Issue with running See3Cam via pycharm - python

So the code works but when the screen pops up it's all black. Can't see any images. I thought my code wasn't picking up the camera but when i ran the external application for the camera (while the code was still running) it said the camera is being used somewhere else (assuming its PyCharm because when I stop the code it works on the external application).
I also tried running the cameras external application prior to running the code but when i do that the code gives me errors. I also tried running the code without the camera plugged in but gives me an error. So I'm assuming it picks up the camera but cant give me an output.
import cv2
print("done")
cap = cv2.VideoCapture(0)
if not(cap.isOpened()):
print("cant open")
cap.set(cv2.CAP_PROP_FRAME_WIDTH, 640)
cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 480)
while(True):
ret,frame=cap.read()
cv2.imshow('preview',frame)
if cv2.waitKey(1)& 0xFF==ord('d'):
break
cap.release()
cv2.destroyAllWindows()

So, it is possible that there is an error in your code, but I think, it's more likely that PyCharm has not got the permission to use your Camera. Try to open cmd(look in the search bar, it's preinstalled) and open it as Administrator. I'm sorry that I can't test it, but I don't have a webcam in my computer.

Related

opencv python camera permission issue on Windows 10

While running a simple opencv video capture script, i am getting False as the result. I suspect it is due to some security setting in Windows 10 which is not allowing camera access. I checked Privacy > Camera settings, but there was no option to allow a script to access the camera. I can see that the camera is not turned on when running the following opencv based test script.
import cv2
cap = cv2.VideoCapture(0)
while(True):
ret, frame = cap.read()
print(ret)
The Key to the answer is "Give time for Microsoft Windows to initalize WebCAM"
import time
capWebcam = cv2.VideoCapture(0)
time.sleep(1.000) # Make sure, you need to give time
# for MS Windows to initialize Camera
It's called "Allow access to classic application" or "Desktop applications" something like this in the bottom of the setting page, under Windows Store type applications.
This gain camera access to all EXE and DLL standalone applications.
One setting for all of them.
More info on exceptions here https://support.microsoft.com/en-us/help/4468234/windows-10-desktop-apps-and-privacy
Works for me in
'cv2.__version__ 4.2.0'
just installed latest opencv and python8 on latest windows10.
As suggested in previous helpful answers, after checking windows camera security setting, adding time delay, and running windows camera app, the program works fine.

BeagleBone Black OpenCV Python is too slow

I try to get images from webcam wtih opencv and python. Code is so basic like:
import cv2
import time
cap=cv2.VideoCapture(0)
cap.set(cv2.cv.CV_CAP_PROP_FRAME_WIDTH,640)
cap.set(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT,480)
cap.set(cv2.cv.CV_CAP_PROP_FPS, 20)
a=30
t=time.time()
while (a>0):
now=time.time()
print now-t
t=now
ret,frame=cap.read()
#Some processes
print a,ret
print frame.shape
a=a-1
k=cv2.waitKey(20)
if k==27:
break
cv2.destroyAllWindows()
But it works slowly. output of program:
VIDIOC_QUERYMENU: Invalid argument
VIDIOC_QUERYMENU: Invalid argument
VIDIOC_QUERYMENU: Invalid argument
VIDIOC_QUERYMENU: Invalid argument
VIDIOC_QUERYMENU: Invalid argument
VIDIOC_QUERYMENU: Invalid argument
HIGHGUI ERROR: V4L: Property <unknown property string>(5) not supported by device
8.82148742676e-06
select timeout
30 True
(480, 640, 3)
2.10035800934
select timeout
29 True
(480, 640, 3)
2.06729602814
select timeout
28 True
(480, 640, 3)
2.07144904137
select timeout
Configuration:
Beaglebone Black RevC
Debian-wheezly
opencv 2.4
python 2.7
The "secret" to obtaining higher FPS when processing video streams with OpenCV is to move the I/O (i.e., the reading of frames from the camera sensor) to a separate thread.
When calling read() method along with cv2.VideoCapture function, it makes the entire process very slow as it has to wait for each I/O operation to be completed for it to move on to the next one (Blocking Process).
In order to accomplish this FPS increase/latency decrease, our goal is to move the reading of frames from a webcam or USB device to an entirely different thread, totally separate from our main Python script.
This will allow frames to be read continuously from the I/O thread, all while our root thread processes the current frame. Once the root thread has finished processing its frame, it simply needs to grab the current frame from the I/O thread. This is accomplished without having to wait for blocking I/O operations.
You can read Increasing webcam FPS with Python and OpenCV to know the steps in implementing threads.
EDIT
Based on the discussions in our comments, I feel you could rewrite the code as follows:
import cv2
cv2.namedWindow("output")
cap = cv2.VideoCapture(0)
if cap.isOpened(): # Getting the first frame
ret, frame = cap.read()
else:
ret = False
while ret:
cv2.imshow("output", frame)
ret, frame = cap.read()
key = cv2.waitKey(20)
if key == 27: # exit on Escape key
break
cv2.destroyWindow("output")
I encountered a similar problem when I was working on a project using OpenCV 2.4.9 on the Intel Edison platform. Before doing any processing, it was taking roughly 80ms just to perform the frame grab. It turns out that OpenCV's camera capture logic for Linux doesn't seem to be implemented properly, at least in the 2.4.9 release. The underlying driver only uses one buffer, so it's not possible to use multi-threading in the application layer to work around it - until you attempt to grab the next frame, the only buffer in the V4L2 driver is locked.
The solution is to not use OpenCV's VideoCapture class. Maybe it was fixed to use a sensible number of buffers at some point, but as of 2.4.9, it wasn't. In fact, if you look at this article by the same author as the link provided by #Nickil Maveli, you'll find that as soon as he provides suggestions for improving the FPS on a Raspberry Pi, he stops using OpenCV's VideoCapture. I don't believe that is a coincidence.
Here's my post about it on the Intel Edison forum: https://communities.intel.com/thread/58544.
I basically wound up writing my own class to handle the frame grabs, directly using V4L2. That way you can provide a circular list of buffers and allow the frame grabbing and application logic to be properly decoupled. That was done in C++ though, for a C++ application. Assuming the above link delivers on its promises, that might be a far easier approach. I'm not sure whether it would work on BeagleBone, but maybe there's something similar to PiCamera out there. Good luck.
EDIT: I took a look at the source code for 2.4.11 of OpenCV. It looks like they now default to using 4 buffers, but you must be using V4L2 to take advantage of that. If you look closely at your error message HIGHGUI ERROR: V4L: Property..., you see that it references V4L, not V4L2. That means that the build of OpenCV you're using is falling back on the old V4L driver. In addition to the singular buffer causing performance issues, you're using an ancient driver that probably has many limitations and performance problems of its own.
Your best bet would be to build OpenCV yourself to make sure that it uses V4L2. If I recall correctly, the OpenCV configuration process checks whether the V4L2 drivers are installed on the machine and builds it accordingly, so you'll want to make sure that V4L2 and any related dev packages are installed on the machine you use to build OpenCV.
try this one ! I replaced some code in the cap.set() section
import cv2
import time
cap=cv2.VideoCapture(0)
cap.set(3,640)
cap.set(4,480)
cap.set(5, 20)
a=30
t=time.time()
while (a>0):
now=time.time()
print now-t
t=now
ret,frame=cap.read()
#Some processes
print a,ret
print frame.shape
a=a-1
k=cv2.waitKey(20)
if k==27:
break
cv2.destroyAllWindows()
output (pc webcam) your code was wrong for me.
>>0.0
>>30 True
>>(480, 640, 3)
>>0.246999979019
>>29 True
>>(480, 640, 3)
>>0.0249998569489
>>28 True
>>(480, 640, 3)
>>0.0280001163483
>>27 True
>>(480, 640, 3)
>>0.0320000648499

how to find the error, Program crash after executing quit sequence (Python, opencv, Ubuntu)

I'm trying to run a program that has been running before. After a while I switched the OS and came back to Ubuntu 14.10 (before it was 14.04). I'm not quite shure if the problem is within openCV or more of a basic thing. I can't find the problem. Maybe someone of you has an idea.
import cv2
cap = cv2.VideoCapture(0)
while(True):
# Capture frame-by-frame
ret, frame = cap.read()
# Display the resulting frame
cv2.imshow('frame',frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# When everything done, release the capture
cap.release()
cv2.destroyAllWindows()
It is running to the point that i can see a video capture.
But typing "q" to quit the program. The window that was opened freez, is turning black after a while and nothing else happens. Then I'l have to close the window and force it to exit.
Any idea what the problem is and how to solve?
Some buffers are perhaps used for drawing and so releasing their memory is a bad idea.
So could you try to call destroyAllWindows, before calling cap.release ?
Okay, found a workaround here on stackoverflow. Don't know why I didn't found it earlier.
Well it seems to be a problem within Linux.
DestroyWindow does not close window on Mac using Python and OpenCV
after
cv2.destroyAllWindow()
add
for i in range (1,5):
cv2.waitKey(1)
Don't ask me why but it works. If someone has an answere to this. Please let me know ;o)
Thanks to all who tried to help.

grab frame NTSCtoUSB dongle, opencv2, python wrapper

Context:
I have been playing around with python's wrapper for opencv2.
I wanted to play with a few ideas and use a wide angle camera similar to 'rear view' cameras in cars.
I got one from a scrapped crash car (its got 4 wires) I took an educated guess from the wires color codding, connect it up so that I power the power and ground line from a usb type A and feed the NTSC composite+ composite- from an RCA connector.
I bought a NTSC to usb converter like this one.
It came with drivers and some off the shelf VHStoDVD software.
the problem:
I used the run of the mill examples online to trial test it like this:
import numpy as np
import cv2
cam_index=0
cap=cv2.VideoCapture(cam_index)
print cap.isOpened()
ret, frame=cap.read()
#print frame.shape[0]
#print frame.shape[1]
while (cap.isOpened()):
ret, frame=cap.read()
#gray=cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
cv2.imshow('frame', frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
#release and close
cap.release()
cv2.destroyAllWindows()
this is the output from shell:
True
Traceback (most recent call last):
File "C:/../cam_capture_.py", line 19, in <module>
cv2.imshow('frame', frame)
error: ..\..\..\..\opencv\modules\highgui\src\window.cpp:261: error: (-215) size.width>0 && size.height>0 in function cv::imshow
>>>
key Observations:
SCREENSHOTS
in control panel the usb dongle is shown as 'OEM capture' in Sound Video & Game controllers . So it's not seen as a simple plug and play Webcam in 'Imaging devices'
If I open the VHStoDVD software I need to configure 2 aspects:
set as Composite
set enconding as NTSC
then the camera feed from the analog camera is shown OK within the VHStoDVD application
When I open the device video channel in FLV (device capture). The device stream is just a black screen but IF i open the VHStoDVD software WHILE flv is streaming I get the camera's feed to stream on FLV and a black screen is shown on the VHStoDVD feed. Another important difference is that there is huge latency of aprox 0.5sec when the feed is in FLV as opposed to running in VHStoDVD.
When running "cam_capture.py" as per the sample code above at some put during runtime i will eventually get a stop error code 0x0000008e:
detail:
stop: 0x0000008E (0xC0000005, 0xB8B5F417, 0X9DC979F4, 0X00000000 )
ks.sys - Address B8B5F417 base at B8B5900, Datestamp...
beg mem dump
phy mem dump complete
5.if i try to print frame.shape[0] or frame.shape[1] I get a type error say I cannot print type None
6.if try other cam_index the result is always false
TLDR:
In 'control panel' the camera device is under 'sound video & game controllers' not under 'imaging devices';
The cam_index==zero;
The capture.isOpened()=True;
The frame size is None;
If VHStoDVD is running with composite NTSC configured the camera works , obviously you cant see the image with printscreen in attachment but trust me ! ;)
Is there any form of initialisation of the start of communication with the dongle that could fix this i.e. emulate VHStoDVD settings (composite+NTSC)? I thought I could buspirate the start of comms between VHStoDVD and the dongle but it feels like I am going above and beyond to do something I thought was a key turn solution.
Any constructive insights, suggestion , corrections are most welcome!
Thanks
Cheers
Ok , so after deeper investigation the initial suspicion was confirmed i.e. because the NTSC dongle is not handled as an imaging device (it's seen as a Video Controller , so similar to an emulation of a TV Tuner card ) it means that although we are able to call cv2.VideoCapture with cam_index=0 the video channel itself is not transmitting because we are required to define a bunch of parameters
encoding
frame size
fps rate etc
The problem is because the device is not supported as an imaging device calling cv2.VideoCapture.set(parameter, value) doesn't seem to change anything on the original video feed.
I didn't find a solution but I found a work around. There seems to be quite a few options online. Search for keywords DV to webcam or camcorder as a webcam.
I used DVdriver (http://www.trackerpod.com/TCamWeb/download.htm) (i used the trial because I am cheap!).
Why does it work?
As much as I can tell DVdriver receives the data from the device which is set as a Video controller (similar to a capture from "Windows Movie Maker" or ffmpeg) and then through "fairydust" outputs the frames on cam_index=0 (assumed no other cam connected) as an 'imaging device' webcam.
Summary
TLDR use DVdriver or similar.
I found a workaround but I would really like to understand it from first principles and possible generate a similar initialisation of the NTSC dongle from within python, without any other software dependencies but until then, hopefully this will help others who were also struggling or assuming it was a hardware issue.
I will now leave you with some Beckett:
Ever tried. Ever failed. No matter. Try again. Fail again. Fail better. (!)
It's a few months late, but might be useful. I was working on a Windows computer and had installed the drivers that came with the device, I tried the same code as your question with an Ezcap from Somagic and got the same error. Since "frame is None," I decided to try an if statement around it - in case it was an initialization error. Placing into the loop:
if frame is None:
print 0
else:
print 1
The result is: 01110111111111111111111111111...
And if the frame = cap.read(), above the loop is commented out - I get: 00111111111111111...
So for my device capture device it appears to be working for all frames beyond the 5th are captured. I'm not sure why this is, but it might be a useful work around for now.
Disclaimer: Unfortunately, my camera input is currently in a radiation field so I can't get to it for a couple of weeks to make sure it works for sure. However, the images are currently a black frame (which is expected without proper input).
I faced the same issue. As a workaround, I first tried the solution proposed by #user3380927 and it worked indeed. But since I didn't want to rely on an external software, I started tweaking parameters using opencv in Python.
This lines of code worked like a charm (you have to insert them before reading the frame for the first time):
cam.set(cv2.CAP_FFMPEG,True)
cam.set(cv2.CAP_PROP_FPS,30)
So, the full code for basic camera reading is as follows:
import cv2
cam = cv2.VideoCapture(1)
cam.set(cv2.CAP_FFMPEG,True)
cam.set(cv2.CAP_PROP_FPS,30)
while(True):
ret,frame = cam.read()
cv2.imshow('frame',frame)
if (cv2.waitKey(1) & 0xFF == ord('q')):
break
cam.release()
cv2.destroyAllWindows()
You can then apply image processing operations as usual. Just for reference, this was my configuration:
Opencv 3.1.0
Python 2.7.5
Windows 8.1
Elgato Video Capture device (this was also shown as Sound Video & Game controllers)

How to stop SimpleCV camera stream?

I'm trying to learn SimpleCV using Python 2.7 in IDLE.
Once the camera form SimpleCV is initialized the camera become unavailable to other programs like native webcam application or skype etc.
from SimpleCV import *
camera = Camera()
After restarting the pc or logoff and logon the webcam becomes to those applications. It seems that even closing out from python IDLE, it doesn't close the camera stream. Is there any way to stop the camera stream of simplecv?
I couldn't replicate your issue, but if the webcam is still running even after your program terminates/you close IDLE, you can end the camera by going into task manager and killing all running Python processes.
After some experimenting, I found that if you want to accomplish the same thing directly inside the code, you could try simply deleting the reference altogether:
>>> import SimpleCV as scv
>>> cam = scv.Camera()
>>> del cam
Calling del cam caused the webcam indicator light on my laptop to turn off. Granted, this appears to be an undocumented (??) solution, so I'm not sure how robust it is. I would probably try testing this on several different laptops/webcams first, to make sure it works reliably and consistently.

Categories