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How to fix IndexError: invalid index to scalar variable
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Closed 2 months ago.
Im getting an error every time i run this script in my environment
Traceback (most recent call last):
File "FaceMark.py", line 55, in <module>
i = i[0]
IndexError: invalid index to scalar variable.
The camera does turns on but as soon it detects my hand or face the camera windows shuts down and it throws me the error posted above.
here's the entire script:
import cv2
import mediapipe as mp
import time
import numpy as np
thres = 0.45 # Threshold to detect object
nms_threshold = 0.2`your text`
cap = cv2.VideoCapture()
cap.set(3, 1280)
cap.set(4, 720)
cap.set(10, 150)
classNames = []
classFile = 'coco.names'
with open(classFile, 'rt') as f:
classNames = f.read().rstrip('\n').split('\n')
configPath = 'ssd_mobilenet_v3_large_coco_2020_01_14.pbtxt'
weightsPath = 'frozen_inference_graph.pb'
net = cv2.dnn_DetectionModel(weightsPath, configPath)
net.setInputSize(320, 320)
net.setInputScale(1.0 / 127.5)
net.setInputMean((127.5, 127.5, 127.5))
net.setInputSwapRB(True)
cap = cv2.VideoCapture(0)
pTime = 0
cTime = 0
mpDraw = mp.solutions.drawing_utils
mpFaceMesh = mp.solutions.face_mesh
faceMesh = mpFaceMesh.FaceMesh(max_num_faces=2)
drawSpec = mpDraw.DrawingSpec(thickness=1, circle_radius=2)
mpHands = mp.solutions.hands
hands = mpHands.Hands()
mpDrawHand = mp.solutions.drawing_utils
while True:
success, img = cap.read()
imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
classIds, confs, bbox = net.detect(img, confThreshold=thres)
bbox = list(bbox)
confs = list(np.array(confs).reshape(1, -1)[0])
confs = list(map(float, confs))
indices = cv2.dnn.NMSBoxes(bbox, confs, thres, nms_threshold)
results = faceMesh.process(imgRGB)
resultsHand = hands.process(imgRGB)
for i in indices:
i = i[0]
box = bbox[i]
# colors = np.random.uniform(0, 255, size=(len(box), 3))
x, y, w, h = box[0], box[1], box[2], box[3]
cv2.rectangle(img, (x, y), (x + w, h + y), color=(0, 255, 0), thickness=2)
cv2.putText(img, classNames[classIds[i][0] - 1].upper(), (box[0] + 10, box[1] + 30),
cv2.FONT_HERSHEY_PLAIN, 1, (0, 255, 0), 2)
print("Objects Ids: ", classIds)
if resultsHand.multi_hand_landmarks:
for handLms in resultsHand.multi_hand_landmarks:
for id, lm in enumerate(handLms.landmark):
print(id, lm)
h, w, c = img.shape
cx, cy = int(lm.x * w), int(lm.y * h)
cv2.circle(img, (cx, cy), 5, (255, 0, 255), cv2.FILLED)
mpDrawHand.draw_landmarks(img, handLms, mpHands.HAND_CONNECTIONS)
if results.multi_face_landmarks:
for faceLms in results.multi_face_landmarks:
mpDraw.draw_landmarks(img, faceLms, mpFaceMesh.FACE_CONNECTIONS,
drawSpec, drawSpec)
for id, lm in enumerate(faceLms.landmark):`
# print(lm)
ih, iw, ic = img.shape
x, y = int(lm.x * iw), int(lm.y * ih)
print("Face id: ", id, x, y)
cTime = time.time()
fps = 1 / (cTime - pTime)
pTime = cTime
cv2.putText(img, f'FPS: {int(fps)}', (20, 70), cv2.FONT_HERSHEY_PLAIN,
3, (255, 0, 0), 3)
cv2.imshow('image', img)
key = cv2.waitKey(1)
if key == 27:
break
cap.release()
cv2.destroyAllWindows()
how can i solve the problem around the indexes loop? i have tried other solutions here in similar questions, but i havent had any luck.
The variable i returns an integer value. This is not a list or tuple. If you change the for loop as follows, it will likely work.
for i in indices:
box = bbox[i]
# colors = np.random.uniform(0, 255, size=(len(box), 3))
x, y, w, h = box[0], box[1], box[2], box[3]
cv2.rectangle(img, (x, y), (x + w, h + y), color=(0, 255, 0), thickness=2)
cv2.putText(img, classNames[classIds[i] - 1].upper(), (box[0] + 10, box[1] + 30),
cv2.FONT_HERSHEY_PLAIN, 1, (0, 255, 0), 2)
print("Objects Ids: ", classIds)
I'm using
OS : Ubuntu
Python : 3.8*
Opencv version: 4.6.0
What I'm trying to do is capture the emotion & save the feed..For that I've used opencv 4.0
Code I've
while True:
ret, frame = cap.read()
frame = cv2.resize(frame, (720, 480))
if not ret:
break
grayFrame = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
rects = detector(grayFrame, 0)
for rect in rects:
shape = predictor(grayFrame, rect)
points = shapePoints(shape)
(x, y, w, h) = rectPoints(rect)
grayFace = grayFrame[y:y + h, x:x + w]
try:
grayFace = cv2.resize(grayFace, (emotionTargetSize))
except:
continue
grayFace = grayFace.astype('float32')
grayFace = grayFace / 255.0
grayFace = (grayFace - 0.5) * 2.0
grayFace = np.expand_dims(grayFace, 0)
grayFace = np.expand_dims(grayFace, -1)
emotion_prediction = emotionClassifier.predict(grayFace)
emotion_probability = np.max(emotion_prediction)
if (emotion_probability > 0.36):
emotion_label_arg = np.argmax(emotion_prediction)
color = emotions[emotion_label_arg]['color']
cv2.rectangle(frame, (x, y), (x + w, y + h), color, 2)
cv2.line(frame, (x, y + h), (x + 20, y + h + 20),
color,
thickness=2)
cv2.rectangle(frame, (x + 20, y + h + 20), (x + 110, y + h + 40),
color, -1)
cv2.putText(frame, emotions[emotion_label_arg]['emotion'],
(x + 25, y + h + 36), cv2.FONT_HERSHEY_SIMPLEX, 0.5,
(255, 255, 255), 1, cv2.LINE_AA)
else:
color = (255, 255, 255)
cv2.rectangle(frame, (x, y), (x + w, y + h), color, 2)
out.write(frame)
#Wait for user input - q, then you will stop the loop
k = cv2.waitKey(1)
if k == 27:
break
cap.release()
if args["isVideoWriter"] == True:
videoWrite.release()
cv2.destroyAllWindows()
Here Issue with wait key ...when I hit on esc program is not exiting...I've tried all the possible methods...the only method that working is keyboard interruption i.e, ctrl+c
Method1: Not working :(
c = cv2.waitKey(0) % 256
if c == ord('a'):
break
Method 2: Not working :(
if cv2.waitKey(0) & 0xFF == ord('q'):
break
Did i missing anything?...Thanks in advance
I have three IP cameras around my house and I want to capture an image when a motion is detected. I want to run the motion capture algorithm in the same time for all 3 cameras.
I manage to do the job for one camera - Open the stream + motion detection algorithm + store image in case of detection :
import cv2
cap3 = cv2.VideoCapture('http://X.X.X.X:XXXX/stream.mjpg')
ret3, frame31 = cap3.read()
ret3, frame32 = cap3.read()
while (True):
diff3 = cv2.absdiff(frame31, frame32)
gray3 = cv2.cvtColor(diff3, cv2.COLOR_BGR2GRAY)
blur3 = cv2.GaussianBlur(gray3, (5, 5), 0)
_, tresh3 = cv2.threshold(blur3, 30, 255, cv2.THRESH_BINARY)
dilated3 = cv2.dilate(tresh3, None, iterations=3)
contours3, _ = cv2.findContours(dilated3, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
for contour in contours3:
(x, y, w, h) = cv2.boundingRect(contour)
if cv2.contourArea(contour) < 800:
continue
cv2.rectangle(frame31, (x, y), (x + w, y + h), (0, 255, 0), 2)
cv2.putText(frame31, "Status: {}".format('Movement'), (10, 20), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 3)
t = time.localtime()
filename = "RASP" + str(t[0]) + str(t[1]) + str(t[2]) + "_" + str(t[3]) + str(t[4]) + str(t[5]) + ".jpg"
cv2.imwrite(filename, frame31)
frame31 = frame32
ret3, frame32 = cap3.read()
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap3.release()
cv2.destroyAllWindows()
The problem I have is when I try to do the same job in parallel for the three cameras.
What I do is duplicating the same process in the while loop for the three cameras and when I do so, it starts running for a few seconds and then I get this error :
Traceback (most recent call last):
File "C:/Users/Guillaume/PycharmProjects/IPCAM/IPCAM2.py", line 54, in <module>
gray2 = cv2.cvtColor(diff2, cv2.COLOR_BGR2GRAY)
cv2.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'
The code I run in below :
import cv2
import numpy as np
from datetime import datetime
import time
cap2 = cv2.VideoCapture('rtsp://') # IPCAM2
cap = cv2.VideoCapture('rtsp://') # IPCAM1
cap3 = cv2.VideoCapture('http://') # RASP
def rescale_frame(frame, percent=75):
width = int(frame.shape[1] * percent / 100)
height = int(frame.shape[0] * percent / 100)
dim = (width, height)
return cv2.resize(frame, dim, interpolation=cv2.INTER_AREA)
while (True):
ret1, frame11 = cap.read()
ret1, frame12 = cap.read()
ret2, frame21 = cap2.read()
ret2, frame22 = cap2.read()
ret3, frame31 = cap3.read()
ret3, frame32 = cap3.read()
diff1 = cv2.absdiff(frame11, frame12)
gray1 = cv2.cvtColor(diff1, cv2.COLOR_BGR2GRAY)
blur1 = cv2.GaussianBlur(gray1, (5, 5), 0)
_, tresh1 = cv2.threshold(blur1, 40, 255, cv2.THRESH_BINARY)
dilated1 = cv2.dilate(tresh1, None, iterations=3)
contours1, _ = cv2.findContours(dilated1, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
for contour in contours1:
(x, y, w, h) = cv2.boundingRect(contour)
if cv2.contourArea(contour) < 1000:
continue
cv2.rectangle(frame11, (x, y), (x + w, y + h), (0, 255, 0), 2)
cv2.putText(frame11, "Status: {}".format('Movement'), (10, 20), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 3)
t = time.localtime()
filename = str(t[0]) + str(t[1]) + str(t[2]) + "_" + str(t[3]) + str(t[4]) + str(t[5]) + ".jpg"
cv2.imwrite(filename, frame11)
# cv2.line(frame, (0, 300), (200, 200), (0, 255, 0), 5)
resizedframe11 = rescale_frame(frame11, percent=75)
cv2.imshow('frame', resizedframe11)
frame11 = frame12
ret1, frame12 = cap.read()
diff2 = cv2.absdiff(frame21, frame22)
gray2 = cv2.cvtColor(diff2, cv2.COLOR_BGR2GRAY)
blur2 = cv2.GaussianBlur(gray2, (5, 5), 0)
_, tresh2 = cv2.threshold(blur2, 40, 255, cv2.THRESH_BINARY)
dilated2 = cv2.dilate(tresh2, None, iterations=3)
contours2, _ = cv2.findContours(dilated2, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
for contour in contours2:
(x, y, w, h) = cv2.boundingRect(contour)
if cv2.contourArea(contour) < 1000:
continue
cv2.rectangle(frame21, (x, y), (x + w, y + h), (0, 255, 0), 2)
cv2.putText(frame21, "Status: {}".format('Movement'), (10, 20), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 3)
t = time.localtime()
filename = str(t[0]) + str(t[1]) + str(t[2]) + "_" + str(t[3]) + str(t[4]) + str(t[5]) + ".jpg"
cv2.imwrite(filename, frame21)
resizedframe21 = rescale_frame(frame21, percent=75)
cv2.imshow('frame2', resizedframe21)
frame21 = frame22
ret2, frame22 = cap2.read()
diff3 = cv2.absdiff(frame31, frame32)
gray3 = cv2.cvtColor(diff3, cv2.COLOR_BGR2GRAY)
blur3 = cv2.GaussianBlur(gray3, (5, 5), 0)
_, tresh3 = cv2.threshold(blur3, 40, 255, cv2.THRESH_BINARY)
dilated3 = cv2.dilate(tresh3, None, iterations=3)
contours3, _ = cv2.findContours(dilated3, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
for contour in contours3:
(x, y, w, h) = cv2.boundingRect(contour)
if cv2.contourArea(contour) < 800:
continue
cv2.rectangle(frame31, (x, y), (x + w, y + h), (0, 255, 0), 2)
cv2.putText(frame31, "Status: {}".format('Movement'), (10, 20), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 3)
t = time.localtime()
filename = "RASP" + str(t[0]) + str(t[1]) + str(t[2]) + "_" + str(t[3]) + str(t[4]) + str(t[5]) + ".jpg"
cv2.imwrite(filename, frame31)
resizedframe31 = rescale_frame(frame31, percent=75)
cv2.imshow('frame3', resizedframe31)
frame31 = frame32
ret3, frame32 = cap3.read()
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release()
cv2.destroyAllWindows()
Thanks Kartik and thekangaroo for your answers.
I managed to run my three cameras at the same time using threads. I am just opening them and showing a resized stream.
There is another issue as one cameras, and then a second, stops after a random time between 5 to 20 seconds. The stream stops and then the windows closes without any messages.
It seems to me that it is due to lagging getting the image from the cameras... any ideas to avoid that with openCV ?
Thanks again for your helpful answers.
Below is the code I use :
import cv2
import threading
import time
class camThread(threading.Thread):
def __init__(self, previewName, camID):
threading.Thread.__init__(self)
self.previewName = previewName
self.camID = camID
def run(self):
print("Starting " + self.previewName)
camPreview(self.previewName, self.camID)
def rescale_frame(frame, percent=75):
width = int(frame.shape[1] * percent / 100)
height = int(frame.shape[0] * percent / 100)
dim = (width, height)
return cv2.resize(frame, dim, interpolation=cv2.INTER_AREA)
def camPreview(previewName, camID):
cv2.namedWindow(previewName)
cam = cv2.VideoCapture(camID)
if cam.isOpened(): # try to get the first frame
rval, frame = cam.read()
else:
time.sleep(10)
rval, frame = cam.read()
percent = 50
width = int(frame.shape[1] * percent / 100)
height = int(frame.shape[0] * percent / 100)
dim = (width, height)
while rval:
# cv2.imshow(previewName, frame)
cv2.imshow(previewName, cv2.resize(frame, dim, interpolation=cv2.INTER_AREA))
time.sleep(0.5)
rval, frame = cam.read()
key = cv2.waitKey(20)
print(previewName + str(cam.isOpened()))
# Create two threads as follows
thread1 = camThread("CLIO", 'rtsp://xxxx')
thread2 = camThread("JARDIN", 'rtsp://xxxx')
thread3 = camThread("RASPCAM", 'http://xxxx')
thread1.start()
thread2.start()
thread3.start()
I want to ask how to change the color of Bounding Box and Font of a detected object when it is past a line. I am currently working on a project on human walking speed estimation by using Haar-cascade. The program works as such: the detected object passes two imaginary lines and when it passes the second line the program will show the speed. If the speed of the detected humans is below 3 km/h, the Bounding Box and the font will be shown in RED, but if it is more than 3 km/h it will be shown in GREEN. And I want the text of the speed to be shown for 5 seconds.
Hope you can help me solve this. Here's the program that I've worked on.
import time
cascade_src = 'haarcascade_fullbody.xml'
video_src = 'video-1.mp4'
#line a
ax1=15
ay=225
ax2=600
#line b
bx1=15
by=275
bx2=600
#car num
i = 1
start_time = time.time()
#video ....
cap = cv2.VideoCapture(video_src)
human_cascade = cv2.CascadeClassifier(cascade_src)
videoWidth = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
videoHeight = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
fourcc = cv2.VideoWriter_fourcc(*'XVID')
out = cv2.VideoWriter('wisuda-14.mp4', fourcc, 25.0, (videoWidth,videoHeight))
def Speed_Cal(time):
try:
Speed = (9.144*3600)/(time*1000)
return Speed
except ZeroDivisionError:
print (5)
while True:
ret, img = cap.read()
if (type(img) == type(None)):
break
#bluring to have exacter detection
blurred = cv2.blur(img, ksize=(3,3))
gray = cv2.cvtColor(blurred, cv2.COLOR_BGR2GRAY)
human = human_cascade.detectMultiScale(gray, scaleFactor=1.04865, minNeighbors=6)
#line a #i know road has got
cv2.line(img,(ax1,ay),(ax2,ay),(255,0,0),2)
#line b
cv2.line(img,(bx1,by),(bx2,by),(255,0,0),2)
for (x,y,w,h) in human:
cv2.rectangle(img, (x,y), (x + w, y + h), (0, 0, 255), 2)
roi_blurred = blurred[x: x + h, y:y + w]
roi_gray = gray[x: x + h, y:y + w]
roi_img = img[x: x + h, y:y + w]
cv2.circle(img,(int((x+x+w)/2),int((y+y+h)/2)), 2,(0,255,0), -1)
#cv2.putText(img, "ID : " + str(i), (x, y-15), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 0, 0), 1);
while int(ay) == int((y+y+h)/2):
start_time = time.time()
break
while int(ay) <= int((y+y+h)/2):
if int(by) <= int((y+y+h)/2)&int(by+10) >= int((y+y+h)/2):
cv2.line(img, (bx1,by), (bx2,by), (0,255,0), 2)
Speed = Speed_Cal(time.time() - start_time)
print("ID Number "+str(i)+" Speed: " + str(int(Speed)))
i = i + 1
cv2.putText(img, "Speed: "+str(int(Speed))+"km/jam", (x,y), cv2.FONT_HERSHEY_SIMPLEX, 1, (255,0,0), 2);
break
else :
break
out.write(img)
cv2.imshow('video', img)
cv2.imshow('Gray', gray)
cv2.imshow('Blurr', blurred)
if cv2.waitKey(33) == 27:
break
cap.release()
out.release()
cv2.destroyAllWindows()
I do really hope you can help me guys, please.
cv2.rectangle(img, (x,y), (x + w, y + h), (0, 0, 255), 2) the tuple with 3 elements: (0, 0, 255) is correspondent to the RGB (or BGR I forgot) value of the bounding rectangle, changing the values will change the color. For more information on bounding rectangles, check out the OpenCV drawing functions doc: https://docs.opencv.org/2.4/modules/core/doc/drawing_functions.html
As for the text color, cv2.putText(img, "Speed: "+str(int(Speed))+"km/jam", (x,y), cv2.FONT_HERSHEY_SIMPLEX, 1, (255,0,0), 2), changing the tuple (255,0,0) will change the text color.
import time
start = time.time()
sec = 5
while True:
if condition:
start = time.time()
if time.time() - start < sec:
#do whatever
so here is my code, I'm using OpenCV's cascade files to detect face and eye position and then using it in the following part.
# Importing relevant libraries
import cv2 import os import tensorflow from keras.models import load_model import numpy as np import pygame import time
# Adding alarm to raise alert pygame.init() sound = pygame.mixer.Sound('alarm.wav')
# initialising -> cascade files into cascade classifier -> OpenCV
face = cv2.CascadeClassifier('/Users/ankush/Desktop/sleepy-driver-alert/haar-cascade-files/haarcascade_frontalface_alt.xml') l_eye = cv2.CascadeClassifier('/Users/ankush/Desktop/sleepy-driver-alert/haar-cascade-files/haarcascade_lefteye_2splits.xml') r_eye = cv2.CascadeClassifier('/Users/ankush/Desktop/sleepy-driver-alert/haar-cascade-files/haarcascade_righteye_2splits.xml')
# start-of-execution label = ['Close', 'Open']
# load model and video capture
model = load_model('/Users/ankush/Desktop/sleepy-driver-alert/models/cnnCat2.h5') path = os.getcwd() cap = cv2.VideoCapture(0) font = cv2.FONT_HERSHEY_COMPLEX_SMALL count = 0 score = 0 dep = 2 rpred = [99] lpred = [99]
while (True):
ret, frame = cap.read()
height, width = frame.shape[:2]
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = face.detectMultiScale(gray, minNeighbors=5, scaleFactor=1.1, minSize=(25, 25))
left_eye_gray = r_eye.detectMultiScale(gray)
right_eye_gray = l_eye.detectMultiScale(gray)
cv2.rectangle(frame, (0, height - 50), (200, height),
(0, 0, 0), thickness=cv2.FILLED)
for (x, y, w, h) in faces:
cv2.rectangle(frame, (x, y), (x + w, y + h), (100, 100, 100), 1)
# Next few lines check if eyes are open or not ->rpred,lpred variables
# right
for (x, y, w, h) in right_eye_gray:
r_eye = frame[y:y + h, x:x + w]
count = count + 1
r_eye = cv2.cvtColor(r_eye, cv2.COLOR_BGR2GRAY)
r_eye = cv2.resize(r_eye, (24, 24))
r_eye = r_eye / 255
r_eye = r_eye.reshape(24, 24, -1)
r_eye = np.expand_dims(r_eye, axis=0)
rpred = model.predict_classes(r_eye)
if (rpred[0] == 1):
label = 'Open'
if (rpred[0] == 0):
label = 'Closed'
break
# left
for (x, y, w, h) in left_eye_gray:
l_eye = frame[y:y + h, x:x + w]
count = count + 1
l_eye = cv2.cvtColor(l_eye, cv2.COLOR_BGR2GRAY)
l_eye = cv2.resize(l_eye, (24, 24))
l_eye = l_eye / 255
l_eye = l_eye.reshape(24, 24, -1)
l_eye = np.expand_dims(l_eye, axis=0)
lpred = model.predict_classes(l_eye)
if (lpred[0] == 1):
label = 'Open'
if (lpred[0] == 0):
label = 'Closed'
break
# if closed eyes detected
if (rpred[0] == 0 and lpred[0] == 0):
score = score + 1
cv2.putText(frame, "Closed", (10, height - 20), font, 1, (255, 255, 255), 1, cv2.LINE_AA)
# if for some reason only one is closed, driver is not sleeping
else:
score = score - 1
cv2.putText(frame, "Open", (10, height - 20), font, 1, (255, 255, 255), 1, cv2.LINE_AA)
if (score < 0):
score = 0
cv2.putText(frame, 'Score:' + str(score), (100, height - 20), font, 1, (255, 255, 255), 1, cv2.LINE_AA)
# if person is very sleepy, high score, eyes closed
if (score > 15):
cv2.imwrites(os.path.join(path, 'image.jpg'), frame)
try:
sound.play()
except:
pass
if (dep < 16):
dep = dep + 2
else:
dep = dep - 2
if (dep < 2):
dep = 2
cv2.rectangle(frame, (0, 0), (width, height), (0, 0, 255), dep)
cv2.imshow('frame', frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
cap.release() cv2.destroyAllWindows()
And the error that I'm getting is;
Traceback (most recent call last): File
"/Users/ankush/Desktop/sleepy-driver-alert/Sleepy-driver-detector.py",
line 44, in
right_eye_gray = l_eye.detectMultiScale(gray) AttributeError: 'numpy.ndarray' object has no attribute 'detectMultiScale'
What am I doing wrong? I'm a beginner.