RuntimeError: Unsupported image type, must be 8bit gray or RGB image.

[s0m31-hub]

• face_recognition version: 1.2.2
• Python version: 3.12.3
• Operating System: Fedora 39

Description

Just trying to launch official example. The issue appears while reading jpg image, not camera input

What I Did

import face_recognition
import cv2
import numpy as np

# This is a demo of running face recognition on live video from your webcam. It's a little more complicated than the
# other example, but it includes some basic performance tweaks to make things run a lot faster:
#   1. Process each video frame at 1/4 resolution (though still display it at full resolution)
#   2. Only detect faces in every other frame of video.

# PLEASE NOTE: This example requires OpenCV (the `cv2` library) to be installed only to read from your webcam.
# OpenCV is *not* required to use the face_recognition library. It's only required if you want to run this
# specific demo. If you have trouble installing it, try any of the other demos that don't require it instead.

# Get a reference to webcam #0 (the default one)
video_capture = cv2.VideoCapture(0)

# Load a sample picture and learn how to recognize it.
obama_image = face_recognition.load_image_file("obama.jpg")
obama_face_encoding = face_recognition.face_encodings(obama_image)[0]

# Load a second sample picture and learn how to recognize it.
biden_image = face_recognition.load_image_file("biden.jpg")
biden_face_encoding = face_recognition.face_encodings(biden_image)[0]

# Create arrays of known face encodings and their names
known_face_encodings = [
    obama_face_encoding,
    biden_face_encoding
]
known_face_names = [
    "Barack Obama",
    "Joe Biden"
]

# Initialize some variables
face_locations = []
face_encodings = []
face_names = []
process_this_frame = True

while True:
    # Grab a single frame of video
    ret, frame = video_capture.read()

    # Only process every other frame of video to save time
    if process_this_frame:
        # Resize frame of video to 1/4 size for faster face recognition processing
        small_frame = cv2.resize(frame, (0, 0), fx=0.25, fy=0.25)

        # Convert the image from BGR color (which OpenCV uses) to RGB color (which face_recognition uses)
        rgb_small_frame = small_frame[:, :, ::-1]

        # Find all the faces and face encodings in the current frame of video
        face_locations = face_recognition.face_locations(rgb_small_frame)
        face_encodings = face_recognition.face_encodings(rgb_small_frame, face_locations)

        face_names = []
        for face_encoding in face_encodings:
            # See if the face is a match for the known face(s)
            matches = face_recognition.compare_faces(known_face_encodings, face_encoding)
            name = "Unknown"

            # # If a match was found in known_face_encodings, just use the first one.
            # if True in matches:
            #     first_match_index = matches.index(True)
            #     name = known_face_names[first_match_index]

            # Or instead, use the known face with the smallest distance to the new face
            face_distances = face_recognition.face_distance(known_face_encodings, face_encoding)
            best_match_index = np.argmin(face_distances)
            if matches[best_match_index]:
                name = known_face_names[best_match_index]

            face_names.append(name)

    process_this_frame = not process_this_frame

    # Display the results
    for (top, right, bottom, left), name in zip(face_locations, face_names):
        # Scale back up face locations since the frame we detected in was scaled to 1/4 size
        top *= 4
        right *= 4
        bottom *= 4
        left *= 4

        # Draw a box around the face
        cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255), 2)

        # Draw a label with a name below the face
        cv2.rectangle(frame, (left, bottom - 35), (right, bottom), (0, 0, 255), cv2.FILLED)
        font = cv2.FONT_HERSHEY_DUPLEX
        cv2.putText(frame, name, (left + 6, bottom - 6), font, 1.0, (255, 255, 255), 1)

    # Display the resulting image
    cv2.imshow('Video', frame)

    # Hit 'q' on the keyboard to quit!
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

# Release handle to the webcam
video_capture.release()
cv2.destroyAllWindows()

Traceback (most recent call last):
  File "/home/admin/PycharmProjects/faces/main.py", line 19, in <module>
    obama_face_encoding = face_recognition.face_encodings(obama_image)[0]
                          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/admin/.local/lib/python3.12/site-packages/face_recognition/api.py", line 213, in face_encodings
    raw_landmarks = _raw_face_landmarks(face_image, known_face_locations, model)
                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/admin/.local/lib/python3.12/site-packages/face_recognition/api.py", line 156, in _raw_face_landmarks
    face_locations = _raw_face_locations(face_image)
                     ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/admin/.local/lib/python3.12/site-packages/face_recognition/api.py", line 105, in _raw_face_locations
    return face_detector(img, number_of_times_to_upsample)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
RuntimeError: Unsupported image type, must be 8bit gray or RGB image.

[realalley]

same problem

[harrrshall]

is there any find solution?

[Noor161]

the same problem wuth dlib face lanmarks dlib.get_frontal_face_detector(gray,1)

ERROR: hog_face_detector(gray,1)
^^^^^^^^^^^^^^^^^^^^^^^^^ RuntimeError: Unsupported image type, must be 8bit gray or RGB image.

a year ago, it was working neatly

[Noor161]

for me, I downgraded numpy to 1.4 and imported it dlib is not working well with numpy 2.0 version

credit for: https://stackoverflow.com/a/78638053/17027049

[JustinWingChungHui]

Same issue, I downgraded numpy to version 1.26.4 and it worked again Good spot @Noor161 !

[Hamza-Zartaj]

so i tried downgrading to numpy version 1.4 but it is giving me some error cant install it or something i also tried it installing manualy by downloading numpy1.4 file but still same error need help currently have these libraries installed

[JustinWingChungHui]

@Hamza-Zartaj have you tried numpy 1.26.4?

[zoldaten]

change this: rgb_small_frame = small_frame[:, :, ::-1] to rgb_small_frame = cv2.cvtColor(small_frame, cv2.COLOR_BGR2RGB)

numpy==1.26.3 opencv-python==4.9.0.80

[Hamza-Zartaj]

@Hamza-Zartaj have you tried numpy 1.26.4?

it was not installing i tried installing it. it had some error with latest python 3.12.4 so i was wondering if i need to downgrade my python version to something like 3.11.8 should i change python version?

[OgunSerifOnargan]

same problem. It looks like old error rises from the grave

[OgunSerifOnargan]

I downgraded my numpy from 2.0.0 to 1.26.4 solved my problem.

[Hamza-Zartaj]

Which python version u using for numpy 1.26.4 I tried downgrading numpy but it give some error something to do with latest python version So should I downgrade to python 3.11 or more lower like 3.9

On Tue, 25 Jun 2024 at 8:05 PM, Ogun Serif Onargan @.***> wrote:

On 16th June, numpy v2.0.0 has been released. I downgraded my numpy from 2.0.0 to 1.26.4 solved my problem.

— Reply to this email directly, view it on GitHub https://github.com/ageitgey/face_recognition/issues/1573#issuecomment-2189206485, or unsubscribe https://github.com/notifications/unsubscribe-auth/BFFISJQI2XSJ6OSTPEY5TF3ZJGBKHAVCNFSM6AAAAABJXE775SVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDCOBZGIYDMNBYGU . You are receiving this because you were mentioned.Message ID: @.***>

[JustinWingChungHui]

@Hamza-Zartaj I was using Python 3.10.5

[n07kiran]

change this: rgb_small_frame = small_frame[:, :, ::-1] to rgb_small_frame = cv2.cvtColor(small_frame, cv2.COLOR_BGR2RGB)

numpy==1.26.3 opencv-python==4.9.0.80

@zoldaten Thank you! it worked.

[dwaipayanddg]

I have moved to these versions numpy==1.26.3 opencv-python==4.9.0.80 but it is still throwing this error to me, kindly help Error: subjects = detect(gray) ^^^^^^^^^^^^ RuntimeError: Unsupported image type, must be 8bit gray or RGB image.

[madhuribs111]

Yep, downgraded numpy to 1.26.4 and its working..

My question is what is the relation between numpy version and the error: "RuntimeError: Unsupported image type, must be 8bit gray or RGB image."?

It's probably because openCV array structures are converted to numpy arrays ? But why didn't I get a better exception message?

[dwaipayanddg]

Can you tell me, whats your python version?

[madhuribs111]

@dwaipayanddg its 3.11.3

[JBelmont72]

thank you so much. I changed my bumpy to 1.26.4 and reloaded my requirements.txt. Presto.

[Boonyarit2442]

use numpy==1.26.4 can complete

[DeveloperLevin]

@Hamza-Zartaj have you tried numpy 1.26.4?

it was not installing i tried installing it. it had some error with latest python 3.12.4 so i was wondering if i need to downgrade my python version to something like 3.11.8 should i change python version?

yes downgrde your ython version, else dlib would not work

[dannamado]

j'utilise la version python 3.12.4 et j'ai installé face_recognition version 1.3.0 apres l'execution du script ,je reçois une erreur comme celle ci: RuntimeError: Unsupported image type, must be 8bit gray or RGB image.

[dannamado]

svp aidez moi

[hamstah]

Downgrading worked for me

pip uninstall numpy
pip install numpy==1.26.4

[ajmcgrail]

Downgrading worked for me, but is there a fix in the works for face recognition/dlib to work with numpy 2.0? Not sure which project would be responsible for this fix- I imagine it's face recognition?

[ramprasathmk]

change this: rgb_small_frame = small_frame[:, :, ::-1] to rgb_small_frame = cv2.cvtColor(small_frame, cv2.COLOR_BGR2RGB)

numpy==1.26.3 opencv-python==4.9.0.80

@zoldaten 100% worked bruh... Thank you so much ❤️

Python version: 3.10.x

[bryango]

Related: https://github.com/davisking/dlib/issues/1134

[ramprasathmk]

Related: https://github.com/davisking/dlib/issues/1134

Use Python 3.10.X version with a virtual environment to solve this error.

Check out: https://github.com/ramprasathmk/Automatic-Attendance-System-for-Face-Recognition/blob/master/Installation.md

[ramprasathmk]

@dwaipayanddg its 3.11.3

python3.10 works fine, ya

[mohamedmokhtar-1]

Same issue, I downgraded numpy to version 1.26.4 and it worked again Good spot @Noor161 !

thanks alot

[rjgrv]

pip install numpy==1.26.3 It worked!

[saidakbardev005]

import cv2 import face_recognition import numpy as np import mysql.connector from datetime import datetime from PIL import Image

Load and prepare images

image1_path = r"C:\Users\Saidakbar\Desktop\camera_loyiha\pythonProject\faces\Javohirbek.jpg" image2_path = r"C:\Users\Saidakbar\Desktop\camera_loyiha\pythonProject\faces\Saidakbarxo'ja.jpg"

Load images with error handling

image1 = cv2.imread(image1_path) image2 = cv2.imread(image2_path)

Agar tasvirlar yuklangan bo'lsa, ularni RGB formatga o'tkazamiz

if image1 is not None: image1 = cv2.cvtColor(image1, cv2.COLOR_BGR2RGB) else: print("image1 yuklanmadi.")

if image2 is not None: image2 = cv2.cvtColor(image2, cv2.COLOR_BGR2RGB) else: print("image2 yuklanmadi.")

MySQL connection function

def connect_database(): conn = mysql.connector.connect( host="localhost", user="root", password="saidakbardev714", database="db1" ) return conn

Save image name to MySQL

def save_image_path_to_db(img_name): conn = connect_database() cursor = conn.cursor() current_date = datetime.now().date() current_time = datetime.now().time() cursor.execute("INSERT INTO talaba_ma'lumot (rasm, kun, vaqt) VALUES (%s, %s, %s)", (img_name, current_date, current_time)) conn.commit() print(f"Rasm nomi '{img_name}' bazaga muvaffaqiyatli saqlandi.") cursor.close() conn.close()

Mark attendance

def markAttendance(name): with open('Attendance.csv', 'r+') as f: myDataList = f.readlines() nameList = [line.split(',')[0] for line in myDataList] if name not in nameList: now = datetime.now() dtString = now.strftime('%Y-%m-%d %H:%M:%S') f.writelines(f'\n{name},{dtString}')

Encode images

def findEncodings(images): encodeList = [] for img in images: if img is None: print("Tasvir yuklanmadi.") continue

Tasvirlarni RGB formatda ekanligiga ishonch hosil qilamiz

    if img.dtype != np.uint8:
        img = img.astype(np.uint8)
    rgb_img = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)
    encode = face_recognition.face_encodings(rgb_img)
    if encode:
        encodeList.append(encode[0])
    else:
        print("Yuz topilmadi.")
return encodeList

Tasvirlarni va ularning nomlarini ro'yxatga qo'shish

images = [] classNames = [] if image1 is not None: images.append(image1) classNames.append("Javohirbek")

if image2 is not None: images.append(image2) classNames.append("Saidakbarxo'ja")

Encode known faces

encodeListKnown = findEncodings(images) print('Encodings Complete')

Start the camera

cap = cv2.VideoCapture(0)

while True: success, img = cap.read() imgS = cv2.resize(img, (0, 0), None, 0.25, 0.25) imgS = cv2.cvtColor(imgS, cv2.COLOR_BGR2RGB)

# Detect faces and encode them
facesCurFrame = face_recognition.face_locations(imgS)
encodesCurFrame = face_recognition.face_encodings(imgS, facesCurFrame)

# Compare faces and save to database
for encodeFace, faceLoc in zip(encodesCurFrame, facesCurFrame):
    matches = face_recognition.compare_faces(encodeListKnown, encodeFace)
    faceDis = face_recognition.face_distance(encodeListKnown, encodeFace)
    matchIndex = np.argmin(faceDis)

    if matches[matchIndex]:
        name = classNames[matchIndex].upper()
        print(name)

        save_image_path_to_db(name)
        markAttendance(name)

        y1, x2, y2, x1 = faceLoc
        y1, x2, y2, x1 = y1 * 4, x2 * 4, y2 * 4, x1 * 4
        cv2.rectangle(img, (x1, y1), (x2, y2), (0, 255, 0), 2)
        cv2.putText(img, name, (x1 + 6, y2 - 6), cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255), 2)

cv2.imshow('Webcam', img)

# 'q' tugmasi bosilsa, chiqish
if cv2.waitKey(1) & 0xFF == ord('q'):
    break

cap.release() cv2.destroyAllWindows() ushbu koddagi File "C:\Users\Saidakbar\Desktop\camera_loyiha\pythonProject.venv\lib\site-packages\face_recognition\api.py", line 121, in face_locations return [_trim_css_to_bounds(_rect_to_css(face), img.shape) for face in _raw_face_locations(img, number_of_times_to_upsample, model)] File "C:\Users\Saidakbar\Desktop\camera_loyiha\pythonProject.venv\lib\site-packages\face_recognition\api.py", line 105, in _raw_face_locations return face_detector(img, number_of_times_to_upsample) RuntimeError: Unsupported image type, must be 8bit gray or RGB image. ushbu hatolarni tog'irlab berilar

[Aanchal33Rana]

I am able to print the names on terminal but its not updated on the .csv and the .csv is not converting into excel...help pls

[SumitDhivar]

change this: rgb_small_frame = small_frame[:, :, ::-1] to rgb_small_frame = cv2.cvtColor(small_frame, cv2.COLOR_BGR2RGB)

numpy==1.26.3 opencv-python==4.9.0.80

thanks it's work for me