2020-01-19 14:28:02 -0600
| commented question | How to group points using treshold? @LBerger, @berak Thanks a lot!!
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2020-01-19 13:39:33 -0600
| asked a question | How to group points using treshold? How to group points using treshold?
I have points list , from rectangle detector
points_list = [(1853, 1054), (1900, |
2018-06-10 19:11:28 -0600
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2017-05-31 23:16:43 -0600
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2016-06-10 07:13:43 -0600
| commented answer | What is MORPH_RECT parameters? |
2016-06-10 04:58:18 -0600
| asked a question | What is MORPH_RECT parameters? What does it mean 21 and 10 parameters? in cv2.getStructuringElement(cv2.MORPH_RECT, (21, 21), (10, 10))
I can understand from docs. |
2016-06-09 08:48:08 -0600
| asked a question | How to reduce noise using scharr filter? I have code #!/usr/bin/env python
# -*- coding= utf-8 -*-
import sys
import numpy as np
import cv2
import math
filename = sys.argv[1]
cap = cv2.VideoCapture(filename)
cap.set(cv2.cv.CV_CAP_PROP_POS_MSEC, 300000)
scale = 1
delta = 0
ddepth = cv2.CV_16S
while(True):
success, img = cap.read()
img = cv2.GaussianBlur(img,(3,3),0)
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
#Scharr filter
scharr_grad_x = cv2.Scharr(gray,ddepth,1,0)
scharr_grad_y = cv2.Scharr(gray,ddepth,0,1)
scharr_abs_grad_x = cv2.convertScaleAbs(scharr_grad_x)
scharr_abs_grad_y = cv2.convertScaleAbs(scharr_grad_y)
#remove noize after scharr filter
###scharr = np.hypot(scharr_abs_grad_x, scharr_abs_grad_y)
###mean = np.mean(scharr);
###scharr[scharr <= mean] = 0;
scharr = cv2.add(scharr_abs_grad_x,scharr_abs_grad_y)
cv2.imshow('scharr',scharr)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
I want to reduce noise. I found something like this scharr = np.hypot(scharr_abs_grad_x, scharr_abs_grad_y)
mean = np.mean(scharr);
scharr[scharr <= mean] = 0;
Scharr. Scharr without noise I need. How can I implement it in my code? |
2016-03-01 09:12:12 -0600
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2015-06-22 03:19:20 -0600
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2013-04-04 22:59:05 -0600
| commented answer | cv2.so missing after opencv installed |
2013-04-03 09:16:20 -0600
| asked a question | cv2.so missing after opencv installed Today I tried to install opencv 2.4.4 to Ubuntu 12.10 The cv2.so missed, so import cv2 not work. root@-:~# find / -name "cv.py"
/root/opencv-2.4.4/modules/python/src2/cv.py
root@-:~# find / -name "cv2.so"
root@-:~#
Python 2.7.3 Where is cv2.so ? My setup steps look like wget http://downloads.sourceforge.net/project/opencvlibrary/opencv-unix/2.4.4/OpenCV-2.4.4a.tar.bz2
tar -xjf OpenCV-2.4.4a.tar.bz2
cd opencv-2.4.4
mkdir release
cd release
cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local -D BUILD_PYTHON_SUPPORT=ON ..
make && make install
echo "/usr/local/lib" >> /etc/ld.so.conf.d/opencv.conf
ldconfig
echo "PKG_CONFIG_PATH=$PKG_CONFIG_PATH:/usr/local/lib/pkgconfig" >> /etc/bash.bashrc
echo "export PKG_CONFIG_PATH" >> /etc/bash.bashrc
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2013-04-03 09:10:13 -0600
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2013-04-03 09:10:03 -0600
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2013-03-25 07:43:28 -0600
| commented answer | How to detect semi transparent logo location on video? I don't know how logo looks like before script start. Automate detection unchanged area on video without any templates. |
2013-03-24 09:37:16 -0600
| asked a question | How to detect semi transparent logo location on video? I make python script which auto detect stationary object on video (to simplify the idea - let it be a logo). I don't know logo location, because I can't see video. I start script in console. The idea of script - auto detection, not manual work. But I know that logo is on all video frames, and it located as usual in one of the coner. I have small test videos: https://dl.dropbox.com/u/100403694/1.mp4 https://dl.dropbox.com/u/100403694/2.mp4 https://dl.dropbox.com/u/100403694/3.mp4 https://dl.dropbox.com/u/100403694/4.mp4 All tests seems to be done except 2.mp4 Script can't detect logo on video 2.mp4 This is my script. Usage script.py 2.mp4 #!/usr/bin/env python
# -*- coding= utf-8 -*-
import sys
import cv2
import numpy as np
from time import clock
tracked_contours = []
class Contour():
def __init__(self, contour):
self.data = get_contour_data(contour)
self.pixel_error = 5
self.score = 0
def __eq__(self, other):
for i in range(len(self.data)):
if abs(self.data[i]-other.data[i]) > self.pixel_error:
return False
return True
def get_contour_data(contour):
xx = np.array([ a[0][0] for a in contour ])
yy = np.array([ a[0][1] for a in contour ])
return [xx.min(), yy.min(), xx.max(), yy.max()]
def check_contours(contours, count, img):
for tracked_contour in tracked_contours:
if count % 2 == 0:
tracked_contour.score -= 1
if tracked_contour.score < 0:
tracked_contours.remove(tracked_contour)
for contour in contours:
c = Contour(contour)
if c in tracked_contours:
i = tracked_contours.index(c)
tracked_contours[i].score += 1
cv2.rectangle(img, (tracked_contours[i].data[0], \
tracked_contours[i].data[1]), (tracked_contours[i].data[2], \
tracked_contours[i].data[3]), (tracked_contours[i].score*10, tracked_contours[i].score*5, tracked_contours[i].score), tracked_contours[i].score)
if tracked_contours[i].score > 40:
return True, c
else: tracked_contours.append(c)
return False, None
def drawContours(contours, img):
for contour in contours:
data = get_contour_data(contour)
cv2.rectangle(img, (data[0], data[1]), (data[2], data[3]), (255,0,0))
def detect(file_name):
c = cv2.VideoCapture(file_name)
_,f = c.read()
f = cv2.cvtColor(f, cv2.COLOR_BGR2GRAY)
avg = np.float32(f)
cv2.namedWindow("img")
cv2.namedWindow("grey")
cv2.namedWindow("avg")
t = 0
count = 0
while(1):
if t % 5 != 0:
_,f = c.read()
if f == None:
exit(1)
t+=1
continue
count += 1
t += 1
_,f = c.read()
if f == None:
exit(1)
cv2.imshow('img',f)
f = np.float32(cv2.cvtColor(f, cv2.COLOR_BGR2GRAY))
cv2.accumulateWeighted(f, avg, 0.005)
res = cv2.convertScaleAbs(avg)
cv2.imshow('grey',res)
thresh, res = cv2.threshold(res, 200, 255, cv2.THRESH_BINARY)
kernel = cv2.getStructuringElement(cv2.MORPH_RECT,(40,40))
mat = cv2.dilate(res,kernel)
contours, hierarchy = cv2.findContours(mat,cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_TC89_L1)
res = cv2.cvtColor(res, cv2.COLOR_GRAY2BGR)
a,b = check_contours(contours, count, res)
if a == True:
cv2.rectangle(res, (b.data[0], b.data[1]), (b.data[2], b.data[3]), (0,255,0), 5)
cv2.imshow('avg',res)
k = cv2.waitKey(5000 ... (more) |
2013-02-08 07:22:01 -0600
| commented answer | Hot to detect logo region in video? I think about searching region with no difference. But how can I do it (I use python) ? I only need detect logo region, so I need data: X coordinate of the top left corner of the logo region, Y coordinate of the top left corner of the logo region, width of the logo region, height of the logo region. |
2013-02-08 07:18:09 -0600
| commented answer | Hot to detect logo region in video? Main condition: I don't know before video processing how the logo looks like. So I can't make and use any template. That is the salt of problem. |
2013-02-08 00:25:24 -0600
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2013-02-07 23:46:21 -0600
| asked a question | Hot to detect logo region in video? Hi, I have video. I need to detect logo region( x y width height). Region=red rectangle.
I do not know in advance how the logo looks like, I do not have its picture. |