def camera(transform):
capture = cv2.VideoCapture(0)
while True:
ret, frame = capture.read()
cv2.imshow('video', frame)
# esc
if cv2.waitKey(1) == 27:
photo = frame
break
capture.release()
cv2.destroyAllWindows()
img = Image.fromarray(cv2.cvtColor(photo, cv2.COLOR_BGR2RGB))
img = img.resize([224, 224], Image.LANCZOS)
if transform is not None:
img = transform(img).unsqueeze(0)
return img
This is my code to get image from the camera,
image_tensor = img.to(device)
And I have an error at the line above...
Traceback (most recent call last):
File "E:/PycharmProjects/ArsElectronica/image_captioning/sample.py", line 126, in <module>
main(args)
File "E:/PycharmProjects/ArsElectronica/image_captioning/sample.py", line 110, in main
caption = Image_Captioning(args, img)
File "E:/PycharmProjects/ArsElectronica/image_captioning/sample.py", line 88, in Image_Captioning
image_tensor = img.to(device)
AttributeError: 'Image' object has no attribute 'to'
The error is like this.
If I have the image as png file and reload it with PIL, it works.
But the one I want is to use the image without saving.
Pls... Someone save me...
You could convert your PIL.Image to torch.Tensor with torchvision.transforms.ToTensor:
if transform is not None:
img = transform(img).unsqueeze(0)
tensor = T.ToTensor()(img)
return tensor
having imported torchvision.transforms as T
Related
i am getting a (-215:Assertion failed) !_src.empty() in function 'cv::cvtColor' while making a face detection using openCv. Here is my code:
import cv2
import numpy as np
# Load HAAR face classifier
face_classifier = cv2.CascadeClassifier('Haarcascades/haarcascade_frontalface_default.xml')
# Load functions
def face_extractor(img):
# Function detects faces and returns the cropped face
# If no face detected, it returns the input image
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
faces = face_classifier.detectMultiScale(gray, 1.3, 5)
if faces is ():
return None
# Crop all faces found
for (x,y,w,h) in faces:
cropped_face = img[y:y+h, x:x+w]
return cropped_face
# Initialize Webcam
cap = cv2.VideoCapture(0)
count = 0
# Collect 100 samples of your face from webcam input
while True:
ret, frame = cap.read()
if face_extractor(frame) is not None:
count += 1
face = cv2.resize(face_extractor(frame), (200, 200))
face = cv2.cvtColor(face, cv2.COLOR_BGR2GRAY)
# Save file in specified directory with unique name
file_name_path = './faces/user/' + str(count) + '.jpg'
cv2.imwrite(file_name_path, face)
# Put count on images and display live count
cv2.putText(face, str(count), (50, 50), cv2.FONT_HERSHEY_COMPLEX, 1, (0,255,0), 2)
cv2.imshow('Face Cropper', face)
else:
print("Face not found")
pass
if cv2.waitKey(1) == 13 or count == 100: #13 is the Enter Key
break
cap.release()
cv2.destroyAllWindows()
print("Collecting Samples Complete")
and here is the output which is an error
error: OpenCV(4.2.0) C:\projects\opencv-python\opencv\modules\imgproc\src\color.cpp:182: error: (-215:Assertion failed) !_src.empty() in function 'cv::cvtColor'
I tried converting / to \ but that resulted in another SyntaxError: EOL while scanning string literal.
Please help me solving this issue i have also tr
You need to specify the path to your haarcascade_frontalface_default.xml file.
Put double \ in your path as i did
I modified your code and hope it helps
`#importing library
import cv2
import numpy as np
# Load HAAR face classifier
face_classifier =
cv2.CascadeClassifier
('D:\\OpenCV\\opencv\\build\\etc\\Haarcascades\\haarcascade_frontalface_default.xml')
# crop the image into 20 by 20 px and change it to B&W
def face_extractor(img):
# Function detects faces and returns the cropped face
# If no face detected, it returns the input image
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
faces = face_classifier.detectMultiScale(gray, 1.3, 5)
if faces is ():
return None
# Crop all faces found
for (x,y,w,h) in faces:
cropped_face = img[y:y+h, x:x+w]
return cropped_face
#Asks for the total number of users
num=int(input("Enter no of user you want to add "))
user=1
# Initialize Webcam
cap = cv2.VideoCapture(0)
#count the total number of faces
count = 0
print("Start Capturing the input Data Set ")
d=input('Enter Face name')
# Collect 100 samples of your face from webcam input
while True:
ret, frame = cap.read()
print(type(frame))
#condition to check if face is in the frame or not
if face_extractor(frame) is not None:
count += 1
face = cv2.resize(face_extractor(frame), (200, 200))
face = cv2.cvtColor(face, cv2.COLOR_BGR2GRAY)
# Save file in specified directory with unique name
file_name_path = './faces/user/' +str(d)+'-' +str(count) + '.jpg'
cv2.imwrite(file_name_path, face)
# Put count on images and display live count
cv2.putText(face, str(count), (50, 50), cv2.FONT_HERSHEY_COMPLEX, 1, (0,255,0), 2)
cv2.imshow('Face Cropper', face)
else:
print("Face not found")
pass
#checks if ech user 100 images is captured
if(count%100)==0 and count!= num*100 and count!=0:
print("Place the new user Signature")
cv2.waitKey()
#checks if total images are captured
if cv2.waitKey(1) == 13 or count == num*100: #13 is the Enter Key
break
#closes all windows
cap.release()
cv2.destroyAllWindows()
print("Collecting Samples Complete")`
I am able to process the video frames by saing the frame as an image and then processing it. But was unable to pass frame directly to the object detection.
Saving image with imwrite is making program slow...
Here is my main method:
cap = cv2.VideoCapture(gstreamer_pipeline(flip_method=2), cv2.CAP_GSTREAMER)
if cap.isOpened():
window_handle = cv2.namedWindow("CSI Camera", cv2.WINDOW_AUTOSIZE)
# Window
while cv2.getWindowProperty("CSI Camera", 0) >= 0:
ret_val, frame = cap.read()
if not ret_val:
break
frame = imutils.resize(frame, width=600)
#cv2.imwrite('box.jpg', frame)
#image = Image.open(path)
#Error in here!!!
predictions = od_model.predict_image(frame)
for x in range(len(predictions)):
probab = (predictions[x]['probability'])*100
if(probab > 45):
print(predictions[x]['tagName'], end=' ')
print(probab)
#cv2.imshow("CSI Camera", frame)
# This also acts as
keyCode = cv2.waitKey(30) & 0xFF
# Stop the program on the ESC key
if keyCode == 27:
break
cap.release()
cv2.destroyAllWindows()
else:
print("Unable to open camera")
Error Message:
predictions = od_model.predict_image(frame)
File "/home/bharat/New_IT3/object_detection.py", line 125, in
predict_image
inputs = self.preprocess(image)
File "/home/bharat/New_IT3/object_detection.py", line 130, in
preprocess
image = image.convert("RGB") if image.mode != "RGB" else image
AttributeError: 'numpy.ndarray' object has no attribute 'mode'
open cv reads image in bgr colour spectrum conver it to rgb and send the image for detection, api for the same is -
frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
i am just learning image processing but cvtColor function is not working properly. it is showing following error.
OpenCV Error: Assertion failed (scn == 3 || scn == 4) in cvtColor, file /build/opencv-SviWsf/opencv-2.4.9.1+dfsg/modules/imgproc/src/color.cpp, line 3737
Traceback (most recent call last):
File "harriscorner.py", line 6, in <module>
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
cv2.error: /build/opencv-SviWsf/opencv-2.4.9.1+dfsg/modules/imgproc/src/color.cpp:3737: error: (-215) scn == 3 || scn == 4 in function cvtColor
actually i am trying harris corner detection method but cvtColor fucion is not working. help from anyone will be appreciated.
here is my code.
import cv2
import numpy as np
filename = 'chessboard.jpg'
img = cv2.imread(filename)
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
gray = np.float32(gray)
dst = cv2.cornerHarris(gray,2,3,0.04)
#result is dilated for marking the corners, not important
dst = cv2.dilate(dst,None)
# Threshold for an optimal value, it may vary depending on the image.
img[dst>0.01*dst.max()]=[0,0,255]
cv2.imshow('dst',img)
if cv2.waitKey(0) & 0xff == 27:
cv2.destroyAllWindows()
Since your code is showing error at the very first cvtColor after reading from a file, it is possible that the imread operation was not successful.
Start by ensuring that your image is correctly read:
filename = 'chessboard.jpg'
img = cv2.imread(filename)
cv2.imshow("src",img)
cv2.waitKey(0)#proceed to remaining code when you press a key
gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
If you're not able to see you image in this imshow, then check if the filePath is correct.
Try this:
filename = './chessboard.jpg'
Please help me to rectify the errors. This is an Opencv feature extraction code.
from __future__ import division
import numpy as np
import cv2
ESC=27
camera = cv2.VideoCapture(0)
orb = cv2.ORB()
bf = cv2.BFMatcher(cv2.NORM_HAMMING, crossCheck=True)
imgTrainColor=cv2.imread('train.jpg')
imgTrainGray = cv2.cvtColor(imgTrainColor, cv2.COLOR_BGR2GRAY)
kpTrain = orb.detect(imgTrainGray,None)
kpTrain, desTrain = orb.compute(imgTrainGray, kpTrain)
firsttime=True
while True:
ret, imgCamColor = camera.read()
imgCamGray = cv2.cvtColor(imgCamColor, cv2.COLOR_BGR2GRAY)
kpCam = orb.detect(imgCamGray,None)
kpCam, desCam = orb.compute(imgCamGray, kpCam)
matches = bf.match(desCam,desTrain)
dist = [m.distance for m in matches]
thres_dist = (sum(dist) / len(dist)) * 0.5
matches = [m for m in matches if m.distance < thres_dist]
if firsttime==True:
h1, w1 = imgCamColor.shape[:2]
h2, w2 = imgTrainColor.shape[:2]
nWidth = w1+w2
nHeight = max(h1, h2)
hdif = (h1-h2)/2
firsttime=False
result = np.zeros((nHeight, nWidth, 3), np.uint8)
result[hdif:hdif+h2, :w2] = imgTrainColor
result[:h1, w2:w1+w2] = imgCamColor
for i in range(len(matches)):
pt_a=(int(kpTrain[matches[i].trainIdx].pt[0]), int(kpTrain[matches[i].trainIdx].pt[1]+hdif))
pt_b=(int(kpCam[matches[i].queryIdx].pt[0]+w2), int(kpCam[matches[i].queryIdx].pt[1]))
cv2.line(result, pt_a, pt_b, (255, 0, 0))
cv2.imshow('Camara', result)
key = cv2.waitKey(30)
if key == ESC:
break
cv2.destroyAllWindows()
camera.release()
ERRORS APPEARING:
Traceback (most recent call last):
File "sift.py", line 39, in
result[hdif:hdif+h2, :w2] = imgTrainColor
ValueError: could not broadcast input array from shape (700,227,3) into shape (0,227,3)
Without digging through your code in detail
result[hdif:hdif+h2, :w2] = imgTrainColor
... from shape (700,227,3) into shape (0,227,3)
I duduce that imgTrainColor is 3d with shape (700,227,3).
result must has (3,) last dimension; the :w2 must be slicing 227 vales. But the hdif:hdif+h2 is slicing 0, probably because h2 is 0.
In other words, you are trying to put the imgTrainColor values into a block of result that is too small.
Can I leave to you to figure out why h2 is wrong? Another possibility is the hdif is too large (>700). You may need to print those indexing values just before this error.
Oh, and clean up the indentation.
I'm trying to make run a face recognition program using OpenCV and Python.
I found this code here on stackoverflow, but the main problem is an error which says:
Traceback (most recent call last):
File "/Users/n1/Desktop/FaceDetection/face.py", line 8, in <module>
gray = imread(fname, CV_LOAD_IMAGE_GRAYSCALE )
NameError: name 'CV_LOAD_IMAGE_GRAYSCALE' is not defined
The code is this one :
from cv2 import *
import numpy as np
face_cascade = CascadeClassifier('haarcascade_frontalface_default.xml')
eye_cascade = CascadeClassifier('haarcascade_eye.xml')
fname='123.jpg'
img = imread(fname)
gray = imread(fname, CV_LOAD_IMAGE_GRAYSCALE ( 0) )
rows,cols = gray.shape
gray = np.array(gray, dtype='uint8')
faces = face_cascade.detectMultiScale(gray, 1.3, 5, 0)
print ('faces=', faces)
for (x,y,w,h) in faces:
rectangle(img, (x,y), ((x+w),(x+h)), (255,0,0), 2)
roi_gray = gray[y:y+h, x:x+w]
roi_color = img[y:y+h, x:x+w]
eyes = eye_cascade.detectMultiScale(roi_gray)
for (ex,ey, ew, eh) in eyes:
rectangle(roi_color, (x,y), ((x+w), (y+h)), (50, 50, 50), 3)
imshow('eyes=%s' % (eyes,), roi_color)
imshow("img", img)
waitKey(0)
destroyAllWindows()
>>> import cv2
>>> help(cv2)
...
IMREAD_ANYCOLOR = 4
IMREAD_ANYDEPTH = 2
IMREAD_COLOR = 1
IMREAD_GRAYSCALE = 0 #that will be it ;)
IMREAD_LOAD_GDAL = 8
IMREAD_UNCHANGED = -1
...
VERSION
3.0.0-dev
( CV_LOAD_IMAGE_GRAYSCALE is from the outdated [and now removed] cv api )
In OpenCV 3.1 for C++ you have to use cv::ImreadModes::IMREAD_GRAYSCALE which is located on <opencv2/imgcodecs.hpp>
simpy change: "CV_LOAD_IMAGE_GRAYSCALE"
to: "IMREAD_GRAYSCALE"
it will work.