ax2.set_adjustable('box-forced')
if __name__ == "__main__":
# Settings
box_size = 80
scale_factor = 0.8
mask_scale = 0.2
plot = False
box_size *= scale_factor
# Load Preprocessor
print("Preprocessing")
p = Preprocessor("../images/slum_image.jpg")
p.scale_image(scale_factor)
p.exposure_equalization(method="equal")
p.convert_color("RGB","HSV")
p.save_current_as("structure")
p.reset()
p.scale_image(mask_scale)
p.exposure_equalization(method="equal")
p.convert_color("RGB","HSV")
p.save_current_as("mask")
# Load images for mask and structure information
img2 = p.get_version("mask")[:,:,0]
img = p.get_version("structure")[:,:,2]
print("Masking")
med_img = median(img2, disk(50*mask_scale))
coords = np.loadtxt("patch_coordinates.txt", delimiter="\t", skiprows=1)
coords = np.multiply(coords, scale_factor)
patches = {'white':coords[:,0:2],
'brown':coords[:,2:4],
'gray':coords[:,4:6],
'green':coords[:,6:8]}
box_size *= scale_factor
# Load Preprocessor
print("Preprocessing")
p = Preprocessor("../images/slum_image.jpg")
p.scale_image(scale_factor)
p.save_current_as("normal")
p.exposure_equalization(method="contrast")
p.convert_color("RGB","RGB CIE")
p.save_current_as("contrast_rgb_cie")
p.reset()
p.scale_image(scale_factor)
p.exposure_equalization(method="equal")
p.convert_color("RGB","HSV")
p.save_current_as("structure")
# ========== Plot img & patches =========
if plot:
plt.figure()
ax = plt.gca()
img = p.get_version('structure')[:,:,1]
plt.imshow(img)
patches = {
'white': coords[:, 0:2],
'brown': coords[:, 2:4],
'gray': coords[:, 4:6],
'green': coords[:, 6:8]
}
box_size *= scale_factor
# Load Preprocessor
print("Preprocessing")
p = Preprocessor("../images/slum_image.jpg")
p.scale_image(scale_factor)
p.save_current_as("normal")
p.exposure_equalization(method="contrast")
p.convert_color("RGB", "RGB CIE")
p.save_current_as("contrast_rgb_cie")
p.reset()
p.scale_image(scale_factor)
p.exposure_equalization(method="equal")
p.convert_color("RGB", "HSV")
p.save_current_as("structure")
# ========== Plot img & patches =========
if plot:
plt.figure()
ax = plt.gca()
img = p.get_version('structure')[:, :, 1]
plt.imshow(img)
if __name__ == "__main__":
# Settings
box_size = 80
scale_factor = 0.8
mask_scale = 0.2
plot = False
box_size *= scale_factor
# Load Preprocessor
print("Preprocessing")
p = Preprocessor("../images/slum_image.jpg")
p.scale_image(scale_factor)
p.exposure_equalization(method="equal")
p.convert_color("RGB", "HSV")
p.save_current_as("structure")
p.reset()
p.scale_image(mask_scale)
p.exposure_equalization(method="equal")
p.convert_color("RGB", "HSV")
p.save_current_as("mask")
# Load images for mask and structure information
img2 = p.get_version("mask")[:, :, 0]
img = p.get_version("structure")[:, :, 2]
print("Masking")
med_img = median(img2, disk(50 * mask_scale))
