I have a keras model on depth perception, I want to load it using tensorflowjs, and apply it frame by frame on my webcam stream. Currently I am unable to capture my webcam video stream using HTML. How to do it?
you can use opencv and python to easily capture your video and make changes on it. for example you can use following code:
import cv2
import sys
from time import sleep
video_capture = cv2.VideoCapture(0)
anterior = 0
while True:
if not video_capture.isOpened():
print('Unable to load camera.')
sleep(5)
pass
# Capture frame-by-frame
ret, frame = video_capture.read()
# Display the resulting frameA
cv2.imshow('Video', frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# Display the resulting frame
cv2.imshow('Video', frame)
# When everything is done, release the capture
video_capture.release()
cv2.destroyAllWindows()
Related
I'm trying to use a .pt model to detect an object via webcam. When I execute this code:
# Importamos librerias
import torch
import cv2
import numpy as np
import pandas
# Leemos el modelo
model = torch.hub.load('ultralytics/yolov5', 'custom',
path = 'C:/Users/maxim/OneDrive/Documentos/jupyterbooks/detector.pt')
# Realizo Videocaptura
cap = cv2.VideoCapture(1)
# Empezamos
while True:
# Realizamos lectura de frames
ret, frame = cap.read()
# Correccion de color
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
# Realizamos las detecciones
detect = model(frame)
# Mostramos FPS
cv2.imshow('Detector de Figuras', np.squeeze(detect.render()))
# Leemos el teclado
t = cv2.waitKey(5)
if t == 27:
break`
cap.release()
cv2.destroyAllWindows()
It's giving me this error:
error: OpenCV(4.7.0) D:\a\opencv-python\opencv-python\opencv\modules\imgproc\src\color.cpp:182: error: (-215:Assertion failed) !_src.empty() in function 'cv::cvtColor'
I'm new into this so I really don't know why is giving me this type of error.
best regards,
maximiliano
I'm expecting to solve this error so I can test my model in my webcam.
Most probably, your frame is empty. That means the webcam did not load properly. You may check something like print(frame.shape) just after cap.read() and see what it prints. If it is not empty, it will print the webcam frame size. Make sure your webcam is in location 1 as you specified. If you have only one webcam, it should be 0.
I am creating a python program to record my desktop screen.
But the output of this code is in very low quality and blurry.
Can anyone help me in capturing (screen capturing) in high quality.
Like the screen recorder like OBS studio and Camtasia do.
what can i do improve my quality change my extention ,codec ,etc. please mention.
import cv2
import numpy as np
import datetime
from PIL import Image, ImageTk, ImageGrab
date = datetime.datetime.now()
filename='rec_%s-%s-%s-%s%s%s.mp4' % (date.year, date.month, date.day,
date.hour, date.minute, date.second)
fourcc = cv2.VideoWriter_fourcc(*'X264')
frame_rate = 16
SCREEN_SIZE = (960,540)
out = cv2.VideoWriter(filename, fourcc,framerate, SCREEN_SIZE)
while True:
img = ImageGrab.grab()
frame = np.array(img)
frame = cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)
out.write(frame)
cv2.imshow('screenshot', frame)
if cv2.waitKey(1) == ord("q"):
break
cv2.destroyAllWindows()
out.release()
frame_rate = 16
SCREEN_SIZE = (960,540)
Both of this are too low, you probably want your frame_rate to be 30, and your screen size to be 1920x1080p.
Also just has an extra info:
.mp4 is a bad format for screen recording, I know OBS recommended using .flv because it doesn't corrupt the whole file if the recording end abruptly, unlike .mp4.
I'm creating a script that will read the state of a supermarket and tell me if there is products missing.
for example in the image below there is some places where there is products missing. I'm using FAST method to find all the corners in the frame. but sometimes the scripts detects the floor corners. What I want to do is remove the floor from the frame before I find the corners.
import cv2
import numpy as np
image = cv2.imread('gondola_imagem.jpeg')
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
fast = cv2.FastFeatureDetector_create()
# Obtain Key points, by default non max suppression is On
# to turn off set fast.setBool('nonmaxSuppression', False)
keypoints = fast.detect(gray, None)
print ("Number of keypoints Detected: ", len(keypoints))
image = cv2.drawKeypoints(image, keypoints, None,
flags=cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS)
cv2.imshow('Feature Method - FAST', image)
cv2.waitKey()
cv2.destroyAllWindows()
You can use a mask to remove the areas you are not interested. For example with the following image as a mask you can get the bellow results.
Mask
Result
Code is as follow:
import numpy as np
import cv2
image = cv2.imread('test.jpg')
mask = cv2.imread('mask.jpg', 0)
cv2.imshow('Original', image)
cv2.imshow('Mask', mask)
res = cv2.bitwise_and(image,image,mask = mask)
gray = cv2.cvtColor(res, cv2.COLOR_BGR2GRAY)
fast = cv2.FastFeatureDetector_create()
# Obtain Key points, by default non max suppression is On
# to turn off set fast.setBool('nonmaxSuppression', False)
keypoints = fast.detect(gray, None)
print ("Number of keypoints Detected: ", len(keypoints))
image = cv2.drawKeypoints(image, keypoints, None,
flags=cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS)
cv2.imwrite('result.jpg', image)
cv2.imshow('Feature Method - FAST', image)
cv2.waitKey()
cv2.destroyAllWindows()
Edit:
If you want to do this in realtime (video from webcam) you just need to do it for every frame you get from the video camera. As long as the camera is not moving you should be able to use the same mask for all the frames. You could make the code above a function and then call it with an image as a parameter, as per the following code:
import numpy as np
import cv2
cap = cv2.VideoCapture(0)
while(True):
# Capture frame-by-frame
ret, frame = cap.read()
# Following function will have to be created with the previews code
CallFunctionToPreviewsCode(frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
# When everything done, release the capture
cap.release()
cv2.destroyAllWindows()
The code above was taken from OpenCV Python-Tutorials It is a good place for learning OpenCV for Python programming language.
I want to close web cam i used the cap.released() but it does not close the web cam after it captures the image. Here is my code:
import cv2
import matplotlib.pyplot as plt
def main():
cap=cv2.VideoCapture(0)
if cap.isOpened():
ret, frame = cap.read()
print(ret)
print(frame)
else:
ret=False
img1= cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
plt.imshow(img1)
plt.title('Color Image RGB')
plt.xticks([])
plt.yticks([])
plt.show()
cap.release()
if __name__=='__main__':
main()
The cam will stay active until you close the figure, i.e. until the script finishes. This is because you only release the capture afterwards,
plt.show()
cap.release()
If you want to turn off the camera after taking the image, reverse this order
cap.release()
plt.show()
Was using opencv to capture a preexisting video. The video pops up on a frame
buts ends in the following error:
cv2.error: D:\Build\OpenCV\opencv-3.2.0\modules\highgui\src\window.cpp:312: error: (-215) size.width>0 && size.height>0 in function cv::imshow
My code is
import numpy as np
import cv2
cap = cv2.VideoCapture('lol.avi')
while(cap.isOpened()):
ret, frame = cap.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
cv2.imshow('frame',gray)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
PS: I do have ffmpeg in windows and environment path set to it.