord, y_coord)
elif len(cent) == 1:
single_droplet.set_data(x_coord, y_coord)
multi_droplet.set_data([], [])
else:
single_droplet.set_data([], [])
multi_droplet.set_data([], [])
plt.title(f'Frame #{i}')
return image_ax, single_droplet, multi_droplet,
except StopIteration as error:
print(error)
ani = FuncAnimation(fig, animate, save_count=N_FRAMES-1)
if save:
ani.save(os.path.join('Output', 'Videos',
f'centroids_{DATASET.lower()}.mp4'), writer=WRITER)
else:
plt.show()
def animate(i):
try:
cent, img = next(data)
image_ax.set_data(img)
x_coord, y_coord = parse_centroid_coords(cent)
if len(cent) > 1:
single_droplet.set_data([], [])
multi_droplet.set_data(x_coord, y_coord)
elif len(cent) == 1:
single_droplet.set_data(x_coord, y_coord)
multi_droplet.set_data([], [])
else:
single_droplet.set_data([], [])
multi_droplet.set_data([], [])
plt.title(f'Frame #{i}')
return image_ax, single_droplet, multi_droplet,
except StopIteration as error:
print(error)
def plot_centroids(num, save=False):
'''
Plots a specific frame of a video and overlays the predicted centroid.
Args:
num {int} -- mumber of the frame to plot.
Kwargs:
save {bool} -- wether to save the plot as .pgf file or to show using plt.show().
'''
cent = CENTROIDS[num]
x_coord, y_coord = parse_centroid_coords(cent)
image = Image.fromarray(IMAGES[num])
mask = Image.fromarray(MASKS[num])
img_mask = get_concat_h(image, mask)
with sns.axes_style('dark'):
fig, axes = plt.subplots(1, 1, figsize=set_size(
width_pt=440, aspect_ratio=.42))
axes.set_xticks([])
axes.set_yticks([])
axes.set_title(f'Frame {num}')
axes.imshow(img_mask)
if len(cent) > 1:
axes.scatter(x_coord, y_coord, s=10, marker='x', color='r')
axes.scatter([x+IMAGES.shape[2] for x in x_coord],
y_coord, s=10, marker='x', color='r')
elif len(cent) == 1:
axes.scatter(x_coord, y_coord, s=10, marker='.', color='k')
axes.scatter([x+IMAGES.shape[2] for x in x_coord],
y_coord, s=10, marker='.', color='k')
if save:
os.makedirs(os.path.join('Output', 'Plots',
'centroid_samples'), exist_ok=True)
fig.tight_layout()
latex_plot_config()
fig.savefig(os.path.join('Output', 'Plots',
'centroid_samples', f'{DATASET.lower()}_{num}.pgf'))
else:
plt.show()
def animate(i):
print(i)
if i != 0 and i % width == 0:
ax0.clear()
ax0.xaxis.tick_top()
ax0.set_xlabel('Frame')
ax0.xaxis.set_label_position('top')
ax0.set_ylabel(r'Area [$mm^2$]')
areas, cent, img, mask = next(data)
if len(areas) == 0:
ax0.plot(i, 0, 'bo')
else:
for area in areas:
if len(areas) > 1:
ax0.plot(i, area, 'rx')
elif len(areas) == 1:
ax0.plot(i, area, 'k.')
image_ax.set_data(img)
mask_ax.set_data(mask)
x_coord, y_coord = parse_centroid_coords(cent)
if len(cent) > 1:
single_droplet_1.set_data([], [])
single_droplet_2.set_data([], [])
multi_droplet_1.set_data(x_coord, y_coord)
multi_droplet_2.set_data(x_coord, y_coord)
elif len(cent) == 1:
single_droplet_1.set_data(x_coord, y_coord)
single_droplet_2.set_data(x_coord, y_coord)
multi_droplet_1.set_data([], [])
multi_droplet_2.set_data([], [])
else:
single_droplet_1.set_data([], [])
single_droplet_2.set_data([], [])
multi_droplet_1.set_data([], [])
multi_droplet_2.set_data([], [])
if i in peaks:
ax0.axvline(x=i, color='k', alpha=0.4, linestyle='--')
ax1.set_title(f'Frame {i}')
return image_ax, mask_ax, single_droplet_1, multi_droplet_1, single_droplet_2, multi_droplet_2,
def animate_centroids_with_masks(save=False):
'''
Saves animation of original image and mask with markers for the centroids of each droplet.
Kwargs:
save {bool} -- wether to save the animation as a .mp4 or to show it with plt.show().
'''
def centroid_mask_img_generator():
for cent, image, mask in zip(CENTROIDS, IMAGES, MASKS):
yield cent, image, mask
data = centroid_mask_img_generator()
cent, img, msk = next(data)
x_coord, y_coord = parse_centroid_coords(cent)
with sns.axes_style('dark'):
fig, axes = plt.subplots(1, 2)
image_ax = axes[0].imshow(img)
mask_ax = axes[1].imshow(msk)
if len(cent) > 1:
single_droplet_1, = axes[0].plot([], [], 'k.')
multi_droplet_1, = axes[0].plot(x_coord, y_coord, 'rx')
single_droplet_2, = axes[1].plot([], [], 'k.')
multi_droplet_2, = axes[1].plot(x_coord, y_coord, 'rx')
elif len(cent) == 1:
single_droplet_1, = axes[0].plot(x_coord, y_coord, 'k.')
multi_droplet_1, = axes[0].plot([], [], 'rx')
single_droplet_2, = axes[1].plot(x_coord, y_coord, 'k.')
multi_droplet_2, = axes[1].plot([], [], 'rx')
else:
single_droplet_1, = axes[0].plot([], [], 'k.')
multi_droplet_1, = axes[0].plot([], [], 'rx')
single_droplet_2, = axes[1].plot([], [], 'k.')
multi_droplet_2, = axes[1].plot([], [], 'rx')
def animate(i):
print(i)
try:
cent, img, msk = next(data)
image_ax.set_data(img)
mask_ax.set_data(msk)
x_coord, y_coord = parse_centroid_coords(cent)
if len(cent) > 1:
single_droplet_1.set_data([], [])
single_droplet_2.set_data([], [])
multi_droplet_1.set_data(x_coord, y_coord)
multi_droplet_2.set_data(x_coord, y_coord)
elif len(cent) == 1:
single_droplet_1.set_data(x_coord, y_coord)
single_droplet_2.set_data(x_coord, y_coord)
multi_droplet_1.set_data([], [])
multi_droplet_2.set_data([], [])
else:
single_droplet_1.set_data([], [])
single_droplet_2.set_data([], [])
multi_droplet_1.set_data([], [])
multi_droplet_2.set_data([], [])
plt.title(f'Frame {i}')
return image_ax, mask_ax, single_droplet_1, multi_droplet_1, single_droplet_2, multi_droplet_2,
except StopIteration as error:
print(error)
ani = FuncAnimation(fig, animate, save_count=N_FRAMES-1)
if save:
ani.save(os.path.join('Output', 'Videos',
f'centroid_with_masks_{DATASET.lower()}.mp4'), writer=WRITER)
else:
plt.show()
def animate_areas_with_masks(width, func, save=False):
'''
Same as animate_areas() but includes the corresponding masks. Also displays the centroids.
Args:
width {int} -- length of the time frames, e.g. a signal with length 100 animated with width 10 will refresh the animation
every 10 frames.
Kwargs:
save {bool} -- wether to save the animation as a .mp4 file or show it using plt.show().
'''
def areas_centroid_img_mask_generator():
for i, cent_img_mask in enumerate(zip(CENTROIDS, IMAGES, MASKS)):
yield AREAS[i], *cent_img_mask
data = areas_centroid_img_mask_generator()
areas, cent, img, mask = next(data)
x_coord, y_coord = parse_centroid_coords(cent)
fig = plt.figure()
grid_spec = fig.add_gridspec(2, 2)
ax0 = fig.add_subplot(grid_spec[0, :])
ax0.xaxis.tick_top()
ax0.set_xlabel('Frame')
ax0.xaxis.set_label_position('top')
ax0.set_ylabel(r'Area [$mm^2$]')
with sns.axes_style('dark'):
ax1 = fig.add_subplot(grid_spec[1, 0])
ax2 = fig.add_subplot(grid_spec[1, 1])
ax1.set_xticks([])
ax1.set_yticks([])
ax2.set_xticks([])
ax2.set_yticks([])
if len(areas) == 0:
ax0.plot(0, 0, 'bo')
else:
for area in areas:
if len(areas) > 1:
ax0.plot(0, area, 'rx')
elif len(areas) == 1:
ax0.plot(0, area, 'k.')
image_ax = ax1.imshow(img)
mask_ax = ax2.imshow(mask)
ax0.set_ylim([0, max(max(AREAS))])
if len(cent) > 1:
single_droplet_1, = ax1.plot([], [], 'k.')
multi_droplet_1, = ax1.plot(x_coord, y_coord, 'rx')
single_droplet_2, = ax2.plot([], [], 'k.')
multi_droplet_2, = ax2.plot(x_coord, y_coord, 'rx')
elif len(cent) == 1:
single_droplet_1, = ax1.plot(x_coord, y_coord, 'k.')
multi_droplet_1, = ax1.plot([], [], 'rx')
single_droplet_2, = ax2.plot(x_coord, y_coord, 'k.')
multi_droplet_2, = ax2.plot([], [], 'rx')
else:
single_droplet_1, = ax1.plot([], [], 'k.')
multi_droplet_1, = ax1.plot([], [], 'rx')
single_droplet_2, = ax2.plot([], [], 'k.')
multi_droplet_2, = ax2.plot([], [], 'rx')
original_area = []
for areas in AREAS:
if len(areas) > 0:
original_area.append(func(areas))
else:
original_area.append(0)
# globular
if DATASET.lower() == 'globular':
smooth_area = smooth_signal(np.array(original_area), 41)
peaks = find_peaks(-smooth_area, height=-5, prominence=2)[0]
# spray
if DATASET.lower() == 'spray':
smooth_area = smooth_signal(np.array(original_area), 7)
peaks = find_peaks(smooth_area)[0]
def animate(i):
print(i)
if i != 0 and i % width == 0:
ax0.clear()
ax0.xaxis.tick_top()
ax0.set_xlabel('Frame')
ax0.xaxis.set_label_position('top')
ax0.set_ylabel(r'Area [$mm^2$]')
areas, cent, img, mask = next(data)
if len(areas) == 0:
ax0.plot(i, 0, 'bo')
else:
for area in areas:
if len(areas) > 1:
ax0.plot(i, area, 'rx')
elif len(areas) == 1:
ax0.plot(i, area, 'k.')
image_ax.set_data(img)
mask_ax.set_data(mask)
x_coord, y_coord = parse_centroid_coords(cent)
if len(cent) > 1:
single_droplet_1.set_data([], [])
single_droplet_2.set_data([], [])
multi_droplet_1.set_data(x_coord, y_coord)
multi_droplet_2.set_data(x_coord, y_coord)
elif len(cent) == 1:
single_droplet_1.set_data(x_coord, y_coord)
single_droplet_2.set_data(x_coord, y_coord)
multi_droplet_1.set_data([], [])
multi_droplet_2.set_data([], [])
else:
single_droplet_1.set_data([], [])
single_droplet_2.set_data([], [])
multi_droplet_1.set_data([], [])
multi_droplet_2.set_data([], [])
if i in peaks:
ax0.axvline(x=i, color='k', alpha=0.4, linestyle='--')
ax1.set_title(f'Frame {i}')
return image_ax, mask_ax, single_droplet_1, multi_droplet_1, single_droplet_2, multi_droplet_2,
ani = FuncAnimation(fig, animate, save_count=N_FRAMES-1)
if save:
ani.save(os.path.join('Output', 'Videos',
f'areas_with_masks_{DATASET.lower()}.mp4'), writer=WRITER)
else:
plt.show()