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helper.py
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helper.py
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import cv2
import numpy
import math
from PIL import Image, ImageEnhance
# =================CONVERT================
def CV2_to_PIL_img(cv2_im):
"""
Convert Opencv's BGR image to PIL image
Input:
--------
cv2_im: Opencv's BGR
Output:
--------
PIL Image
"""
cv2_im = cv2.cvtColor(cv2_im, cv2.COLOR_BGR2RGB)
pil_im = Image.fromarray(cv2_im)
return pil_im
def PIL_to_CV2_img(img):
"""
Convert PIL image to Opencv's BGR image
Input:
--------
img: PIL Image
Output:
--------
Opencv's BGR Image
"""
cv_image = numpy.array(img.convert('RGB'))
cv_image = cv_image[:, :, ::-1].copy()
return cv_image
# ========================================
# =========POLYNOMIAL FUNCTIONS===========
def first_polynomial_function(image):
"""
Implementation of first polynomial function.
Input:
--------
image: Opencv's BGR Image
More detail at `Documentation.pdf`
"""
table = numpy.array([1.657766*i-0.009157128*(i**2) + 0.00002579473*(i**3)
for i in numpy.arange(0, 256)]).astype("uint8")
return cv2.LUT(image, table)
def second_polynomial_function(image):
"""
Implementation of second polynomial function.
Input:
--------
image: Opencv's BGR Image
More detail at `Documentation.pdf`
"""
table = numpy.array([
-4.263256 * math.exp(-14)+1.546429*i-0.005558036*(i**2)+0.00001339286*(i**3)
for i in numpy.arange(0, 256)]).astype("uint8")
return cv2.LUT(image, table)
# ========================================
# ===========GAMMA CORRECTION ============
def adjust_gamma(image, gamma=1.0):
"""
Implementation of gamma correction
Input:
--------
image: Opencv's BGR Image
More detail at `Gamma-Correction.pdf`
"""
invGamma = 1.0 / gamma
table = numpy.array([((i / 255.0) ** invGamma) * 255
for i in numpy.arange(0, 256)]).astype("uint8")
return cv2.LUT(image, table)
# ========================================
# =========CONTRAST & BRIGHTNESS==========
def enhance_contrast(image, factor=1.4):
"""
Enhance contrast base on PIL->ImageEnhance.
Default suitable factor is 1,4.
Input:
image: Opencv's BGR Image
factor: contrast's factor
Output:
Enhanced contrast BGR image
"""
_image = ImageEnhance.Contrast(
CV2_to_PIL_img(image)
).enhance(factor)
return PIL_to_CV2_img(_image)
# ========================================
# =================METHODS================
def reduce_glare(image):
"""
Mixed 4 filter:
1. First polynomial function
2. Gamma correction: g = 0.75
3. Second polynomial function
4. Gamma correction: g = 0.8
Input: BGR Image.\n
Output: Reduce glare.
"""
_image = adjust_gamma(
second_polynomial_function(
adjust_gamma(
first_polynomial_function(image),
0.75
)
),
0.8
)
return _image
def mix_filter(image):
"""
Mixed 4 steps:
1. Reduce glare
2. Enhance contract: f = 1.6
3. Reduce glare
4. Enhance contract: f = 1.4
Input: BGR Image.\n
Output: Reduced glare & clearly image.
"""
_image = enhance_contrast(
reduce_glare(
enhance_contrast(
reduce_glare(image),
factor=1.6
)
),
factor=1.4
)
return _image
# ========================================