def overlap_img(img1, img2):
np.zeros((512, 512))
# Load two images
# img1 = cv2.imread('227351.jpg') # 背景
# img2 = cv2.imread('logo.png') # logo
# I want to put logo on top-left corner, So I create a ROI
rows, cols, channels = img2.shape
roi = img1[0:rows, 0:cols]
# Now create a mask of logo and create its inverse mask also
img2gray = cv2.cv2tColor(img2, cv2.COLOR_BGR2GRAY)
ret, mask = cv2.threshold(img2gray, 254, 255, cv2.THRESH_BINARY) # 这个254很重要
mask_inv = cv2.bitwise_not(mask)
# cv2.imshow('mask', mask_inv)
# Now black-out the area of logo in ROI
img1_bg = cv2.bitwise_and(roi, roi, mask=mask) # 这里是mask,我参考的博文写反了,我改正了,费了不小劲
# Take only region of logo from logo image.
img2_fg = cv2.bitwise_and(img2, img2, mask=mask_inv) # 这里才是mask_inv
# Put logo in ROI and modify the main image
dst = cv2.add(img1_bg, img2_fg)
img1[0:rows, 0:cols] = dst
cv2.imshow('res', img1)
cv2.waitKey(0)
cv2.destroyAllWindows()
def processImage(fn):
print('processing %s... ' % fn)
img = cv2.imread(fn, 0)
if img is None:
print("Failed to load", fn)
return None
assert w == img.shape[1] and h == img.shape[0], (
"size: %d x %d ... " % (img.shape[1], img.shape[0]))
found, corners = cv2.findChessboardCorners(img, pattern_size)
if found:
term = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_COUNT, 30, 0.1)
cv2.cornerSubPix(img, corners, (5, 5), (-1, -1), term)
if debug_dir:
vis = cv2.cv2tColor(img, cv2.COLOR_GRAY2BGR)
cv2.drawChessboardCorners(vis, pattern_size, corners, found)
_path, name, _ext = splitfn(fn)
outfile = os.path.join(debug_dir, name + '_chess.png')
cv2.imwrite(outfile, vis)
if not found:
print('chessboard not found')
return None
print(' %s... OK' % fn)
return (corners.reshape(-1, 2), pattern_points)
def get_roi_hist(self, cam_shift):
roi = cam_shift[self.r:self.r+self.h, self.c:self.c+self.w]
hsv_roi = cv2.cv2tColor(roi, cv2.COLOR_BGR2HSV)
mask = cv2.inRange(hsv_roi, np.array((0., 60.,32.)), np.array((180.,255.,255.)))
roi_hist = cv2.calcHist([hsv_roi], [0], mask, [180],[0,180])
cv2.normalize(roi_hist, roi_hist, 0, 255, cv2.NORM_MINMAX)
return roi_hist
def process(self, img):
# Get region of interest
if self.img_num == 0:
self.roi_hist = self.get_roi_hist(img)
hsv = cv2.cv2tColor(img, cv2.COLOR_BGR2HSV)
dst = cv2.calcBackProject([hsv],[0], self.roi_hist, [0,180], 1)
# apply meanshift to get the new location
self.ret, self.track_window = cv2.CamShift(dst, self.track_window, self.term_crit)
# Increment image counter
self.img_num += 1
return self.ret
def Reformat_Image(self, img):
# img_dot = cv2.imread("dot.jpg", cv2.IMREAD_COLOR)
# gray = cv2.cv2tColor(img_dot, cv2.COLOR_BGR2GRAY)
# ret, th1 = cv2.threshold(gray, 170, 255, cv2.THRESH_BINARY)
# Load the image
img = Image.fromarray(cv2.cv2tColor(img, cv2.COLOR_BGR2RGB))
img_w, img_h = img.size
background = Image.new('RGB', (200, 200), (255, 255, 255, 255))
bg_w, bg_h = background.size
offset = ((bg_w - img_w) // 2, (bg_h - img_h) // 2)
background.paste(img, offset)
# Converting Image to the opencv2 format(BGR)
open_cv2_image = np.array(background)
# Convert RGB to BGR
open_cv2_image = open_cv2_image[:, :, ::-1].copy()
if self.no_of_contours(open_cv2_image) == 1:
# Getting smallest square contour character
cropped_img = self.char_contour(None, open_cv2_image)
elif self.no_of_contours(open_cv2_image) > 1:
teimg = self.morph(open_cv2_image)
cropped_img = self.char_contour(teimg, open_cv2_image)
else:
cropped_img = self.char_contour(None, open_cv2_image)
# Resizing image to 50*50 resolution
width = 50
height = 50
dim = (width, height)
# resize image
if cropped_img is None:
return -1
else:
resized = cv2.resize(cropped_img, dim, interpolation=cv2.INTER_AREA)
return resized
Python 2.7.11 (v2.7.11:6d1b6a68f775, Dec 5 2015, 20:40:30) [MSC v.1500 64 bit (AMD64)] on win32
Type "copyright", "credits" or "license()" for more information.
>>> import sys
sys.path.append('/usr/local/include/')
import cv2
import numpy as np
import math
cap = cv2.VideoCapture(0)
while(cap.isOpened()):
ret, img = cap.read()
cv2.rectangle(img,(300,300),(100,100),(0,255,0),0)
crop_img = img[100:300, 100:300]
grey = cv2.cv2tColor(crop_img, cv2.COLOR_BGR2GRAY)
value = (35, 35)
blurred = cv2.GaussianBlur(grey, value, 0)
_, thresh1 = cv2.threshold(blurred, 127, 255,
cv2.THRESH_BINARY_INV+cv2.THRESH_OTSU)
cv2.imshow('Thresholded', thresh1)
image, contours, hierarchy = cv2.findContours(thresh1.copy(), \
cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
max_area = -1
for i in range(len(contours)):
cnt=contours[i]
area = cv2.contourArea(cnt)
if(area>max_area):
max_area=area
ci=i
cnt=contours[ci]
x,y,w,h = cv2.boundingRect(cnt)
cv2.rectangle(crop_img,(x,y),(x+w,y+h),(0,0,255),0)
def test():
img = cv2.imread('./test.jpg')
newImg = img
# 设定窗口
# cv2.namedWindow('Image',cv2.WINDOW_NORMAL)
# cv2.imshow('Image',img)
# 调用matplotlib画图
plot.imshow(img, cmap='gray', interpolation='bicubic')
plot.xticks([]), plot.yticks([])
plot.show()
# print(img.shape)
# print(img.dtype)
width = img.shape[0]
height = img.shape[1]
# print(width,height)
# 添加文字
cv2.putText(newImg, 'hello', (100, 100), cv2.FONT_HERSHEY_COMPLEX, 3,
(255, 255, 255), 10)
# 等待IO
key = cv2.waitKey(0)
if key == 27:
cv2.destroyAllWindows()
elif key == ord('s'):
# 保存图像
cv2.imwrite('newtest.png', newImg)
print("保存完毕!\n")
elif key == ord('m'):
# 放大图像
res = cv2.resize(img, (2 * width, 2 * height),
interpolation=cv2.INTER_CUBIC)
cv2.imwrite('scaleImg.png', res)
print("保存完毕!\n")
elif key == ord('e'):
# 边缘提取
img_gray = cv2.cv2tColor(img, cv2.COLOR_BGR2GRAY)
img_gb = cv2.GaussianBlur(img_gray, (5, 5), 0)
edges = cv2.Canny(img_gray, 100, 200)
cv2.imshow('edge', edges)
cv2.imwrite('edges.png', edges)
cv2.waitKey(0)
cv2.destroyAllWindows()
elif key == ord('b'):
# 图像信息二值化
th = 100
ret, binary1 = cv2.threshold(img, th, 255, cv2.THRESH_BINARY_INV)
ret, binary2 = cv2.threshold(img, th, 255, cv2.THRESH_BINARY)
ret, binary3 = cv2.threshold(img, th, 255, cv2.THRESH_TRUNC)
ret, binary4 = cv2.threshold(img, th, 255, cv2.THRESH_TOZERO)
ret, binary5 = cv2.threshold(img, th, 255, cv2.THRESH_TOZERO_INV)
#ret,binary6=cv2.threshold(img,th,255,cv2.THRESH_OTSU)
#ret,binary7=cv2.threshold(img,th,255,cv2.THRESH_TRIANGLE)
cv2.imshow("THRESH_BINARY_INV", binary1)
cv2.imshow("THRESH_BINARY", binary2)
cv2.imshow("THRESH_TRUNC", binary3)
cv2.imshow("THRESH_TOZERO", binary4)
cv2.imshow("THRESH_TOZERO_INV", binary5)
#cv2.imshow("THRESH_OTSU",binary6)
#cv2.imshow("THRESH_TRIANGLE",binary7)
cv2.waitKey(0)
cv2.destroyAllWindows()
def load_image(path, gray=True):
im = cv2.imread(path)
if gray: im = cv2.cv2tColor(im, cv2.COLOR_BGR2RGB)
return im
C=2)
#%%
#%%
#Opencv2 notes
#Leitura
image = cv2.imread("images/obama.jpg")
obama = cv2.imread("images/obama.jpg")
fraude = load_image("images/fraude_1.jpeg")
np_image = np.array(image)
image = cv2.cv2tColor(image, cv2.COLOR_BGR2GRAY)
# plt.imshow(image)
#image = cv2.cv2tColor(image,cv2.COLOR_BGR2RGB)
# plt.imshow(image, cmap=cmap, norm=plt.Normalize(vmin=0, vmax=255))
# cv2.waitKey(0)
# cv2.imshow('Image',image)
#%%
#%%
#Resize
new_image = resizeImage(image, 0.5)
# plt.subplot(121)
# imshow(image, cmap="gray")
# plt.subplot(122)
# imshow(new_image, cmap="gray")
image = new_image.copy()
def cv2image_to_pygame(image):
"""Convert cv2image into a pygame image"""
image_rgb = cv2.CreateMat(image.height, image.width, cv2.cv2_8UC3)
cv2.cv2tColor(image, image_rgb, cv2.cv2_BGR2RGB)
return pygame.image.frombuffer(image.tostring(), cv2.GetSize(image_rgb),
"RGB")
def cv2image_grayscale(cv2_image):
"""Converts a cv2image into grayscale"""
grayscale = cv2.CreateImage(cv2.GetSize(cv2_image), 8, 1)
cv2.cv2tColor(cv2_image, grayscale, cv2.cv2_RGB2GRAY)
return grayscale
diff_y = np.subtract(new_y, old_y)
diff_x = np.subtract(new_x, old_x)
ang = np.arctan2(diff_y, diff_x) * 180 / np.pi
mag = np.sqrt(diff_x * diff_x + diff_y * diff_y)
return ang, mag
ctr = 0
flag = 1
while (count < 250):
count += 1
if flag == 1:
flag = 0
frameName = 'View3/image' + str(count) + '.jpg'
frame = cv2.imread(frameName, 1)
frame_gray = cv2.cv2tColor(frame, cv2.COLOR_BGR2GRAY)
# calculate optical flow
p1, st, err = cv2.calcOpticalFlowPyrLK(old_gray, frame_gray, p0, None,
**lk_params)
# Select good points
good_new = p1[st == 1]
good_old = p0[st == 1]
# draw the tracks
for i, (new, old) in enumerate(zip(good_new, good_old)):
a, b = new.ravel()
c, d = old.ravel()
#mask = cv2.line(mask, (a,b),(c,d), (0,255,0), 2)
frame = cv2.circle(frame, (a, b), 5, (0, 255, 0), -1)
#img = cv2.add(frame,mask)
#draw_flow(frame_gray, good_new, good_old, step=16)
cv2.imshow('frame', frame)
import cv2
src = cv2.imread("./test.png")
cv2.namedWindow("input", cv2.WINDOW_AUTOSIZE)
cv2.imshow("input", src)
gray = cv2.cv2tColor(src, cv2.COLOR_BGR2GRAY)
cv2.imwrite('gray.png', gray)
cv2.imshow("gray", gray)
cv2.waitKey(0)
cv2.destroyAllWindows()
