def main(args):
m = 100
img = im_to_arr(args[0])
m = max(0, min(m, 255))
inv = bound(img + m)
inv = Image.fromarray(inv.astype(np.uint8))
inv.show()
def main(args):
img = im_to_arr(args[0])
thresholded = threshold(img, 90)
projection = np.zeros(
(thresholded.shape[0] + 32, thresholded.shape[1] + 32))
projection[32:, 32:] = thresholded
projection = np.repeat(projection, 3).reshape(
(projection.shape[0], projection.shape[1], 3))
projection[30:32, :] = (0, 0, 200)
projection[:, 30:32] = (0, 0, 200)
for x in range(thresholded.shape[0]):
sum_in_row = np.sum(thresholded[x, :])
white_ratio = sum_in_row / thresholded.shape[1] / 255
stretched = int(round(30 * white_ratio))
for p in range(stretched, -1, -1):
projection[x + 32, p] = (255, 0, 0)
for x in range(thresholded.shape[1]):
sum_in_col = np.sum(thresholded[:, x])
white_ratio = sum_in_col / thresholded.shape[0] / 255
stretched = int(round(30 * white_ratio))
for p in range(stretched, -1, -1):
projection[p, x + 32] = (255, 0, 0)
projection = Image.fromarray(projection.astype(np.uint8))
projection.show()
def main(args):
img = im_to_arr(args[0])
avg = applyFilter(img, averaging)
avg = Image.fromarray(avg.astype(np.uint8))
avg.show()
ga = applyFilter(img, gauss)
ga = Image.fromarray(ga.astype(np.uint8))
ga.show()
sha = applyFilter(img, sharpening)
sha = Image.fromarray(sha.astype(np.uint8))
sha.show()
rob = roberts_filter(img)
rob = Image.fromarray(rob.astype(np.uint8))
rob.show()
sobel = sobel_filter(img)
sobel = Image.fromarray(sobel.astype(np.uint8))
sobel.show()
img = Image.fromarray(img.astype(np.uint8))
img.show()
def main(args):
img = im_to_arr(args[0])
wei, avg = conv_gray(img)
wei = Image.fromarray(wei)
avg = Image.fromarray(avg)
wei.show()
avg.show()
def main(args):
img = im_to_arr(args[0])
thresholded = threshold(img)
thresholded = Image.fromarray(thresholded.astype(np.uint8))
thresholded.show()
def main(args):
img = im_to_arr(args[0])
r_lut = bound(np.array(range(0, 256)) + 50)
g_lut = bound(np.array(range(0, 256)) + 40)
b_lut = bound(np.array(range(0, 256)) - 100)
img[:, :, 0] = lut_mainp(img[:, :, 2], r_lut)
img[:, :, 1] = lut_mainp(img[:, :, 2], g_lut)
img[:, :, 2] = lut_mainp(img[:, :, 2], b_lut)
img = Image.fromarray(img.astype(np.uint8))
img.show()
def main(args):
img = im_to_arr(args[0])
r_channel = img[:, :, 0]
g_channel = img[:, :, 1]
b_channel = img[:, :, 2]
expanded = np.zeros_like(img)
expanded[:, :, 0] = expand_hist(r_channel)
expanded[:, :, 1] = expand_hist(g_channel)
expanded[:, :, 2] = expand_hist(b_channel)
Image.fromarray(img.astype(np.uint8)).show(title='original image')
Image.fromarray(expanded.astype(np.uint8)).show(title='histogram expanded')
print_hist_img([img, expanded])
def main(args):
factor = 8
img = im_to_arr(args[0])
ce = bound(((img / 255 - 0.5) * factor + 0.5) * 255)
ce = Image.fromarray(ce.astype(np.uint8))
ce.show()
