When making a program to count seeds, the contrast is poor on the image:
And a Backlight isn't possible.
Tried the following WaterShed Algorithms:
- [https://stackoverflow.com/questions/25789278/coffee-beans-separation-algorithm](https://stackoverflow.com/questions/25789278/coffee-beans-separation-algorithm)
- [https://codegolf.stackexchange.com/q/40831/71194](https://codegolf.stackexchange.com/q/40831/71194)
- [https://www.pyimagesearch.com/2015/11/02/watershed-opencv/](https://www.pyimagesearch.com/2015/11/02/watershed-opencv/)
Without success, due to the poor contrast and shadow between the Seeds.
To improve remove the shadow between the seeds, [GrabCut](https://docs.opencv.org/3.1.0/d8/d83/tutorial_py_grabcut.html) was tried.
import numpy as np
import cv2
from matplotlib import pyplot as plt
img = cv2.imread("C:\\image\\img.bmp")
mask = np.zeros(img.shape[:2],np.uint8)
bgdModel = np.zeros((1,65),np.float64)
fgdModel = np.zeros((1,65),np.float64)
rect = (0,0,1023,767)
cv2.grabCut(img,mask,rect,bgdModel,fgdModel,5,cv2.GC_INIT_WITH_RECT)
mask2 = np.where((mask==2)|(mask==0),0,1).astype('uint8')
img = img*mask2[:,:,np.newaxis]
cv2.imshow('Imagem', img)
cv2.waitKey(0)
cv2.imwrite('C:\\Users\\Desktop\\test\\result.bmp', img)
plt.imshow(img),plt.colorbar(),plt.show()
And the following result:
**Question**
It wasn't possible to remove the shadows between the seeds, to improve the performance of the watershed algorithm.
Is there a better way to remove the sadhows between objects?
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Remove Shadows Between Objects
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when I run the below code, I take below error. Can you help me ?
import cv2
import numpy as np
image = cv2.imread('yüz1.jpg')
faceCascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
greyImage = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)
faces = faceCascade.detectMultiScale(image,1.1,4)
for(x,y,w,h) in faces :
cv2.rectangle(image, (x,y), (x+w,y+h),(0,255,0),3)
cv2.imshow('faces', image)
cv2.waitKey(0)
cv2.destroyAllWindows()
"C:\Users\asus\Documents\Python Çalışma\venv\Scripts\python.exe" "C:/Users/asus/Documents/Python Çalışma/İmageProcessing/faceDetection.py"
Traceback (most recent call last):
File "C:/Users/asus/Documents/Python Çalışma/İmageProcessing/faceDetection.py", line 8, in
greyImage = cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)
cv2.error: OpenCV(3.4.3) C:\projects\opencv-python\opencv\modules\imgproc\src\color.cpp:181: error: (-215:Assertion failed) !_src.empty() in function 'cv::cvtColor'
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OpenCV-java341.dll is not getting generated
Hi I configured the open-contrib modules in cmake, when i execute the below command
cmake.exe --build . --config Release --target Install
OpenCV-java341.dll is not getting generated but opencv-341.jar gets generated with face folder.
Can you please help me in this as this is urgent
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Dataset used for training DNN Face Detector
I would like to know the source of the dataset used for the DNN based Face Detector corresponding to the model - res10_300x300_ssd_iter_140000_fp16.caffemodel.
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libpng warning: Image width is zero in IHDR
Hi, when i run my first OpenCV application in Java i receive that message from compiler:
Running DetectFaceDemo
Detected 0 faces
Writing faceDetection.png
*libpng warning: Image width is zero in IHDR
libpng warning: Image height is zero in IHDR
libpng error: Invalid IHDR data*
i try the example from: http://docs.opencv.org/2.4.4-beta/doc/tutorials/introduction/desktop_java/java_dev_intro.html
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↧
OpenCV.js Unable to load cascade file
Hi. I'm having an issue where my project is unable to load the cascade file I want to use. Here is the code that is causing the problem.
let faceCascade = 'haarcascade_frontalface_default.xml';
// Build and load the cascade file
let utils = new Utils('errorMessage');
utils.createFileFromUrl(faceCascade, faceCascade, () => {
console.log('Cascade ready.');
classifier.load(faceCascade)
});
if(!classifier.load(faceCascade)){
console.log('Unable to load cascade file.');
}
It manages get within the createFileFromUrl statement and execute the console.log. However, it is unable to load the xml file when classifier.load is called. There are no errors in the browser but the if statement is executed and confirms that it hasn't been loaded.
I've tried giving the full path to the file, I've tried using alternate cascade files and I've tried loading the files from a separate folder. None of these seem to effect anything. I'm running the web page from a Xampp server and I'm using OpenCV.js version 3.4.3.
I have no idea what the issue could be. Any help would be appreciated, cheers.
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minAreaRect internal Error
I am trying to run the following code but an error arise when I call the minAreaRect but it goes well through boundingRect. I am confused because these two functions take the same input.
The image is in this link: [img](/upfiles/15396199619181676.png)
#!/usr/bin/env python
import numpy as np
import cv2
img = cv2.imread('test.png', cv2.IMREAD_COLOR)
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
# define range of blue color in HSV
gimp_lower_blue = np.array([210, 60, 60])
gimp_upper_blue = np.array([230, 80, 80])
# https://stackoverflow.com/questions/10948589/choosing-the-correct-upper-and-lower-hsv-boundaries-for-color-detection-withcv
gimp_to_opencv_hsv = np.array([180.0/360, 255.0/100, 255.0/100])
lower_blue = np.multiply(gimp_lower_blue, gimp_to_opencv_hsv)
upper_blue = np.multiply(gimp_upper_blue, gimp_to_opencv_hsv)
# Threshold the HSV image to get only blue colors
mask = cv2.inRange(hsv, lower_blue, upper_blue)
contours = cv2.findContours(
mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
x, y, w, h = cv2.boundingRect(contours[0])
cv2.rectangle(img, (x-3, y-3), (x+w+3, y+h+3), (0, 255, 0), 5)
cv2.imshow('image', img)
cv2.waitKey()
rect = cv2.minAreaRect(contours[0])
box = cv2.boxPoints(rect)
box = np.int0(box)
cv2.drawContours(img, [box], 0, (0, 0, 255), 2)
cv2.imshow('image', img)
cv2.waitKey(0)
The first line of the error is: OpenCV Error: Assertion failed (total >= 0 && (depth == CV_32F || depth == CV_32S)) in convexHull, file /build/opencv-L2vuMj/opencv-3.2.0+dfsg/modules/imgproc/src/convhull.cpp, line 136
↧
Hologram Detection With Irregular Patterns
Is there any way to detect holograms that are embedded in id cards which aren't that visible. I've searched stack and this forum for similar ones using mobile ar but the holograms there were quite visible mine aint. Check this out for example: https://www.youtube.com/watch?v=PF6Fow7nIuY&feature=youtu.be
↧
Fire detecion and smoke detection
I want to create 2 binary classifier model
1) Fire detection
2) Smoke detection
Can you please suggest which will be better to train LBP cascade(It require annotated data) or SVM/Logistic regression/ or any other deep learning binary classifier(Inception-v3, Dense-net)?
I have a positive and negative dataset of both fire and smoke dataset.
My concern here is speed(accuracy around 80% is acceptable)!
↧
↧
LINK : fatal error LNK1104: cannot open file '..\..\lib\Debug\opencv_xfeatures2d343d.lib'
When I install OpenCV 3.4.3 source code using cmake and then I opened this project and target "Debug" and build, they show this error message:
**LINK : fatal error LNK1104: cannot open file '..\..\lib\Debug\opencv_xfeatures2d343d.lib'
LINK : fatal error LNK1104: cannot open file '..\..\lib\Debug\opencv_xfeatures2d343d.lib'**
I would like to know where I need to modify and where I made wrong.
Thank you in advance,
↧
Show video after few seconds
Hello
How can I show (on screen) the webcam video with a time lag of few seconds?
I'm sport's'coach and I want to film my players and show them their actions "in live" with a video projector.
I'm using python and I've just discover opencv.
Sorry for my language; I'm french...
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Reduce Blurring/Warping of image after repeated warpAffine
My code uses input from a rotary encoder connected to a Rapsberry Pi send over TCP:
num_rows, num_cols = img.shape[:2]
data = s.recv(BUFFER_SIZE)
speed = data.decode("utf-8")
print("Speed = ", speed)
translation_matrix = np.float32([ [1,0,np.float32(speed)], [0,1,0] ])
img = cv2.warpAffine(img, translation_matrix, (num_cols, num_rows))
I use this input to make a translation matrix so that i can shift my image according the input from the encoder.
My initial Image looks like this:
After a few warpAffines it looks like this:
Is there a way to reduce the blurring/warping of the image while still being able to move it in a nice way
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Read from file and write to another in opencv-python
Hey Guys, can anyone please share with me how i can read data from a file and write selective data from this file to another file? example :
I have 10 files from a.txt, b.txt....j.txt and each file has 5 rows and 3 columns. I want to read the first 3 rows and the third column from each file and then save it as .xml file. Can anyone help me on how to achieve this?
I just started with opencv and python last week so please treat me as beginner. I am reading up on this in the meantime but any help would be appreciated. Also i would be grateful if some code and/or reference code can be provided to help me visualize.
↧
↧
Help with centroid python
I am doing a college project to count eggs and found that when eggs come together a lot, the centroid recognizes as just one object (as in the image below).
I wanted to know if there is any process, to be able to recognize the eggs apart.
**Sorry for my English, because I used google translator.
↧
OpenCV 3.4.3 imread not able to load tiff image
Hey there,
I just compiled OpenCV 3.4.3 on Kubuntu 18.04, which worked like a charm.
Unfortunately I am not able to load a tif file. The minimal example
#include
#include
#include
using namespace std;
using namespace cv;
int main(int argc, char** argv)
{
if(argc < 2)
{
cout<<"usage: "< /modules/imgcodecs/test/
and started
> ./opencv_test_imgcodecs
which resulted into
[----------] 6 tests from Imgcodecs_Tiff
[ RUN ] Imgcodecs_Tiff.decode_tile16384x16384
[ OK ] Imgcodecs_Tiff.decode_tile16384x16384 (4584 ms)
[ RUN ] Imgcodecs_Tiff.write_read_16bit_big_little_endian
[ OK ] Imgcodecs_Tiff.write_read_16bit_big_little_endian (0 ms)
[ RUN ] Imgcodecs_Tiff.decode_tile_remainder
/home/stefan/clibs/src/opencv-3.4.3/modules/imgcodecs/test/test_tiff.cpp:107: Failure
Value of: img.empty()
Actual: true
Expected: false
[ FAILED ] Imgcodecs_Tiff.decode_tile_remainder (0 ms)
[ RUN ] Imgcodecs_Tiff.decode_infinite_rowsperstrip
[ OK ] Imgcodecs_Tiff.decode_infinite_rowsperstrip (1 ms)
[ RUN ] Imgcodecs_Tiff.readWrite_32FC1
/home/stefan/clibs/src/opencv-3.4.3/modules/imgcodecs/test/test_tiff.cpp:156: Failure
Value of: img.empty()
Actual: true
Expected: false
[ FAILED ] Imgcodecs_Tiff.readWrite_32FC1 (0 ms)
[ RUN ] Imgcodecs_Tiff.imdecode_no_exception_temporary_file_removed
/home/stefan/clibs/src/opencv-3.4.3/modules/imgcodecs/test/test_tiff.cpp:248: Failure
Value of: img.empty()
Actual: true
Expected: false
[ FAILED ] Imgcodecs_Tiff.imdecode_no_exception_temporary_file_removed (0 ms)
[----------] 6 tests from Imgcodecs_Tiff (4585 ms total)
[----------] 1 test from Imgcodecs_Tiff_Modes
[ RUN ] Imgcodecs_Tiff_Modes.write_multipage
Speicherzugriffsfehler (Speicherabzug geschrieben)
An example image is [C:\fakepath\loremA.tiff](/upfiles/15397085434419976.tiff)
The output of my cv::getBuildInformation() is
General configuration for OpenCV 3.4.3 =====================================
Version control: unknown
Extra modules:
Location (extra): /home/stefan/clibs/src/opencv_contrib-3.4.3/modules
Version control (extra): unknown
Platform:
Timestamp: 2018-10-16T16:05:05Z
Host: Linux 4.15.0-36-generic x86_64
CMake: 3.10.2
CMake generator: Unix Makefiles
CMake build tool: /usr/bin/make
Configuration: Release
CPU/HW features:
Baseline: SSE SSE2 SSE3
requested: SSE3
Dispatched code generation: SSE4_1 SSE4_2 FP16 AVX AVX2 AVX512_SKX
requested: SSE4_1 SSE4_2 AVX FP16 AVX2 AVX512_SKX
SSE4_1 (5 files): + SSSE3 SSE4_1
SSE4_2 (2 files): + SSSE3 SSE4_1 POPCNT SSE4_2
FP16 (2 files): + SSSE3 SSE4_1 POPCNT SSE4_2 FP16 AVX
AVX (6 files): + SSSE3 SSE4_1 POPCNT SSE4_2 AVX
AVX2 (11 files): + SSSE3 SSE4_1 POPCNT SSE4_2 FP16 FMA3 AVX AVX2
AVX512_SKX (1 files): + SSSE3 SSE4_1 POPCNT SSE4_2 FP16 FMA3 AVX AVX2 AVX_512F AVX512_SKX
C/C++:
Built as dynamic libs?: YES
C++11: YES
C++ Compiler: /usr/bin/c++ (ver 7.3.0)
C++ flags (Release): -fsigned-char -W -Wall -Werror=return-type -Werror=non-virtual-dtor -Werror=address -Werror=sequence-point -Wformat -Werror=format-security -Wmissing-declarations -Wundef -Winit-self -Wpointer-arith -Wshadow -Wsign-promo -Wuninitialized -Winit-self -Wsuggest-override -Wno-narrowing -Wno-delete-non-virtual-dtor -Wno-comment -Wimplicit-fallthrough=3 -fdiagnostics-show-option -Wno-long-long -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections -msse -msse2 -msse3 -fvisibility=hidden -fvisibility-inlines-hidden -O3 -DNDEBUG -DNDEBUG
C++ flags (Debug): -fsigned-char -W -Wall -Werror=return-type -Werror=non-virtual-dtor -Werror=address -Werror=sequence-point -Wformat -Werror=format-security -Wmissing-declarations -Wundef -Winit-self -Wpointer-arith -Wshadow -Wsign-promo -Wuninitialized -Winit-self -Wsuggest-override -Wno-narrowing -Wno-delete-non-virtual-dtor -Wno-comment -Wimplicit-fallthrough=3 -fdiagnostics-show-option -Wno-long-long -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections -msse -msse2 -msse3 -fvisibility=hidden -fvisibility-inlines-hidden -g -O0 -DDEBUG -D_DEBUG
C Compiler: /usr/bin/cc
C flags (Release): -fsigned-char -W -Wall -Werror=return-type -Werror=non-virtual-dtor -Werror=address -Werror=sequence-point -Wformat -Werror=format-security -Wmissing-declarations -Wmissing-prototypes -Wstrict-prototypes -Wundef -Winit-self -Wpointer-arith -Wshadow -Wuninitialized -Winit-self -Wno-narrowing -Wno-comment -Wimplicit-fallthrough=3 -fdiagnostics-show-option -Wno-long-long -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections -msse -msse2 -msse3 -fvisibility=hidden -O3 -DNDEBUG -DNDEBUG
C flags (Debug): -fsigned-char -W -Wall -Werror=return-type -Werror=non-virtual-dtor -Werror=address -Werror=sequence-point -Wformat -Werror=format-security -Wmissing-declarations -Wmissing-prototypes -Wstrict-prototypes -Wundef -Winit-self -Wpointer-arith -Wshadow -Wuninitialized -Winit-self -Wno-narrowing -Wno-comment -Wimplicit-fallthrough=3 -fdiagnostics-show-option -Wno-long-long -pthread -fomit-frame-pointer -ffunction-sections -fdata-sections -msse -msse2 -msse3 -fvisibility=hidden -g -O0 -DDEBUG -D_DEBUG
Linker flags (Release):
Linker flags (Debug):
ccache: YES
Precompiled headers: NO
Extra dependencies: dl m pthread rt
3rdparty dependencies:
OpenCV modules:
To be built: aruco bgsegm bioinspired calib3d ccalib core datasets dnn dnn_objdetect dpm face features2d flann freetype fuzzy hdf hfs highgui img_hash imgcodecs imgproc java_bindings_generator line_descriptor ml objdetect optflow phase_unwrapping photo plot python_bindings_generator reg rgbd saliency sfm shape stereo stitching structured_light superres surface_matching text tracking ts video videoio videostab world xfeatures2d ximgproc xobjdetect xphoto
Disabled: js
Disabled by dependency: -
Unavailable: cnn_3dobj cudaarithm cudabgsegm cudacodec cudafeatures2d cudafilters cudaimgproc cudalegacy cudaobjdetect cudaoptflow cudastereo cudawarping cudev cvv java matlab ovis python2 python3 viz
Applications: tests perf_tests apps
Documentation: NO
Non-free algorithms: NO
GUI:
GTK+: YES (ver 3.22.30)
GThread : YES (ver 2.56.2)
GtkGlExt: NO
VTK support: NO
Media I/O:
ZLib: /usr/lib/x86_64-linux-gnu/libz.so (ver 1.2.11)
JPEG: /usr/lib/x86_64-linux-gnu/libjpeg.so (ver 80)
WEBP: /usr/lib/x86_64-linux-gnu/libwebp.so (ver encoder: 0x020e)
PNG: /usr/lib/x86_64-linux-gnu/libpng.so (ver 1.6.34)
TIFF: /usr/lib/x86_64-linux-gnu/libtiff.so (ver 42 / 4.0.9)
JPEG 2000: build (ver 1.900.1)
OpenEXR: /usr/lib/x86_64-linux-gnu/libImath.so /usr/lib/x86_64-linux-gnu/libIlmImf.so /usr/lib/x86_64-linux-gnu/libIex.so /usr/lib/x86_64-linux-gnu/libHalf.so /usr/lib/x86_64-linux-gnu/libIlmThread.so (ver 2.2.0)
HDR: YES
SUNRASTER: YES
PXM: YES
Video I/O:
DC1394: NO
FFMPEG: YES
avcodec: YES (ver 57.107.100)
avformat: YES (ver 57.83.100)
avutil: YES (ver 55.78.100)
swscale: YES (ver 4.8.100)
avresample: YES (ver 3.7.0)
GStreamer: NO
libv4l/libv4l2: NO
v4l/v4l2: linux/videodev2.h
Parallel framework: pthreads
Trace: YES (with Intel ITT)
Other third-party libraries:
Intel IPP: 2017.0.3 [2017.0.3]
at: /home/stefan/clibs/src/opencv-3.4.3/build/3rdparty/ippicv/ippicv_lnx
Intel IPP IW: sources (2017.0.3)
at: /home/stefan/clibs/src/opencv-3.4.3/build/3rdparty/ippicv/ippiw_lnx
Lapack: NO
Eigen: YES (ver 3.3.4)
Custom HAL: NO
Protobuf: build (3.5.1)
Python (for build): /usr/bin/python2.7
Java:
ant: NO
JNI: NO
Java wrappers: NO
Java tests: NO
Matlab: NO
Install to: /home/stefan/clibs/opencv_unstable
-----------------------------------------------------------------
↧
Picking range of HSV from video - huge variation on sample
I've created the program that picks up the pixel from the video and convert it from RGB to HSV. Then using range function it filter that colour on the video.
The problem is:
When I look at the video, the sample I'm picking the pixel from looks flat - in term of colour. But computer sees it as a huge variety of colours. Is it the low quality video from laptop camera, some kind of compression that mix colours on the level invisible for the eye?
Possible solution:
take a sample not from single pixel, but rather from few - 10 -20 pixels around cursor?
Samples taken literally 5mm from each other and results:
Code if you want to test it on your machine:
import cv2 as cv
import numpy as np
#variable with HSV value of measured pixel
px_hsv = []
#default variable of HSV range values,
#nothing special just anything to define new variable
min_h = 10
min_s = 10
min_v = 10
max_h = 10
max_s = 10
max_v = 10
#trackbars need some function to operate correctly,
#so I generated empty one
def nothing(_):
pass
#mouse function operate all events from mouse:
#- Move of cursor
#- LMB Double click
def mouse(event,x,y,flags,param):
global px_hsv, min_h, min_s, min_v, max_h, max_s, max_v
if event == cv.EVENT_MOUSEMOVE:
#showing converted HSV value of pixel under cursor
px = frame[x,y]
px_array = np.uint8([[px]])
px_hsv = cv.cvtColor(px_array,cv.COLOR_BGR2HSV)
elif event == cv.EVENT_LBUTTONDBLCLK:
#get x,y position of cursor and convert its value to HSV
px = frame[x,y]
px_array = np.uint8([[px]])
px_hsv = cv.cvtColor(px_array,cv.COLOR_BGR2HSV)
#set minimum and maximum values of range, of the selected colour,
#represented by pixel I double clicked on
#range is set to -20/+20. Is it enough?
min_h = (px_hsv[0][0][0]-20 if px_hsv[0][0][0]-20 > 0 else 0)
min_s = (px_hsv[0][0][1]-40 if px_hsv[0][0][1]-20 > 0 else 0)
min_v = (px_hsv[0][0][2]-40 if px_hsv[0][0][2]-20 > 0 else 0)
max_h = (px_hsv[0][0][0]+20 if px_hsv[0][0][0]+20 < 180 else 180)
max_s = (px_hsv[0][0][1]+20 if px_hsv[0][0][1]+20 < 255 else 255)
max_v = (px_hsv[0][0][2]+40 if px_hsv[0][0][2]+20 < 255 else 255)
#start recording
cap = cv.VideoCapture(0)
#create new window, video with main view directly
#from the camera and attach mouse operations to it
cv.namedWindow('video')
cv.setMouseCallback("video",mouse)
while True:
# Take each frame
_, frame = cap.read()
# Convert BGR to HSV
hsv = cv.cvtColor(frame, cv.COLOR_BGR2HSV)
# define range of color in HSV
cv.createTrackbar("H1", "video", min_h, 180, nothing)
cv.createTrackbar("S1", "video", min_s, 255, nothing)
cv.createTrackbar("V1", "video", min_v, 255, nothing)
cv.createTrackbar("H2", "video", max_h, 180, nothing)
cv.createTrackbar("S2", "video", max_s, 255, nothing)
cv.createTrackbar("V2", "video", max_v, 255, nothing)
h1 = cv.getTrackbarPos('H1', 'video')
s1 = cv.getTrackbarPos('S1', 'video')
v1 = cv.getTrackbarPos('V1', 'video')
h2 = cv.getTrackbarPos('H2', 'video')
s2 = cv.getTrackbarPos('S2', 'video')
v2 = cv.getTrackbarPos('V2', 'video')
lower = np.array([h1,s1,v1])
upper = np.array([h2,s2,v2])
# Threshold the HSV video to get only colour in defined range
mask = cv.inRange(hsv, lower, upper)
#text with HSV value on the main screen
pixel_hsv = " ".join(str(values) for values in px_hsv)
font = cv.FONT_HERSHEY_SIMPLEX
cv.putText(frame, "px HSV: "+pixel_hsv, (10, 260),
font, 1, (255, 255, 255), 1, cv.LINE_AA)
# Bitwise-AND mask and original video
cv.imshow('video',frame)
cv.imshow('mask',mask)
#click ESC to exit the program
key = cv.waitKey(5) & 0xFF
if key == 27:
break
cv.destroyAllWindows()
↧
solvePnP and problems with perspective
I feed 8 corners of the cube, but after reprojection sometimes (not for all images) the nearest point becomes the farthest and vice versa.
Can anybody explain the reason and how to cope with it?
↧
↧
How to implement multi-processing ?
Hi,
I tried to run face detection using multi processing I am getting below error
E:\git\opencv-dnn-demo\face_detectors>python sample.py
i am detect
i am detect
i am detect
i am detect
i am detect
i am detect
Traceback (most recent call last):
File "sample.py", line 17, in
pool.map(fd.detect, imgs)
File "C:\Anaconda3\lib\multiprocessing\pool.py", line 260, in map
return self._map_async(func, iterable, mapstar, chunksize).get()
File "C:\Anaconda3\lib\multiprocessing\pool.py", line 608, in get
raise self._value
File "C:\Anaconda3\lib\multiprocessing\pool.py", line 119, in worker
result = (True, func(*args, **kwds))
File "C:\Anaconda3\lib\multiprocessing\pool.py", line 44, in mapstar
return list(map(*args))
File "E:\git\opencv-dnn-demo\face_detectors\yolov2.py", line 34, in detect
detections = self.net.forward()
cv2.error: OpenCV(3.4.3) C:\projects\opencv-python\opencv\modules\dnn\src\dnn.cpp:841: error: (-215:Assertion failed) memHosts.find(lp) == memHosts.end() in function 'cv::dnn::experimental_dnn_34_v7::BlobManager::addHost'
What was the issue sorry I new to CV and Yolo
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Why the optical center stay unchanged when do stereRectify
I find that the stereo rectify algorithm always keep the optical center unchanged and just rotate the two cameras. Is it possible to translate the cameras during stereo rectification?
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How to make a shear algorithm using opencv and python no libraries
Hi i'm trying to make a shear algorithm in python without using libraries. I can use opencv to load and show image in greyscale.
if anyone can help with it, i would appreciate it
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