I am writing my project on face detection and recognition system which i need programming work for

U chose a project u don't hv idea of. Better go change topic

slimjohn2k5:
U chose a project u don't hv idea of. Better go change topic

I knew about the project but i don't know about the programming stuff

Do you have some level of coding knowledge?
Go and use ChatGPT. It can help you with an idea on what to do.
Here is what I got when I asked the question on ChatGPT:


There are many libraries and frameworks available that can be used for face detection and recognition, such as OpenCV, Dlib, and FaceNet. Here's an example of how to use OpenCV's Haar Cascade classifier for face detection in Python:

Copy code
import cv2

# Load the cascade classifier
face_cascade = cv2.CascadeClassifier("path/to/haarcascade_frontalface_default.xml"

# Read the input image
img = cv2.imread("path/to/image.jpg"

# Convert into grayscale
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

# Detect faces
faces = face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5)

# Draw rectangle around the faces
for (x, y, w, h) in faces:
cv2.rectangle(img, (x, y), (x+w, y+h), (255, 0, 0), 2)

# Display the output
cv2.imshow("img", img)
cv2.waitKey()
Note that this is a basic example, and you may need to adjust the parameters depending on the specific image and use case.

For Face Recognition, you can use the libraries like face_recognition, facenet-pytorch, etc.

Copy code
import face_recognition

# Load the jpg files into numpy arrays
biden_image = face_recognition.load_image_file("biden.jpg"
obama_image = face_recognition.load_image_file("obama.jpg"
unknown_image = face_recognition.load_image_file("unknown.jpg"

# Get the face encodings for each face in each image file
# Since there could be more than one face in each image, it returns a list of encodings.
# But since I know each image only has one face, I only care about the first encoding in each image, so I grab index 0.
try:
biden_face_encoding = face_recognition.face_encodings(biden_image)[0]
obama_face_encoding = face_recognition.face_encodings(obama_image)[0]
unknown_face_encoding = face_recognition.face_encodings(unknown_image)[0]
except IndexError:
print("I wasn't able to locate any faces in at least one of the images. Check the image files. Aborting..."
quit()

known_faces = [
biden_face_encoding,
obama_face_encoding
]

# results is an array of True/False telling if the unknown face matched anyone in the known_faces array
results = face_recognition.compare_faces(known_faces, unknown_face_encoding)

print("Is the unknown face a picture of Biden? {}".format(results[0]))
print("Is the unknown face a picture of Obama? {}".format(results[1]))
print("Is the unknown face a new person that we've never seen before? {}".format(not True in results))
You can also use deep learning libraries like facenet

Thanks

Enskynelson:
Do you have some level of coding knowledge?
Go and use ChatGPT. It can help you with an idea on what to do.
Here is what I got when I asked the question on ChatGPT:


There are many libraries and frameworks available that can be used for face detection and recognition, such as OpenCV, Dlib, and FaceNet. Here's an example of how to use OpenCV's Haar Cascade classifier for face detection in Python:

Copy code
import cv2

# Load the cascade classifier
face_cascade = cv2.CascadeClassifier("path/to/haarcascade_frontalface_default.xml"

# Read the input image
img = cv2.imread("path/to/image.jpg"

# Convert into grayscale
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

# Detect faces
faces = face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5)

# Draw rectangle around the faces
for (x, y, w, h) in faces:
cv2.rectangle(img, (x, y), (x+w, y+h), (255, 0, 0), 2)

# Display the output
cv2.imshow("img", img)
cv2.waitKey()
Note that this is a basic example, and you may need to adjust the parameters depending on the specific image and use case.

For Face Recognition, you can use the libraries like face_recognition, facenet-pytorch, etc.

Copy code
import face_recognition

# Load the jpg files into numpy arrays
biden_image = face_recognition.load_image_file("biden.jpg"
obama_image = face_recognition.load_image_file("obama.jpg"
unknown_image = face_recognition.load_image_file("unknown.jpg"

# Get the face encodings for each face in each image file
# Since there could be more than one face in each image, it returns a list of encodings.
# But since I know each image only has one face, I only care about the first encoding in each image, so I grab index 0.
try:
biden_face_encoding = face_recognition.face_encodings(biden_image)[0]
obama_face_encoding = face_recognition.face_encodings(obama_image)[0]
unknown_face_encoding = face_recognition.face_encodings(unknown_image)[0]
except IndexError:
print("I wasn't able to locate any faces in at least one of the images. Check the image files. Aborting..."
quit()

known_faces = [
biden_face_encoding,
obama_face_encoding
]

# results is an array of True/False telling if the unknown face matched anyone in the known_faces array
results = face_recognition.compare_faces(known_faces, unknown_face_encoding)

print("Is the unknown face a picture of Biden? {}".format(results[0]))
print("Is the unknown face a picture of Obama? {}".format(results[1]))
print("Is the unknown face a new person that we've never seen before? {}".format(not True in results))
You can also use deep learning libraries like facenet

E can never understand anything here...

slimjohn2k5:
U chose a project u don't hv idea of. Better go change topic

you need to change where you are commenting first since you have no idea for poster.

Mubarak225:

I knew about the project but i don't know about the programming stuff

How you intend defending it ?

Enskynelson:
Do you have some level of coding knowledge?
Go and use ChatGPT. It can help you with an idea on what to do.
Here is what I got when I asked the question on ChatGPT:


There are many libraries and frameworks available that can be used for face detection and recognition, such as OpenCV, Dlib, and FaceNet. Here's an example of how to use OpenCV's Haar Cascade classifier for face detection in Python:

Copy code
import cv2

# Load the cascade classifier
face_cascade = cv2.CascadeClassifier("path/to/haarcascade_frontalface_default.xml"

# Read the input image
img = cv2.imread("path/to/image.jpg"

# Convert into grayscale
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

# Detect faces
faces = face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5)

# Draw rectangle around the faces
for (x, y, w, h) in faces:
cv2.rectangle(img, (x, y), (x+w, y+h), (255, 0, 0), 2)

# Display the output
cv2.imshow("img", img)
cv2.waitKey()
Note that this is a basic example, and you may need to adjust the parameters depending on the specific image and use case.

For Face Recognition, you can use the libraries like face_recognition, facenet-pytorch, etc.

Copy code
import face_recognition

# Load the jpg files into numpy arrays
biden_image = face_recognition.load_image_file("biden.jpg"
obama_image = face_recognition.load_image_file("obama.jpg"
unknown_image = face_recognition.load_image_file("unknown.jpg"

# Get the face encodings for each face in each image file
# Since there could be more than one face in each image, it returns a list of encodings.
# But since I know each image only has one face, I only care about the first encoding in each image, so I grab index 0.
try:
biden_face_encoding = face_recognition.face_encodings(biden_image)[0]
obama_face_encoding = face_recognition.face_encodings(obama_image)[0]
unknown_face_encoding = face_recognition.face_encodings(unknown_image)[0]
except IndexError:
print("I wasn't able to locate any faces in at least one of the images. Check the image files. Aborting..."
quit()

known_faces = [
biden_face_encoding,
obama_face_encoding
]

# results is an array of True/False telling if the unknown face matched anyone in the known_faces array
results = face_recognition.compare_faces(known_faces, unknown_face_encoding)

print("Is the unknown face a picture of Biden? {}".format(results[0]))
print("Is the unknown face a picture of Obama? {}".format(results[1]))
print("Is the unknown face a new person that we've never seen before? {}".format(not True in results))
You can also use deep learning libraries like facenet

programing no be like other courses anyone could pick up or cut & join along the way. How OP wan take know where to stich above code into the workflow him already get.

Shey OP even understand the language above, let along how to stich it into his existing words. You sef wey dey provide sentences, shey you know what language OP already dey On ?

Very soon, just very soon, people would turn to ChatGPT for all those Threads they create asking Marriage / relationship ADVICEs

bassdow:



programing no be like other courses anyone could pick up or cut & join along the way. How OP wan take know where to stich above code into the workflow him already get.

Shey OP even understand the language above, let along how to stich it into his existing words. You sef wey dey provide sentences, shey you know what language OP already dey On ?

Very soon, just very soon, people would turn to ChatGPT for all those Threads they create asking Marriage / relationship ADVICEs

Like as someone pointed out, OP is required to have some level of knowledge of programming in one of the languages for that research project.
Otherwise, he will have to contract that part of the project to someone. I am sure those codes would have made sense to him if he had an idea on any of the major programming languages.

bassdow:

How you intend defending it ?

Haven't know

Enskynelson:

Like as someone pointed out, OP is required to have some level of knowledge of programming in one of the languages for that research project.
Otherwise, he will have to contract that part of the project to someone. I am sure those codes would have made sense to him if he had an idea on any of the major programming languages.

I know some programming language like java, cobol, fortran and so on but i am told to use phyton to write the program for the project.