def test_gray2rgb():
image_path = '../lena.jpg'
img = Image.open(image_path).convert('L')
img = np.array(img)
print('input grayscale image has dimension of: '),
print(img.shape)
assert isgrayimage(img), 'the input image is not a gray image'
visualize_image(img, vis=True)
img_rgb = gray2rgb(img, with_color=True)
print('converted rgb image has dimension of: '),
print(img_rgb.shape)
assert iscolorimage(img_rgb), 'the converted image is not a color image'
visualize_image(img_rgb, vis=True)
# test when input image is float image
test_floatimage = (img.astype('float32')) / 255.
img_rgb = gray2rgb(test_floatimage, with_color=True)
assert iscolorimage(img_rgb), 'the converted image is not a color image'
visualize_image(img_rgb, vis=True)
# test when input image is PIL image
test_pil_format_image = Image.fromarray(img)
img_rgb = gray2rgb(test_pil_format_image, with_color=True)
assert iscolorimage(img_rgb), 'the converted image is not a color image'
print('\n\nDONE! SUCCESSFUL!!\n')
def image_clahe(input_image, clip_limit=2.0, grid_size=8, warning=True, debug=True):
'''
do contrast limited adative histogram equalization for an image: could be a color image or gray image
the color space used for histogram equalization is LAB
parameters:
input_image: a pil or numpy image
outputs:
clahe_image: an uint8 numpy image (rgb or gray)
'''
np_image, _ = safe_image(input_image, warning=warning, debug=debug)
if isfloatimage(np_image): np_image = (np_image.astype('float32') * 255.).astype('uint8')
if debug: assert isuintimage(np_image), 'the input image should be a uint8 image'
clahe = cv2.createCLAHE(clipLimit=clip_limit, tileGridSize=(grid_size, grid_size))
if iscolorimage(np_image):
lab_image = rgb2lab(np_image, warning=warning, debug=debug)
input_data = lab_image[:, :, 0] # extract the value channel
clahe_lab_image = clahe.apply(input_data)
lab_image[:, :, 0] = clahe_lab_image
clahe_image = lab2rgb(lab_image, warning=warning, debug=debug)
elif isgrayimage(np_image):
clahe_image = clahe.apply(np_image)
else: assert False, 'the input image is neither a color image or a grayscale image'
return clahe_image
def image_hist_equalization_hsv(input_image, warning=True, debug=True):
'''
do histogram equalization for an image: could be a color image or gray image
the color space used for histogram equalization is HSV
parameters:
input_image: a pil or numpy image
outputs:
equalized_image: an uint8 numpy image (rgb or gray)
'''
np_image, _ = safe_image(input_image, warning=warning, debug=debug)
if isuintimage(np_image): np_image = np_image.astype('float32') / 255.
if debug: assert isfloatimage(np_image), 'the input image should be a float image'
if iscolorimage(np_image):
hsv_image = rgb2hsv(np_image, warning=warning, debug=debug)
input_data = hsv_image[:, :, 2] # extract the value channel
equalized_hsv_image = (hist_equalization(input_data, num_bins=256, debug=debug) * 255.).astype('uint8')
hsv_image[:, :, 2] = equalized_hsv_image
equalized_image = hsv2rgb(hsv_image, warning=warning, debug=debug)
elif isgrayimage(np_image):
equalized_image = (hist_equalization(np_image, num_bins=256, debug=debug) * 255.).astype('uint8')
else: assert False, 'the input image is neither a color image or a grayscale image'
return equalized_image
def image_rgb2bgr(input_image, warning=True, debug=True): ''' this function converts a rgb image to a bgr image parameters: input_image: a pil or numpy rgb image outputs: np_image: a numpy bgr image ''' np_image, _ = safe_image(input_image, warning=warning, debug=debug) if debug: assert iscolorimage(np_image), 'the input image is not a color image' np_image = np_image[:, :, ::-1] # convert RGB to BGR return np_image
def hsv2rgb(input_image, warning=True, debug=True):
'''
convert a hsv image to a rgb image using opencv package
parameters:
input_image: an pil or numpy image
output:
rgb_img: an uint8 rgb numpy image
'''
np_image, _ = safe_image(input_image, warning=warning, debug=debug)
if isfloatimage(np_image): np_image = (np_image * 255.).astype('uint8')
if debug:
assert iscolorimage(np_image), 'the input image should be a rgb image'
assert isuintimage(np_image), 'the input numpy image should be uint8 image in order to use opencv'
rgb_img = cv2.cvtColor(np_image, cv2.COLOR_HSV2RGB)
return rgb_img
def rgb2hsv_v2(input_image, warning=True, debug=True):
'''
convert a rgb image to a hsv image, using PIL package, not compatible with opencv package
parameters:
input_image: an pil or numpy image
output:
hsv_image: an uint8 hsv numpy image
'''
np_image, _ = safe_image(input_image, warning=warning, debug=debug)
if isfloatimage(np_image): np_image = (np_image * 255.).astype('uint8')
if debug:
assert iscolorimage(np_image), 'the input image should be a rgb image'
assert isuintimage(np_image), 'the input numpy image should be uint8 image in order to use PIL'
pil_rgb_img = Image.fromarray(np_image)
pil_hsv_img = pil_rgb_img.convert('HSV')
hsv_img = np.array(pil_hsv_img)
return hsv_img