def monitor(self):
html_path = os.path.join(os.getcwd(), "web_pages", "monitor.html")
if self.best_fit != -1:
# If there is a segmentor then display the images segmentation
img = imageio.imread(self.rgb_filename)
gmask = imageio.imread(self.label_filename)
print(self.best_ind["params"])
self.best_ind["params"]
seg = Segmentors.algoFromParams(self.best_ind["params"])
mask = seg.evaluate(img)
static_dir = os.path.join(os.getcwd(), "public")
imageio.imwrite(os.path.join(static_dir, "mask.jpg"), mask)
code = GeneticSearch.print_best_algorithm_code(self.best_ind["params"])
# Calculate progress bar precentage
percentage = (1 - self.best_ind["fitness"]) * 100
rounded_fitness = float("{0:.2f}".format(self.best_ind["fitness"]))
data = ["", code, self.best_ind["params"], rounded_fitness, percentage]
else:
data = ['style="display:none;"', "", "", "",""]
return fill_html_template(html_path, data)
def test_print_best_algorithm_code():
"""Unit test for print_best_algorithm_code function.
Checks function output matches method contents it's printing."""
individual = ['FB', 0, 0, 984, 0.09, 92, 0, 0, 0, 0, 0, 0, 0, 0, 0,\
(1, 2), 0, "checkerboard", "checkerboard", 0, 0, 0, 0, 0, 0]
print_statement = "multichannel = False\n\
if len(img.shape) > 2:\n\
multichannel = True\n\
output = skimage.segmentation.felzenszwalb(\n\
img,\n\
984,\n\
0.09,\n\
92,\n\
multichannel=multichannel,\n\
)\n"
assert GeneticSearch.print_best_algorithm_code(individual) == print_statement
def update_code_display(n_intevals, currently_displayed_code):
if has_results():
return GeneticSearch.print_best_algorithm_code(best_ind["params"])
else:
return currently_displayed_code
