def dxdy_hist(img_gray, num_bins):
assert len(img_gray.shape) == 2, 'image dimension mismatch'
assert img_gray.dtype == 'float', 'incorrect image type'
sigma, caps = 3, (-6, 6)
kernel = gauss_module.gaussdx(sigma)[0]
kernel = kernel[int((len(kernel) - 1) / 2) + caps[0]: int((len(kernel) + 1) / 2) + caps[1]]
kernel = (kernel / kernel.sum()).reshape(1, kernel.shape[0])
imgDx = conv2(img_gray, kernel, 'same')
imgDy = conv2(img_gray, kernel.transpose(), 'same')
# rescaling to [0, 255]
def scale(img):
img_flat = img.flatten()
img_scaled = ((img - min(img_flat)) / (max(img_flat) - min(img_flat))) * 255
return img_scaled
imgDx, imgDy, imgDz = scale(imgDx), scale(imgDy), np.zeros_like(imgDx)
img_concat = np.zeros(shape=(imgDx.shape[0], imgDx.shape[1], 3))
img_concat[:, :, 0], img_concat[:, :, 1], img_concat[:, :, 2] = imgDx, imgDy, imgDz
# Define a 2D histogram with "num_bins^2" number of entries
hists = rg_hist(img_concat.astype('double'), num_bins)
return hists
smooth_img = gauss_module.gaussianfilter(img, sigma)
plt.figure(2)
ax1 = plt.subplot(1, 2, 1)
ax2 = plt.subplot(1, 2, 2)
plt.sca(ax1)
plt.imshow(img, cmap='gray', vmin=0, vmax=255)
plt.sca(ax2)
plt.imshow(smooth_img, cmap='gray', vmin=0, vmax=255)
plt.show()
## function gaussdx (Question 1.c)
sigma = 4.0
[Gx, x] = gauss_module.gauss(sigma)
[Dx, x] = gauss_module.gaussdx(sigma)
plt.figure(5)
plt.plot(x, Gx, 'b.-')
plt.plot(x, Dx, 'r-')
plt.legend(('gauss', 'gaussdx'))
plt.show()
## function gaussdx (Question 1.d)
img_imp = np.zeros([27, 27])
img_imp[13, 13] = 1.0
plt.figure(6), plt.imshow(img_imp, cmap='gray')
sigma = 7.0
[Gx, x] = gauss_module.gauss(sigma)
ax2 = plt.subplot(1, 2, 2)
plt.sca(ax1)
plt.imshow(img, cmap='gray', vmin=0, vmax=255)
plt.sca(ax2)
plt.imshow(smooth_img, cmap='gray', vmin=0, vmax=255)
plt.show()
## function gaussdx (Question 1.c)
img = np.zeros([27, 27])
img[13, 13] = 1.0
plt.figure(), plt.imshow(img, cmap='gray')
sigma = 7.0
[G, x] = gauss_module.gauss(sigma)
[D, x] = gauss_module.gaussdx(sigma)
plt.figure()
plt.plot(x, G, 'b.-')
plt.plot(x, D, 'r-')
plt.legend(('gauss', 'gaussdx'))
plt.show()
G = G.reshape(1, G.size)
D = D.reshape(1, D.size)
plt.figure()
plt.subplot(2, 3, 1)
plt.imshow(conv2(img, G, 'same'), cmap='gray')
plt.subplot(2, 3, 2)
plt.imshow(conv2(img, G.T, 'same'), cmap='gray')
