Python cv2.pyrUp() Examples

The following are 26 code examples of cv2.pyrUp(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module cv2 , or try the search function .
Example #1
Source File: util.py    From DoNotSnap with GNU General Public License v3.0 6 votes vote down vote up 
def pyramid(image, minSize):
    yield image

    if image.shape[0] < minSize[0] and image.shape[1] < minSize[1]:
        # image too small - upscaling until we hit window level
        image = cv2.pyrUp(image)

        while (image.shape[0] <= minSize[0] or image.shape[1] <= minSize[1]):
            yield image
            image = cv2.pyrUp(image)
    else:
        # image too big - downscaling until we hit window level
        image = cv2.pyrDown(image)

        while (image.shape[0] >= minSize[0] or image.shape[1] >= minSize[1]):
            yield image
            image = cv2.pyrDown(image)


# Malisiewicz et al.
Example #2
Source File: Cartoonlization.py    From rabbitVE with GNU General Public License v3.0 6 votes vote down vote up 
def cartoonise(self, img_rgb, num_down, num_bilateral, medianBlur, D, sigmaColor, sigmaSpace):
        # 用高斯金字塔降低取样
        img_color = cv2.cvtColor(img_rgb, cv2.COLOR_RGB2BGR)
        for _ in range(num_down):
            img_color = cv2.pyrDown(img_color)
        # 重复使用小的双边滤波代替一个大的滤波
        for _ in range(num_bilateral):
            img_color = cv2.bilateralFilter(img_color, d=D, sigmaColor=sigmaColor, sigmaSpace=sigmaSpace)
        # 升采样图片到原始大小
        for _ in range(num_down):
            img_color = cv2.pyrUp(img_color)
        if not self.Save_Edge:
            img_cartoon = img_color
        else:
            img_gray = cv2.cvtColor(img_rgb, cv2.COLOR_RGB2GRAY)
            img_blur = cv2.medianBlur(img_gray, medianBlur)
            img_edge = cv2.adaptiveThreshold(img_blur, 255,
                                             cv2.ADAPTIVE_THRESH_GAUSSIAN_C,
                                             cv2.THRESH_BINARY,
                                             blockSize=self.Adaptive_Threshold_Block_Size,
                                             C=self.C)
            img_edge = cv2.cvtColor(img_edge, cv2.COLOR_GRAY2RGB)
            img_edge = cv2.resize(img_edge, img_color.shape[:2][::-1])
            img_cartoon = cv2.bitwise_and(img_color, img_edge)
        return cv2.cvtColor(img_cartoon, cv2.COLOR_RGB2BGR)
Example #3
Source File: CVAnalysis.py    From DE3-ROB1-CHESS with Creative Commons Attribution 4.0 International 5 votes vote down vote up 
def get_image_diff (img1, img2):
	"""
		Function: get_image_diff
		------------------------
		given two images, this finds the eroded/dilated difference 
		between them on a coarse grain.
		NOTE: assumes both are full-size, color
	"""
	#=====[ Step 1: convert to gray	]=====
	img1_gray = cv2.cvtColor (img1, cv2.COLOR_BGR2GRAY)
	img2_gray = cv2.cvtColor (img2, cv2.COLOR_BGR2GRAY)	

	#=====[ Step 2: downsample 	]=====
	img1_small = cv2.pyrDown(cv2.pyrDown(img1_gray))
	img2_small = cv2.pyrDown(cv2.pyrDown(img2_gray))	

	#=====[ Step 3: find differnece	]=====
	difference = img2_small - img1_small

	#=====[ Step 4: erode -> dilate	]=====
	kernel = np.ones ((4, 4), np.uint8)
	difference_ed = cv2.dilate(cv2.erode (difference, kernel), kernel)

	#=====[ Step 5: blow back up	]=====
	return cv2.pyrUp (cv2.pyrUp (difference_ed))






####################################################################################################
##############################[ --- CORNER DETECTION/DESCRIPTION--- ]###############################
####################################################################################################
Example #4
Source File: amplify_color.py    From Heart-rate-measurement-using-camera with Apache License 2.0 5 votes vote down vote up 
def reconstract_from_tensorlist(self,filter_tensor_list,levels=3):
        final=np.zeros(filter_tensor_list[-1].shape)
        for i in range(filter_tensor_list[0].shape[0]):
            up = filter_tensor_list[0][i]
            for n in range(levels-1):
                up=cv2.pyrUp(up)+filter_tensor_list[n + 1][i]
            final[i]=up
        return final    
    
    #butterworth bandpass filter
Example #5
Source File: amplify_color.py    From Heart-rate-measurement-using-camera with Apache License 2.0 5 votes vote down vote up 
def build_laplacian_pyramid(self, src,levels=3):
        gaussianPyramid = self.build_gaussian_pyramid(src, levels)
        pyramid=[]
        for i in range(levels,0,-1):
            GE=cv2.pyrUp(gaussianPyramid[i])
            L=cv2.subtract(gaussianPyramid[i-1],GE)
            pyramid.append(L)
        return pyramid
        
    #reconstract video from laplacian pyramid
Example #6
Source File: amplify_color.py    From Heart-rate-measurement-using-camera with Apache License 2.0 5 votes vote down vote up 
def reconstract_video(self,amp_video,origin_video,levels=3):
        final_video=np.zeros(origin_video.shape)
        for i in range(0,amp_video.shape[0]):
            img = amp_video[i]
            for x in range(levels):
                img=cv2.pyrUp(img)
            img=img+origin_video[i]
            final_video[i]=img
        return final_video
Example #7
Source File: lappyr.py    From PyCV-time with MIT License 5 votes vote down vote up 
def merge_lappyr(levels):
    img = levels[-1]
    for lev_img in levels[-2::-1]:
        img = cv2.pyrUp(img, dstsize=getsize(lev_img))
        img += lev_img
    return np.uint8(np.clip(img, 0, 255))
Example #8
Source File: lappyr.py    From PyCV-time with MIT License 5 votes vote down vote up 
def build_lappyr(img, leveln=6, dtype=np.int16):
    img = dtype(img)
    levels = []
    for i in xrange(leveln-1):
        next_img = cv2.pyrDown(img)
        img1 = cv2.pyrUp(next_img, dstsize=getsize(img))
        levels.append(img-img1)
        img = next_img
    levels.append(img)
    return levels
Example #9
Source File: turing.py    From PyCV-time with MIT License 5 votes vote down vote up 
def process_scale(a_lods, lod):
        d = a_lods[lod] - cv2.pyrUp(a_lods[lod+1])
        for i in xrange(lod):
            d = cv2.pyrUp(d)
        v = cv2.GaussianBlur(d*d, (3, 3), 0)
        return np.sign(d), v
Example #10
Source File: lappyr.py    From PyCV-time with MIT License 5 votes vote down vote up 
def merge_lappyr(levels):
    img = levels[-1]
    for lev_img in levels[-2::-1]:
        img = cv2.pyrUp(img, dstsize=getsize(lev_img))
        img += lev_img
    return np.uint8(np.clip(img, 0, 255))
Example #11
Source File: lappyr.py    From PyCV-time with MIT License 5 votes vote down vote up 
def build_lappyr(img, leveln=6, dtype=np.int16):
    img = dtype(img)
    levels = []
    for i in xrange(leveln-1):
        next_img = cv2.pyrDown(img)
        img1 = cv2.pyrUp(next_img, dstsize=getsize(img))
        levels.append(img-img1)
        img = next_img
    levels.append(img)
    return levels
Example #12
Source File: 03_pyramid_down_smaple.py    From Practical-Computer-Vision with MIT License 5 votes vote down vote up 
def main():
    # read an image 
    img = cv2.imread('../figures/flower.png')
    print(img.shape)

    lower_resolution1 = cv2.pyrDown(img)
    print(lower_resolution1.shape)

    lower_resolution2 = cv2.pyrDown(lower_resolution1)
    print(lower_resolution2.shape)

    lower_resolution3 = cv2.pyrDown(lower_resolution2)
    print(lower_resolution3.shape)

    higher_resolution3 = cv2.pyrUp(lower_resolution3)
    print(higher_resolution3.shape)

    higher_resolution2 = cv2.pyrUp(higher_resolution3)
    print(higher_resolution2.shape)

    higher_resolution1 = cv2.pyrUp(higher_resolution2)
    print(higher_resolution1.shape)




    
    # Do plot
    plot_lr_img(img, lower_resolution1, lower_resolution2, lower_resolution3)
    plot_hy_img(lower_resolution3, higher_resolution3, higher_resolution2, higher_resolution1)
Example #13
Source File: ImageFusion.py    From ImageStitch with MIT License 5 votes vote down vote up 
def reconstruct(self, input_pyramid):
        out = input_pyramid[0]
        for i in range(1, len(input_pyramid)):
            out = cv2.pyrUp(out)
            out = cv2.resize(out, (input_pyramid[i].shape[1],input_pyramid[i].shape[0]), interpolation = cv2.INTER_CUBIC)
            out = cv2.add(out, input_pyramid[i])
        return out
Example #14
Source File: ImageFusion.py    From ImageStitch with MIT License 5 votes vote down vote up 
def LaplacianPyramid(self, img, level):
        gp = self.GaussianPyramid(img, level)
        lp = [gp[level-1]]
        for i in range(level - 1, -1, -1):
            GE = cv2.pyrUp(gp[i])
            GE = cv2.resize(GE, (gp[i - 1].shape[1], gp[i - 1].shape[0]), interpolation=cv2.INTER_CUBIC)
            L = cv2.subtract(gp[i - 1], GE)
            lp.append(L)
        return lp, gp
Example #15
Source File: image_region_analysis.py    From DE3-ROB1-CHESS with Creative Commons Attribution 4.0 International 5 votes vote down vote up 
def show_image (image, title):
	cv2.imshow (title, cv2.pyrUp(cv2.pyrUp(image)))
Example #16
Source File: lappyr.py    From OpenCV-Python-Tutorial with MIT License 5 votes vote down vote up 
def build_lappyr(img, leveln=6, dtype=np.int16):
    img = dtype(img)
    levels = []
    for i in xrange(leveln-1):
        next_img = cv2.pyrDown(img)
        img1 = cv2.pyrUp(next_img, dstsize=getsize(img))
        levels.append(img-img1)
        img = next_img
    levels.append(img)
    return levels
Example #17
Source File: CVAnalysis_old.py    From DE3-ROB1-CHESS with Creative Commons Attribution 4.0 International 5 votes vote down vote up 
def get_image_diff (img1, img2):
	"""
		Function: get_image_diff
		------------------------
		given two images, this finds the eroded/dilated difference 
		between them on a coarse grain.
		NOTE: assumes both are full-size, color
	"""
	#=====[ Step 1: convert to gray	]=====
	img1_gray = cv2.cvtColor (img1, cv2.COLOR_BGR2GRAY)
	img2_gray = cv2.cvtColor (img2, cv2.COLOR_BGR2GRAY)	

	#=====[ Step 2: downsample 	]=====
	img1_small = cv2.pyrDown(cv2.pyrDown(img1_gray))
	img2_small = cv2.pyrDown(cv2.pyrDown(img2_gray))	

	#=====[ Step 3: find differnece	]=====
	difference = img2_small - img1_small

	#=====[ Step 4: erode -> dilate	]=====
	kernel = np.ones ((4, 4), np.uint8)
	difference_ed = cv2.dilate(cv2.erode (difference, kernel), kernel)

	#=====[ Step 5: blow back up	]=====
	return cv2.pyrUp (cv2.pyrUp (difference_ed))






####################################################################################################
##############################[ --- CORNER DETECTION/DESCRIPTION--- ]###############################
####################################################################################################
Example #18
Source File: Square.py    From DE3-ROB1-CHESS with Creative Commons Attribution 4.0 International 5 votes vote down vote up 
def show_edges (self):

		# diff = (self.image_region_normalized - self.last_image_region_normalized)
		# gray = cv2.cvtColor ()
		# cv2.imshow ('NORMALIZED', cv2.pyrUp(cv2.pyrUp(np.abs(self.image_region_normalized - self.last_image_region_normalized))))

		cv2.imshow ('EDGES', cv2.pyrUp(cv2.pyrUp(self.edges)))
		cv2.imshow ('REGION', cv2.pyrUp(cv2.pyrUp(self.image_region)))

		key = 0
		while key != 27:
			key = cv2.waitKey (30)
Example #19
Source File: util.py    From SPTM with MIT License 5 votes vote down vote up 
def double_upsampling(input):
  return cv2.pyrUp(cv2.pyrUp(input))
Example #20
Source File: Pyramids.py    From Finger-Detection-and-Tracking with BSD 2-Clause "Simplified" License 5 votes vote down vote up 
def main():
    image = cv2.imread("../data/4.2.03.tiff", 1)

    first_layer_down = cv2.pyrDown(image)
    first_layer_up = cv2.pyrUp(first_layer_down)

    laplasian = cv2.subtract(image, first_layer_up)

    cv2.imshow("Orignal Image", image)
    cv2.imshow("Laplasian Image", laplasian)

    cv2.waitKey(0)
    cv2.destroyAllWindows()
Example #21
Source File: multi_band_blending.py    From dual-fisheye-video-stitching with MIT License 5 votes vote down vote up 
def reconstruct(LS):
    img = LS[-1]
    for lev_img in LS[-2::-1]:
        img = cv2.pyrUp(img, lev_img.shape[1::-1])
        img += lev_img
    return img
Example #22
Source File: multi_band_blending.py    From dual-fisheye-video-stitching with MIT License 5 votes vote down vote up 
def LaplacianPyramid(img, leveln):
    LP = []
    for i in range(leveln - 1):
        next_img = cv2.pyrDown(img)
        LP.append(img - cv2.pyrUp(next_img, img.shape[1::-1]))
        img = next_img
    LP.append(img)
    return LP
Example #23
Source File: blending.py    From dual-fisheye-video-stitching with MIT License 5 votes vote down vote up 
def reconstruct(LS):
    img = LS[-1]
    for lev_img in LS[-2::-1]:
        img = cv2.pyrUp(img, lev_img.shape[1::-1])
        img += lev_img
    return img
Example #24
Source File: blending.py    From dual-fisheye-video-stitching with MIT License 5 votes vote down vote up 
def LaplacianPyramid(img, leveln):
    LP = []
    for i in range(leveln - 1):
        next_img = cv2.pyrDown(img)
        LP.append(img - cv2.pyrUp(next_img, img.shape[1::-1]))
        img = next_img
    LP.append(img)
    return LP
Example #25
Source File: turing.py    From OpenCV-Python-Tutorial with MIT License 5 votes vote down vote up 
def process_scale(a_lods, lod):
        d = a_lods[lod] - cv2.pyrUp(a_lods[lod+1])
        for i in xrange(lod):
            d = cv2.pyrUp(d)
        v = cv2.GaussianBlur(d*d, (3, 3), 0)
        return np.sign(d), v
Example #26
Source File: lappyr.py    From OpenCV-Python-Tutorial with MIT License 5 votes vote down vote up 
def merge_lappyr(levels):
    img = levels[-1]
    for lev_img in levels[-2::-1]:
        img = cv2.pyrUp(img, dstsize=getsize(lev_img))
        img += lev_img
    return np.uint8(np.clip(img, 0, 255))