本文整理汇总了Python中cv.CreateImage方法的典型用法代码示例。如果您正苦于以下问题:Python cv.CreateImage方法的具体用法?Python cv.CreateImage怎么用?Python cv.CreateImage使用的例子?那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类cv
的用法示例。
在下文中一共展示了cv.CreateImage方法的11个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: rotate
# 需要导入模块: import cv [as 别名]
# 或者: from cv import CreateImage [as 别名]
def rotate(self, degrees):
if (degrees > 180):
# Flip around both axes
cv.Flip(self.image, None, -1)
degrees = degrees - 180
img = self.image
size = cv.GetSize(img)
if (degrees / 90 % 2):
new_size = (size[1], size[0])
center = ((size[0] - 1) * 0.5, (size[0] - 1) * 0.5)
else:
new_size = size
center = ((size[0] - 1) * 0.5, (size[1] - 1) * 0.5)
mapMatrix = cv.CreateMat(2, 3, cv.CV_64F)
cv.GetRotationMatrix2D(center, degrees, 1.0, mapMatrix)
dst = cv.CreateImage(new_size, self.image_depth, self.image_channels)
cv.SetZero(dst)
cv.WarpAffine(img, dst, mapMatrix)
self.image = dst
示例2: gen_image
# 需要导入模块: import cv [as 别名]
# 或者: from cv import CreateImage [as 别名]
def gen_image(self, size, color_value):
img0 = cv.CreateImage(size, self.image_depth, self.image_channels)
if color_value == 'transparent':
color = (255, 255, 255, 255)
else:
color = self.parse_hex_color(color_value)
if not color:
raise ValueError('Color %s is not valid.' % color_value)
cv.Set(img0, color)
return img0
示例3: resize
# 需要导入模块: import cv [as 别名]
# 或者: from cv import CreateImage [as 别名]
def resize(self, width, height):
thumbnail = cv.CreateImage(
(int(round(width, 0)), int(round(height, 0))),
self.image_depth,
self.image_channels
)
cv.Resize(self.image, thumbnail, cv.CV_INTER_AREA)
self.image = thumbnail
示例4: crop
# 需要导入模块: import cv [as 别名]
# 或者: from cv import CreateImage [as 别名]
def crop(self, left, top, right, bottom):
new_width = right - left
new_height = bottom - top
cropped = cv.CreateImage(
(new_width, new_height), self.image_depth, self.image_channels
)
src_region = cv.GetSubRect(self.image, (left, top, new_width, new_height))
cv.Copy(src_region, cropped)
self.image = cropped
示例5: image_data_as_rgb
# 需要导入模块: import cv [as 别名]
# 或者: from cv import CreateImage [as 别名]
def image_data_as_rgb(self, update_image=True):
# TODO: Handle other formats
if self.image_channels == 4:
mode = 'BGRA'
elif self.image_channels == 3:
mode = 'BGR'
else:
mode = 'BGR'
rgb_copy = cv.CreateImage((self.image.width, self.image.height), 8, 3)
cv.CvtColor(self.image, rgb_copy, cv.CV_GRAY2BGR)
self.image = rgb_copy
return mode, self.image.tostring()
示例6: enable_alpha
# 需要导入模块: import cv [as 别名]
# 或者: from cv import CreateImage [as 别名]
def enable_alpha(self):
if self.image_channels < 4:
with_alpha = cv.CreateImage(
(self.image.width, self.image.height), self.image_depth, 4
)
if self.image_channels == 3:
cv.CvtColor(self.image, with_alpha, cv.CV_BGR2BGRA)
else:
cv.CvtColor(self.image, with_alpha, cv.CV_GRAY2BGRA)
self.image = with_alpha
示例7: detect_and_draw
# 需要导入模块: import cv [as 别名]
# 或者: from cv import CreateImage [as 别名]
def detect_and_draw(img, cascade):
# allocate temporary images
gray = cv.CreateImage((img.width,img.height), 8, 1)
small_img = cv.CreateImage((cv.Round(img.width / image_scale),
cv.Round (img.height / image_scale)), 8, 1)
# convert color input image to grayscale
cv.CvtColor(img, gray, cv.CV_BGR2GRAY)
# scale input image for faster processing
cv.Resize(gray, small_img, cv.CV_INTER_LINEAR)
cv.EqualizeHist(small_img, small_img)
if(cascade):
t = cv.GetTickCount()
faces = cv.HaarDetectObjects(small_img, cascade, cv.CreateMemStorage(0),
haar_scale, min_neighbors, haar_flags, min_size)
t = cv.GetTickCount() - t
print "detection time = %gms" % (t/(cv.GetTickFrequency()*1000.))
if faces:
for ((x, y, w, h), n) in faces:
# the input to cv.HaarDetectObjects was resized, so scale the
# bounding box of each face and convert it to two CvPoints
pt1 = (int(x * image_scale), int(y * image_scale))
pt2 = (int((x + w) * image_scale), int((y + h) * image_scale))
cv.Rectangle(img, pt1, pt2, cv.RGB(255, 0, 0), 3, 8, 0)
print "x= "+str(x)+" y= "+str(y)+" w= "+str(w)+" h= "+str(h)
cv.ShowImage("Face detection", img)
示例8: process_file
# 需要导入模块: import cv [as 别名]
# 或者: from cv import CreateImage [as 别名]
def process_file(filenameIN, WIDTH = 31, HEIGHT = 31):
print "processing file: "+ filenameIN
if not (os.path.exists(filenameIN)):
print "file not found. Aborting."
return
else :
srcImg = cv.LoadImage(filenameIN,0)
res = cv.CreateImage( (WIDTH, HEIGHT), cv.IPL_DEPTH_8U, 1 )
cv.Set(res, 255)
xmin=WIDTH
xmax=0
ymin=HEIGHT
ymax=0
for i in range(srcImg.width):
for j in range(srcImg.height):
#print "xmax"
#print cv.Get2D(srcImg, j, i)
if cv.Get2D(srcImg, j, i)[0] == 0.0 :
#print "xin"
if i<xmin:
xmin = i
if i>xmax:
xmax = i
if j<ymin:
ymin=j
if j>ymax:
ymax=j
offsetx = (WIDTH - (xmax-xmin))/2
offsety = (HEIGHT - (ymax-ymin))/2
#print 'WIDTH',WIDTH,"offset",offsety,offsetx
for i in range(xmax-xmin):
for j in range(ymax-ymin):
if ((offsety+j>0) and (offsety+j<res.height) and (offsetx+i>0) and (offsetx+i<res.width)):
#print "haha"
cv.Set2D(res, offsety+j, offsetx+i, cv.Get2D(srcImg, ymin+j, xmin+i))
cv.SaveImage(filenameIN, res)
示例9: detect_and_draw
# 需要导入模块: import cv [as 别名]
# 或者: from cv import CreateImage [as 别名]
def detect_and_draw(img):
t1 = time.time()
# allocate temporary images
gray = cv.CreateImage((img.width,img.height), 8, 1)
small_img = cv.CreateImage((cv.Round(img.width / image_scale),
cv.Round (img.height / image_scale)), 8, 1)
# blur the source image to reduce color noise
cv.Smooth(img, img, cv.CV_BLUR, 3);
hsv_img = cv.CreateImage(cv.GetSize(img), 8, 3)
cv.CvtColor(img, hsv_img, cv.CV_BGR2HSV)
thresholded_img = cv.CreateImage(cv.GetSize(hsv_img), 8, 1)
#cv.InRangeS(hsv_img, (120, 80, 80), (140, 255, 255), thresholded_img)
# White
sensitivity = 15
cv.InRangeS(hsv_img, (0, 0, 255-sensitivity), (255, sensitivity, 255), thresholded_img)
# Red
#cv.InRangeS(hsv_img, (0, 150, 0), (5, 255, 255), thresholded_img)
# Blue
#cv.InRangeS(hsv_img, (100, 50, 50), (140, 255, 255), thresholded_img)
# Green
#cv.InRangeS(hsv_img, (40, 50, 50), (80, 255, 255), thresholded_img)
mat=cv.GetMat(thresholded_img)
moments = cv.Moments(mat, 0)
area = cv.GetCentralMoment(moments, 0, 0)
# scale input image for faster processing
cv.Resize(gray, small_img, cv.CV_INTER_LINEAR)
cv.EqualizeHist(small_img, small_img)
if(area > 5000):
#determine the x and y coordinates of the center of the object
#we are tracking by dividing the 1, 0 and 0, 1 moments by the area
x = cv.GetSpatialMoment(moments, 1, 0)/area
y = cv.GetSpatialMoment(moments, 0, 1)/area
x = int(round(x))
y = int(round(y))
#create an overlay to mark the center of the tracked object
overlay = cv.CreateImage(cv.GetSize(img), 8, 3)
cv.Circle(overlay, (x, y), 2, (0, 0, 0), 20)
cv.Add(img, overlay, img)
#add the thresholded image back to the img so we can see what was
#left after it was applied
#cv.Merge(thresholded_img, None, None, None, img)
t2 = time.time()
message = "Color tracked!"
print "detection time = %gs x=%d,y=%d" % ( round(t2-t1,3) , x, y)
cv.ShowImage("Color detection", img)
示例10: run
# 需要导入模块: import cv [as 别名]
# 或者: from cv import CreateImage [as 别名]
def run(self):
while True:
img = cv.QueryFrame( self.capture )
t1 = time.time()
#blur the source image to reduce color noise
cv.Smooth(img, img, cv.CV_BLUR, 3);
#convert the image to hsv(Hue, Saturation, Value) so its
#easier to determine the color to track(hue)
hsv_img = cv.CreateImage(cv.GetSize(img), 8, 3)
cv.CvtColor(img, hsv_img, cv.CV_BGR2HSV)
#limit all pixels that don't match our criteria, in this case we are
#looking for purple but if you want you can adjust the first value in
#both turples which is the hue range(120,140). OpenCV uses 0-180 as
#a hue range for the HSV color model
thresholded_img = cv.CreateImage(cv.GetSize(hsv_img), 8, 1)
# White
sensitivity = 10
cv.InRangeS(hsv_img, (0, 0, 255-sensitivity), (255, sensitivity, 255), thresholded_img)
# Red
#cv.InRangeS(hsv_img, (0, 150, 0), (5, 255, 255), thresholded_img)
# Blue
#cv.InRangeS(hsv_img, (100, 50, 50), (140, 255, 255), thresholded_img)
# Green
#cv.InRangeS(hsv_img, (40, 50, 50), (80, 255, 255), thresholded_img)
#determine the objects moments and check that the area is large
#enough to be our object
mat=cv.GetMat(thresholded_img)
moments = cv.Moments(mat, 0)
area = cv.GetCentralMoment(moments, 0, 0)
#there can be noise in the video so ignore objects with small areas
if(area > 10000):
#determine the x and y coordinates of the center of the object
#we are tracking by dividing the 1, 0 and 0, 1 moments by the area
x = cv.GetSpatialMoment(moments, 1, 0)/area
y = cv.GetSpatialMoment(moments, 0, 1)/area
x = int(round(x))
y = int(round(y))
#create an overlay to mark the center of the tracked object
overlay = cv.CreateImage(cv.GetSize(img), 8, 3)
cv.Circle(overlay, (x, y), 2, (255, 255, 255), 20)
cv.Add(img, overlay, img)
#add the thresholded image back to the img so we can see what was
#left after it was applied
t2 = time.time()
cv.Merge(thresholded_img, None, None, None, img)
print "detection time = %gs x=%d,y=%d" % ( round(t2-t1,3) , x, y)
#display the image
cv.ShowImage(color_tracker_window, img)
if cv.WaitKey(10) == 27:
break
示例11: FPV_thread
# 需要导入模块: import cv [as 别名]
# 或者: from cv import CreateImage [as 别名]
def FPV_thread():
global camera_index
global capture
global WINDOW_NAME
global latest_frame
global FPV_thread_stop
global overlay_message # shared with application return results
global face_position # shared with application return results
FPV_init()
cv.NamedWindow(WINDOW_NAME, cv.CV_WINDOW_NORMAL)
cv.MoveWindow(WINDOW_NAME, 0, 0)
width_scale = 1.0
height_scale = 1.0
while True:
frame = cv.QueryFrame(capture)
cv.Flip(frame, None, 1)
#copy to buffer
frame_lock.acquire()
original_imagesize = (0,0)
resized_imagesize = (0,0)
if not latest_frame:
latest_frame = cv.CreateImage((640, 480), frame.depth, frame.nChannels)
original_imagesize = cv.GetSize(frame)
resized_imagesize = cv.GetSize(latest_frame)
width_scale = original_imagesize[0]*1.0/resized_imagesize[0]
height_scale = original_imagesize[1]*1.0/resized_imagesize[1]
cv.Resize(frame, latest_frame)
frame_lock.release()
#Display Result
text_start_point = (10, 50)
cv.PutText(frame, overlay_message, text_start_point, font, cv.Scalar(255,255,255))
cv.Rectangle(frame, text_start_point, (original_imagesize[0], 100), cv.Scalar(0,0,0), thickness=cv.CV_FILLED)
if face_position[0] > 0.0:
point1 = (int(face_position[0]*width_scale), int(face_position[1]*height_scale))
point2 = (int((face_position[0] + face_position[2])*width_scale), \
int((face_position[1]+face_position[3])*height_scale))
cv.Rectangle(frame, point1, point2, \
cv.Scalar(255, 255, 255), thickness=2)
cv.ShowImage(WINDOW_NAME, frame)
cv.ResizeWindow(WINDOW_NAME, 200, 100)
cv.NamedWindow(WINDOW_NAME, cv.CV_WINDOW_NORMAL);
cv.SetWindowProperty(WINDOW_NAME, 0, cv.CV_WINDOW_FULLSCREEN);
c = cv.WaitKey(10)
if c == ord('q'):
break
print "[INFO] FPV Thread is finished"
FPV_thread_stop = True
FPV_close()