def main():
'''Demo blob finding in grain image.'''
# Load and show
img = imread('img/104_E5R_0.jpg')
img = rgb2gray(img)
show_with_hist(img, 'Original image')
# Get temperature bounds
print(get_temperature_bounds(img))
# Crop
img_crop = crop_ui(img)
show_with_hist(img_crop, 'Cropped image')
# Invert
img_inv = invert(img_crop)
show_with_hist(img_inv, 'Inverted')
img_prep = img_inv
blobs = find_blobs(img_prep)
_, ax = plt.subplots(1)
plt.title("blobs detection with DoH")
plt.imshow(img_crop, cmap=plt.get_cmap('gray'))
for blob in blobs:
y, x, r = blob
c = plt.Circle((x, y), r, color='r', linewidth=0.75, fill=False)
ax.add_patch(c)
ax.set_axis_off()
print(len(blobs))
def grain_samples_imgs_gen():
samples_names = ('104_E5R', '117_E6R')
for name in samples_names:
imgs = load_img_series('img/' + name)
for i, img in enumerate(imgs):
img = rgb2gray(img)
imsave('exports/' + name + '_' + str(i) + '.png',
img_as_ubyte(crop_ui(img)))
def blob_detection_compare_plots_gen():
img = imread('img/104_E5R_0.jpg')
img_crop = crop_ui(rgb2gray(img))
img_prep = full_prepare(img)
blobs_list = compare_detection(img_prep)
suffixes = ('LoG', 'DoG', 'DoH')
for blobs, suffix in zip(blobs_list, suffixes):
_, ax = plt.subplots()
plt.title('Liczba wykrytych detali: {}'.format(len(blobs)))
plt.imshow(img_crop, cmap=plt.get_cmap('gray'))
for blob in blobs:
y, x, r = blob
c = plt.Circle((x, y), r, color='r', fill=False)
ax.add_patch(c)
ax.set_axis_off()
tikzplotlib.save('exports/blob_detection_compare_' + suffix)
def blob_count_plots_gen():
imgs = load_img_series('img/104_E5R')
imgs_prep = [full_prepare(img) for img in imgs]
imgs_crop = [crop_ui(rgb2gray(img)) for img in imgs]
stages_all = find_blob_series(imgs_prep, only_remaining=False)
stages_rem = find_blob_series(imgs_prep)
# Map stages on first image
colors = ('blue', 'blueviolet', 'magenta', 'crimson', 'red')
fig = plt.figure(frameon=False)
ax = fig.add_axes([0, 0, 1, 1])
plt.imshow(imgs_crop[0], cmap=plt.get_cmap('gray'))
for stage, color in zip(stages_rem, colors):
for blob in stage:
y, x, r = blob
c = plt.Circle((x, y), r, color=color, fill=False)
ax.add_patch(c)
ax.set_axis_off()
plt.savefig('exports/blob_tracker', dpi=300)
# Show two methods combined to compare
loop_set = enumerate(zip(stages_rem, stages_all, imgs_crop))
for i, (stage_rem, stage_all, img) in loop_set:
fig = plt.figure(frameon=False)
ax = fig.add_axes([0, 0, 1, 1])
plt.imshow(img, cmap=plt.get_cmap('gray'))
for blob_all in stage_all:
y, x, r = blob_all
c = plt.Circle((x, y), r, color='b', fill=False)
ax.add_patch(c)
for blob_rem in stage_rem:
y, x, r = blob_rem
c = plt.Circle((x, y), r, color='r', fill=False)
ax.add_patch(c)
ax.set_axis_off()
plt.savefig('exports/blob_tracker_min_' + str(i))
def main():
'''Demo blob tracking with various ways of counting blobs.'''
# Load images
imgs = load_img_series('img/104_E5R')
# Prepare images for processing
imgs_prep = [full_prepare(img) for img in imgs]
# Prepare cropped images for displaying
imgs_crop = [crop_ui(rgb2gray(img)) for img in imgs]
# Find blobs for stages of cooling with preserving only remainig ones
stages_rem = find_blob_series(imgs_prep)
# Map stages on first image
colors = ('blue', 'blueviolet', 'magenta', 'crimson', 'red')
_, ax = plt.subplots(1)
plt.title("Blobs detection with DoH")
plt.imshow(imgs_crop[0], cmap=plt.get_cmap('gray'))
for stage, color in zip(stages_rem, colors):
for blob in stage:
y, x, r = blob
c = plt.Circle((x, y), r, color=color, linewidth=0.75, fill=False)
ax.add_patch(c)
labels = ('Minute 0', 'Minute 1', 'Minute 2', 'Minute 3', 'Minute 4')
patch_plot_legend_outside(colors, labels)
print(ratio_of_remaining_blobs_in_stages(stages_rem))
# Show stages on subplots
_, ax = plt.subplots(2, 3, figsize=(12, 7))
ax = ax.flatten()
for idx, (stage, img) in enumerate(zip(stages_rem, imgs_crop)):
ax[idx].imshow(img, cmap=plt.get_cmap('gray'))
ax[idx].set_title("Minute: {}, blobs: {}".format(idx, len(stage)))
for blob in stage:
y, x, r = blob
c = plt.Circle((x, y), r, color='r', linewidth=0.75, fill=False)
ax[idx].add_patch(c)
ax[-1].set_axis_off()
plt.tight_layout()
# Find all blobs for every stage of cooling
stages_all = find_blob_series(imgs_prep, only_remaining=False)
# Show stages on subplots
_, ax = plt.subplots(2, 3, figsize=(12, 7))
ax = ax.flatten()
for idx, (stage, img) in enumerate(zip(stages_all, imgs_crop)):
ax[idx].imshow(img, cmap=plt.get_cmap('gray'))
ax[idx].set_title("Minute: {}, blobs: {}".format(idx, len(stage)))
for blob in stage:
y, x, r = blob
c = plt.Circle((x, y), r, color='r', linewidth=0.75, fill=False)
ax[idx].add_patch(c)
ax[-1].set_axis_off()
plt.tight_layout()
# Show two methods combined to compare
_, ax = plt.subplots(2, 3, figsize=(10, 7))
ax = ax.flatten()
# Show stages on subplots
loop_set = enumerate(zip(stages_rem, stages_all, imgs_crop))
for idx, (stage_rem, stage_all, img) in loop_set:
ax[idx].imshow(img, cmap=plt.get_cmap('gray'))
ax[idx].set_title("Minute: {}, all blobs: {}, rem blobs: {}".format(
idx, len(stage_all), len(stage_rem)))
for blob_all in stage_all:
y, x, r = blob_all
c = plt.Circle((x, y), r, color='b', linewidth=0.75, fill=False)
ax[idx].add_patch(c)
for blob_rem in stage_rem:
y, x, r = blob_rem
c = plt.Circle((x, y), r, color='r', linewidth=0.75, fill=False)
ax[idx].add_patch(c)
ax[-1].set_axis_off()
plt.tight_layout()
plt.show()