def DetectCorners(self):
"""
Detect Page Corners
Args:
No Args needed
"""
os.chdir(self.Directory)
os.chdir("Cambire")
for Image in glob.glob("Enhanced_*.jpg"):
ImageOriginal = cv2.imread(Image, cv2.IMREAD_COLOR)
GrayscaleImage = cv2.cvtColor(ImageOriginal, cv2.COLOR_BGR2GRAY)
GrayscaleImage = np.float32(GrayscaleImage)
cv2.imshow("Enhanced", ImageOriginal)
corners = cv2.cornerHarris(GrayscaleImage, 2, 3, 1)
GrayscaleImage = cv2.dilate(GrayscaleImage, None)
ImageOriginal[GrayscaleImage > 0.4 * GrayscaleImage.max()] = [0,0,255]
Imagename = "Cornered_" + Image
cv2.imwrite(Imagename, ImageOriginal)
cv2.imshow(Imagename, ImageOriginal)
cv2.waitKey(0)
cv2.distroyAllWindows()
os.chdir("..")
def live_from_video(self, video_path):
cap = cv2.VideoCapture(video_path)
while cap.isOpened():
ret, image = cap.read()
self.set_image(cv2.resize(image, (640, 360), interpolation=cv2.INTER_AREA))
self.detect_face()
cv2.imshow('age_detection_api detection',self.image_bounding_boxes)
if cv2.waitKey(5) == 27:
break
cap.release()
cv2.distroyAllWindows()
def live_cv2(self):
video_capture = cv2.VideoCapture(0)
while True:
if not video_capture.isOpened():
sleep(5)
ret, self.image = video_capture.read()
self.detect_face()
cv2.imshow(self.image_bounding_boxes)
if cv2.waitKey(5) == 27:
break
video_capture.release()
cv2.distroyAllWindows()
import cv2
import numpy as np
img = cv2.imread("12.png")
scaled_img = cv2.resize(img, None, fx=1, fy=2)
rows, cols, ch = img.shape
print(rows)
print(cols)
matrix = np.float32([[1, 0, 50], [0, 1, 50]])
translate_img = cv2.warpAffine(img, matrix, (cols, rows))
cv2.imshow("GeoTransformation", img)
cv2.imshow("scaled", scaled_img)
cv2.imshow("translated", translate_img)
cv2.waitKey(0)
cv2.distroyAllWindows()
for n in range(0, 250, 30):
cv2.rectangle(rectangle, (n, n), (500-n, 500-n), (255, 255, 0), 3)
cv2.imshow('Rectangle', rectangle)
cv2.waitKey(150)
cv2.imwrite('rectangle.png', rectangle)
# 4. Draw Ellipse
ellipse = np.zeros((502, 502, 3), np.uint8)
cv2.ellipse(ellipse, (250, 250), (10, 10), (30 + n * 60), 0, 360, (0, 255, 255), -1)
for n in range(0, 3, 1):
cv2.ellipse(ellipse, (250, 250), (200, 50), (30 + n * 60), 0, 360, (0, 255, 255), 1)
cv2.imshow('Ellipse', ellipse)
cv2.waitKey(200)
cv2.imwrite('ellipse.png', ellipse)
# 5. Draw Text
text = np.zeros((502, 502, 3), np.uint8)
font = cv2.FONT_HERSHEY_SIMPLEX
for n in range(0, 255):
cv2.putText(text, 'OpenCV', (10, 100), font, 4, (0, 0, n), 4)
cv2.imshow('Draw Text', text)
cv2.waitKey(10)
if (ord('q') == (cv2.waitKey(0) & 0xff)):
cv2.distroyAllWindows()
def display(self, image):
self.img = image
count = 0
#filling all dictionaries with zeros
for i in range(0, 256):
self.frequency[i] = 0
self.cdf[i] = 0
self.equalized[i] = 0
#setting the frequency
for i in range(0, self.img.shape[0]):
for j in range(0, self.img.shape[1]):
self.frequency[self.img[i,
j]] = self.frequency[self.img[i,
j]] + 1
#deleting pixels are not in the image
self.frequency = {
key: value
for key, value in self.frequency.items() if value != 0
}
#sorting by key
self.frequency = collections.OrderedDict(sorted(
self.frequency.items()))
#setting cdf
prev_key = 0
first = True
for key, value in self.frequency.items():
if first:
self.cdf[key] = self.frequency[key]
first = False
else:
self.cdf[key] = self.frequency[key] + self.cdf[prev_key]
prev_key = key
#deleting pixels are not in the image
self.cdf = {
key: value
for key, value in self.cdf.items() if value != 0
}
#sorting by key
self.cdf = collections.OrderedDict(sorted(self.cdf.items()))
first = True
for key, value in self.cdf.items():
if first:
min = value
first = False
else:
top = value - min
bottom = (self.img.shape[0] * self.img.shape[1]) - 1
res = (top / bottom) * 255
self.equalized[key] = int(math.floor(res))
equalized_img = np.zeros((self.img.shape[0], self.img.shape[1], 3),
np.uint8)
for i in range(0, equalized_img.shape[0]):
for j in range(0, equalized_img.shape[1]):
equalized_img[i, j] = self.equalized[self.img[i, j]]
#printing
for k, v in self.frequency.items():
if v != 0:
print("pixel: " + str(k) + " was repeated " + str(v) +
" times, CDF: " + str(self.cdf[k]))
print(self.img.shape)
cv2.imshow('equalized image', equalized_img)
cv2.waitKey(0)
cv2.distroyAllWindows()
