class LogoFinder:
def __init__(self):
self.heatmapper = Heatmapper(
point_diameter=15,
point_strength=0.05,
opacity=3,
colours='reveal',
)
self.heatmap_name = 'heatmap.png'
self.detector = CENSURE()
@staticmethod
def read_image(image_path):
image = cv2.imread(image_path)
bgr = image
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
return bgr, rgb, gray
def make_heatmap(self, image_path):
bgr_heatmap, rgb_heatmap, gray_heatmap = self.read_image(image_path)
# Find contours and edges
contours = find_contours(gray_heatmap,
100,
fully_connected='high',
positive_orientation='high')
edge_roberts = roberts(gray_heatmap)
edge_sobel = sobel(gray_heatmap)
self.detector.detect(gray_heatmap)
thresh = threshold_otsu(gray_heatmap)
bw = closing(gray_heatmap > thresh, square(3))
cleared = clear_border(bw)
label_image = label(cleared)
image_label_overlay = label2rgb(label_image, image=gray_heatmap)
edges = edge_roberts / 2 + edge_sobel / 2
dots = list()
for x in range(edges.shape[1]):
for y in range(edges.shape[0]):
for i in range(int(edges[y][x] * 2)):
dots.append([x, y])
for n, point in enumerate(self.detector.keypoints):
for i in range(self.detector.scales[n] * 10):
dots.append([
point[1] + (random.random() - 0.5) * 10,
point[0] + (random.random() - 0.5) * 10
])
for n, contour in enumerate(contours):
if len(contour) > 50:
for dot in contour:
dots.append([dot[1], dot[0]])
for region in regionprops(label_image):
# take regions with large enough areas
if region.area >= 100:
# draw rectangle around segmented coins
minr, minc, maxr, maxc = region.bbox
for x in range(minc, maxc):
for y in range(minr, maxr, 8):
dots.append([x, y])
heatmap = self.heatmapper.heatmap_on_img_path(dots, image_path)
heatmap.save(self.heatmap_name)
bgr_heatmap, rgb_heatmap, gray_heatmap = self.read_image(
self.heatmap_name)
thresh = threshold_otsu(gray_heatmap)
bw = closing(gray_heatmap > thresh, square(3))
cleared = clear_border(bw)
label_image = label(cleared)
image_label_overlay = label2rgb(label_image, image=gray_heatmap)
for n, region in enumerate(regionprops(label_image)):
minr, minc, maxr, maxc = region.bbox
if maxr - minr > 30 and maxc - minc > 30:
yield minr, minc, maxr, maxc
from heatmappy import Heatmapper
from PIL import Image
example_points = [(100, 20), (120, 25), (200, 50), (60, 300), (170, 250)]
example_img_path = 'default-cat.png'
example_img = Image.open(example_img_path)
heatmapper = Heatmapper()
heatmap = heatmapper.heatmap_on_img(example_points, example_img)
heatmap.save('heatmapbasic.png')
heatmapper = Heatmapper(opacity=0.9, colours='reveal')
heatmap = heatmapper.heatmap_on_img_path(example_points, example_img_path)
heatmap.save('heatmapreveal.png')