Im trying to get opencv working for a face recognition program. My webcam is working since I tested it using cv2.VideoCapture and the window popped up, then when i added the next step which is turning the image gray using cv2.cvtcolor(frame, cv2.COLOR_BGR2GRAY) I got the error message saying AttributeError: module 'cv2.cv2' has no attribute 'cvtcolor. I tried uninstalling and reinstalling opencv using pip3 install opencv-contrib-python. Im not sure what im doing wrong here, my guess is maybe my files arnt in the write place but im not sure where they would need to be
When I use this code my window of my webcam pops up and works fine.
Working code
import os
import PIL
import cv2
import numpy
face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades +
"haarcascade_frontalface_alt2.xml")
cap = cv2.VideoCapture(0)
while(True):
#frame by frame
ret, frame = cap.read()
gray = cv2.cvtcolor(frame, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiscale(gray, scaleFactor=1.5,
minNeighbors=5)
#display frame
cv2.imshow('frame',frame)
if cv2.waitKey(20) & 0xFF == ord('q'):
break
#when done relase cap
cap.release()
cv2.destroyAllWindows()
Traceback (most recent call last):
File "c:/Users/Nick Miller/all_for_vs/Code/facerecg.py", line 14, in
gray = cv2.cvtcolor(frame, cv2.COLOR_BGR2GRAY)
AttributeError: module 'cv2.cv2' has no attribute 'cvtcolor'
[ WARN:0] terminating async callback
Change
cv2.cvtcolor(frame, cv2.COLOR_BGR2GRAY) to cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY).
Also, change faces = face_cascade.detectMultiscale(gray,scaleFactor=1.5,minNeighbors=5) to faces = face_cascade.detectMultiScale(gray,scaleFactor=1.5,minNeighbors=5)
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 followed a tutorial line by line on YouTube, and it worked. As this is my first time doing recognition stuff
I haven't changed anything and now it's giving me an error.
import cv2
url = 'http//192.168.1.88:4747/video'
cap = cv2.VideoCapture(url)
face_cascade = cv2.CascadeClassifier("Lib\\site-packages\\cv2\\data\\haarcascade_frontalface_alt2.xml")
while True:
ret, frame = cap.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) # <----------THIS LINE IS GIVING ME THE ERROR
face = face_cascade.detectMultiScale(gray, 1.5, 5)
for(x,y,w,h) in faces:
print(x,y,w,h)
cv2.rectangle(gray, (x,y), (x+w, y+h), (255,0,0), 5)
cv2.imshow('Window', frame)
if cv2.waitKey(1) & 0xff == ord('q'):
break
cv2.destroyAllWindows()
I've tried deleting the whole code-block and rewriting it but I still get the error. Its like that saying, only an idiot does the same thing over and over expecting a different result.
Here is the error:
Traceback (most recent call last):
File "C:/Users/Tomas/PycharmProjects/Webcam Phone/venv/Webcam.py", line 9, in <module>
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
cv2.error: OpenCV(4.3.0) C:\projects\opencv-python\opencv\modules\imgproc\src\color.cpp:182: error: (-215:Assertion failed) !_src.empty() in function 'cv::cvtColor'
You're seeing what happens when None gets passed to cvtColor()
You need either test ret, or frame is not None. If you're using a laptop webcam, it's not uncommon in my experience that it take a few frames for the camera to 'warm up' and return images.
CREDIT TO - mkrieger & fmw42 - their comments helped my work out why is was returning nothing.
Missing : in the URL
Caused the cap = cv2.VideoCapture(url) function to not receive any frames from the webcam, so ret, frame = cap.read() just returned False and None
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.
import numpy as np
import cv2
cap = cv2.VideoCapture(0)
while(True):
# Capture frame-by-frame
ret, frame = cap.read()
# Our operations on the frame come here
gray = cv2.cvtColor('frame', cv2.COLOR_BGR2GRAY)
# Display the resulting frame
cv2.imshow('frame',frame)
cv2.imshow('gray',gray)
if cv2.waitKey(20) & 0xFF == ord('q'):
break
# When everything done, release the capture
cap.release()
cv2.destroyAllWindows()`
Traceback (most recent call last):
File "C:\Users\Kouissi\Desktop\camera-test\camera_test.py", line 11, in <module>
gray = cv2.cvtColor('frame', cv2.COLOR_BGR2GRAY)
TypeError: Expected cv::UMat for argument 'src'
You need to change:
gray = cv2.cvtColor('frame', cv2.COLOR_BGR2GRAY)
to:
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
In this case the frame variable is a numpy array.
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.