We Keep Coding

How to stack all images in a directory vertically into one long image

I've been trying to merge images together into one long image. The images are all in one folder and have the same file name format group1.X.jpg with X being a number, starting at 0. I've tried using img.paste to merge the images together.
This is basically what I've been trying:
img1 = Image.open(directory + filePrefix + str(fileFirst) + fileExtension)
w, h = img1.size
h = h * fileCount
img = Image.new("RGB", (w, h))
tmpImg = img.load()
console.log("Setup Complete")
number = 0
for number in track(range(fileCount - 1)):
imgPaste = Image.open(dir + prefix + str(number) + extension)
if not number >= fileCount:
Image.Image.paste(tmpImg, imgPaste, (0, h * (number + 1)))
number += 1
img.save(file)
stitch(directory, filePrefix, fileExtension)
The above code, when ran, outputs the following:
Working... ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 0% -:--:--
Traceback (most recent call last):
File "c:\Users\marcus\Desktop\Stuff\Files\code\webtoonstitcher.py", line 36, in <module>
stitch(directory, filePrefix, fileExtension)
File "c:\Users\marcus\Desktop\Stuff\Files\code\webtoonstitcher.py", line 32, in stitch
Image.Image.paste(tmpImg, imgPaste, (0, h * (number + 1)))
File "C:\Users\marcus\AppData\Roaming\Python\Python310\site-packages\PIL\Image.py", line 1619, in paste
if self.mode != im.mode:
AttributeError: 'PixelAccess' object has no attribute 'mode'```

You can get list of all images using glob and then just iterate through that list:
import glob
from PIL import Image
def stitch(directory, file_prefix, file_extension):
files = glob.glob(directory + f'{file_prefix}*.{file_extension}')
images = [Image.open(file) for file in files]
background_width = max([image.width for image in images])
background_height = sum([image.height for image in images])
background = Image.new('RGBA', (background_width, background_height), (255, 255, 255, 255))
y = 0
for image in images:
background.paste(image, (0, y))
y += image.height
background.save('image.png')
stitch('', 'group1', 'png')
Sample output:

I think the issue is here:
h = h * fileCount
img = Image.new("RGB", (w, h))
You should delete the first line and change the second line to:
img = Image.new("RGB", (w, h * fileCount))
Otherwise your h will be far too big when you use it later to calculate the offset for paste().

Is there a way to determine which camera has recognized a person in live stream when using multiple cameras for facial recognition in python

This is a facial recognition program and is programmed with python and opencv with database insertion model through MySQL.
I have one query in the program.
In the first part, there is real-time data insertion in a table when the camera recognizes a person through the pictures given in which a date, time, name and ID stamp is inserted in the database. I also want to insert the camera name which has recognized the person to know the particular location also.
face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')
recognizer = cv2.face.LBPHFaceRecognizer_create()
recognizer.read("trainner.yml")
labels = {"person_name": 1}
with open("labels.pickle", 'rb') as f:
og_labels = pickle.load(f)
labels = {v: k for k, v in og_labels.items()}
cap = cv2.VideoCapture(0)
#cap1 = cv2.VideoCapture('rtsp://admin:umerkhan261#192.168.226.201')
while True:
ret, frame = cap.read()
# ret, frame1 = cap1.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
#gray1 = cv2.cvtColor(frame1, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, scaleFactor=1.5, minNeighbors=5)
now = datetime.now()
print("Today's date: ", str(now))
for (x, y, w, h) in faces:
roi_gray = gray[y:y + h, x:x + w]
# roi_gray1 = gray1[y:y + h, x:x + w]
roi_color = frame[y:y + h, x:x + w]
# roi_color1 = frame1[y:y + h, x:x + w]
# deep Learned Model for recognizing the person in live stream
id_, conf = recognizer.predict(roi_gray)
# id_, conf = recognizer.predict(roi_gray1)
if 45 <= conf <= 85:
print(id_)
print(labels[id_])
font = cv2.FONT_HERSHEY_SIMPLEX
name = labels[id_]
new = datetime.now()
tString = new.strftime('%H:%M:%S')
dtString = new.strftime('%D:%m')

I figured out a way to solve the problem. I made the frame reading from my webcam a function with a variable named cam1, then I made another python file copied the whole program and named that variable to cam2. I made another file calling those functions on the main file and by the multi threading function I called them simultaneously. It turned out to be successful

AttributeError: 'bytes' object has no attribute 'read'

I am working on this face recognition system.I have a folder with subfolders that has face images inside it. I am trying to loop through all the subfolders that consists of images and use my 'align_face' function that detects the face and crops and aligns all the images in subfolders. It then has to save all the aligned and cropped in another folder
I have tried this:
def align_face(imagePath):
image = face_recognition.load_image_file(imagePath)
face_locations = face_recognition.face_locations(image)
face_landmarks = face_recognition.face_landmarks(image)
if len(face_locations) == 0:
print("Couldn't detect face for pid {} in path {}".format(Id,imagePath))
return []
if len(face_locations) > 1:
return []
else:
(top, right, bottom, left) = face_locations[0]
desiredWidth = (right - left)
desiredHeight = (bottom - top)
leftEyePts = face_landmarks[0]['left_eye']
rightEyePts = face_landmarks[0]['right_eye']
if len(leftEyePts) == 0 or len(rightEyePts) == 0:
print("Couldn't detect both eyes for pid {} in path {}".format(Id,imagePath))
return []
else:
leftEyeCenter = np.array(leftEyePts).mean(axis=0).astype("int")
rightEyeCenter = np.array(rightEyePts).mean(axis=0).astype("int")
leftEyeCenter = (leftEyeCenter[0],leftEyeCenter[1])
rightEyeCenter = (rightEyeCenter[0],rightEyeCenter[1])
dY = rightEyeCenter[1] - leftEyeCenter[1]
dX = rightEyeCenter[0] - leftEyeCenter[0]
angle = np.degrees(np.arctan2(dY, dX))
desiredLeftEye=(0.35, 0.35)
desiredFaceWidth = desiredWidth
desiredFaceHeight = desiredHeight
desiredRightEyeX = 1.0 - desiredLeftEye[0]
dist = np.sqrt((dX ** 2) + (dY ** 2))
desiredDist = (desiredRightEyeX - desiredLeftEye[0])
desiredDist *= desiredFaceWidth
scale = desiredDist / dist
eyesCenter = ((leftEyeCenter[0] + rightEyeCenter[0]) // 2,
(leftEyeCenter[1] + rightEyeCenter[1]) // 2)
M = cv2.getRotationMatrix2D(eyesCenter, angle, scale)
tX = desiredFaceWidth * 0.5
tY = desiredFaceHeight * desiredLeftEye[1]
M[0, 2] += (tX - eyesCenter[0])
M[1, 2] += (tY - eyesCenter[1])
(w, h) = (desiredFaceWidth, desiredFaceHeight)
output = cv2.warpAffine(image, M, (w, h),flags=cv2.INTER_CUBIC)
output = cv2.cvtColor(output, cv2.COLOR_BGR2RGB)
print("images aligned")
return output
#Now that we have defined the face alignmet and cropping, we walk through each subfolder and use the align function
for root, dirs, files in os.walk('<path to subdirectories that has face pictures>'):
for fname in files:
fpath = os.path.join(root, fname)
with open(fpath, 'rb') as f, open('<path to new folder to store cropped and aligned picture>', 'w') as newfile:
data = f.read()
new_data = align_face(data) #Implementing align_face function
newfile.write(new_data)
However, I keep getting an error.
AttributeError: 'bytes' object has no attribute 'read'
Does anyone know why?Any help would be appreciated. Thank you.
Full error is this:

The argument to align_face is the name of the file containing the image data, not the image data. So you don't need to open and read the data in your loop.
for root, dirs, files in os.walk('<path to subdirectories that has face pictures>'):
for fname in files:
fpath = os.path.join(root, fname)
with open('<path to new folder to store cropped and aligned picture>', 'w') as newfile:
new_data = align_face(fpath) #Implementing align_face function
newfile.write(new_data)

OpenCV + RaspberyPI like a room monitor

I'm new using opencv and python, my project its about a smarthome.
I managed to install opencv on a raspberrypi and using a webcam.
My program will work on the following three scenarios.
1.A person enters the room, detects face and person, sends message "Dad is in room 1."
2.A person enters the room, detects face but not person, sends message "Unknown person is in room 1"
3. No one is in the room, send a message "No one is in room 1"
Scenarios 1 and 2 I have idea how to solve them, but where I am stuck is in the esceanrio 3. I tried to save the name of the detected person in a variable, if this is empty should send the message, but it has not worked for me.
The code I am using is the following, the problem I have is at the end of the code:
import cv2, sys, numpy, os
size = 1
fn_haar = 'haarcascade_frontalface_default.xml'
fn_dir = 'att_faces'
# Part 1: Create fisherRecognizer
print('Training...')
# Create a list of images and a list of corresponding names
(images, lables, names, id) = ([], [], {}, 0)
# Get the folders containing the training data
for (subdirs, dirs, files) in os.walk(fn_dir):
# Loop through each folder named after the subject in the photos
for subdir in dirs:
names[id] = subdir
subjectpath = os.path.join(fn_dir, subdir)
# Loop through each photo in the folder
for filename in os.listdir(subjectpath):
# Skip non-image formates
f_name, f_extension = os.path.splitext(filename)
if(f_extension.lower() not in
['.png','.jpg','.jpeg','.gif','.pgm']):
print("Skipping "+filename+", wrong file type")
continue
path = subjectpath + '/' + filename
lable = id
# Add to training data
images.append(cv2.imread(path, 0))
lables.append(int(lable))
id += 1
(im_width, im_height) = (112, 92)
# Create a Numpy array from the two lists above
(images, lables) = [numpy.array(lis) for lis in [images, lables]]
# OpenCV trains a model from the images
model = cv2.face.createFisherFaceRecognizer()
model.train(images, lables)
# Part 2: Use fisherRecognizer on camera stream
haar_cascade = cv2.CascadeClassifier(fn_haar)
webcam = cv2.VideoCapture(0)
while True:
# Loop until the camera is working
rval = False
while(not rval):
# Put the image from the webcam into 'frame'
(rval, frame) = webcam.read()
if(not rval):
print("Failed to open webcam. Trying again...")
# Flip the image (optional)
frame=cv2.flip(frame,1,0)
# Convert to grayscalel
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# Resize to speed up detection (optinal, change size above)
mini = cv2.resize(gray, (int(gray.shape[1] / size), int(gray.shape[0] / size)))
# Detect faces and loop through each one
faces = haar_cascade.detectMultiScale(mini)
for i in range(len(faces)):
face_i = faces[i]
# Coordinates of face after scaling back by `size`
(x, y, w, h) = [v * size for v in face_i]
face = gray[y:y + h, x:x + w]
face_resize = cv2.resize(face, (im_width, im_height))
# Try to recognize the face
prediction = model.predict(face_resize)
cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 3)
# [1]
# Write the name of recognized face
cv2.putText(frame,
'%s - %.0f' % (names[prediction[0]],prediction[1]),
(x-10, y-10), cv2.FONT_HERSHEY_PLAIN,1,(0, 255, 0))
face = '%S' % (names[prediction[0]]) #Guardar nombre en variable
#Start to validate the name
if face != "" : #If a name is detected
print(face + "Is in the room..") #Print the name in terminal
elif face == "" : #If a name is not detected
print("The room is empty...") #Print the text in terminal
#This last part is where I have problem, when a face is not detected, the text is not printed in the terminal
# Show the image and check for ESC being pressed
cv2.imshow('OpenCV', frame)
key = cv2.waitKey(10)
if key == 27:
break
The code I am using is based on the following tutorial: Face Detection
Any help is appreciated, thank you. Greetings

If there are no faces detected in the room, your code does not enter the for i in range(len(faces)) loop, which by the way could be simplified to for i in faces.
Thus, an else at the end of your for loop solves your problem:
for face in faces:
do_stuff(face)
else:
print("room is empty")

downsampling images as a function in Python

I am trying to resample some tiff files from 2000*2000 to 500*500.
I have created a function and I tried for one file and it worked nicely. Now I want to apply it for all the available file I have.
I want to write the output of the function and I have written the code based on my knowledge and I receive error on the writing out_file. I have copied the both function and main code for your consideration. The main code just read the tif files according to their naming and applies the function. I would be thankful if sb could guide me where my mistake is.
#*********function********************
def ResampleImage(infile):
fp = open(infile, "rb")
p = ImageFile.Parser()
while 1:
s = fp.read()
if not s:
break
p.feed(s)
img = p.close()
basewidth = 500
wpercent = (basewidth / float(img.size[0]))
hsize = int((float(img.size[1]) * float(wpercent)))
outfile=img.resize((basewidth, hsize), PIL.Image.ANTIALIAS)
return outfile
#********* main code********
import os,sys
import ImageResizeF
import PIL
from PIL import Image
from PIL import Image,ImageFile
tpath = 'e:/.../resampling_test/all_tiles/'
tifext = '.tif'
east_start = 32511616
north_start = 5400756
ilist = range (0,14)
jlist = range (0,11)
north = north_start
ee = ',4_'
en = ',2'
for i in ilist:
east = east_start
north = north_start + i * 400
snorth = str (north)
for j in jlist:
east = east_start + j * 400
seast = str (east)
infile = tpath + seast + ee + snorth + en + tifext
output = tpath + seast + ee + snorth + en + '_res'+tifext
out_file = ImageResizeF.ResampleImage(infile)
out_file.write (output)
out_file.close ()

Your error is probably related to what you are returning from ImageResizeF.ResampleImage, is it a file handle? Otherwise you are doing it wrong because you cannot close() something which is not a file handle. You should do the whole file processing inside the function or return an image object, for example:
def process_image(image):
"Processes the image"
image.resize((x, y), Image.ANTIALIAS) # or whatever you are doing to the image
return image
image = Image.open('infile.tiff')
proc_image = process_image(image)
proc_image.save('outfile.tiff')