Sign language detection with Python and Scikit Learn | Landmark detection | Computer vision tutorial

[@ComputerVisionEngineer]

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[@jesussachez5468]

Hello from Mexico! I love your job, I did each step in the same way as you, and I had no difficulties, I really feel very grateful for the time you spent teaching us. Congratulations teacher! 👨‍🏫

[@ComputerVisionEngineer]

Thank you! So glad you enjoy the content! 😃🙌

[@ITRAiswaryaS]

Could you tell me the installation process

[@joque4]

For all who are getting errors like "inhomogeneous shapes" while training on big datasets take into account that the MP Hands processing not always return 42 features (sometimes it just doesn't predict the coordinates well enough). To avoid this situations always check the length of every array. You must have the same amount of images and labels, and the labels (landmark coordinates) should have the same shapes. Just remove the samples that doesn't return all the landmarks or doesn't work well with the Mediapipe hands solution, to ensure all the data has the same shape and to avoid these numpy errors (and bad models).

[@RAHUL-dt5xm]

can you help me. when I trained only one gesture nothing else, but the system detects untrained gestures as the trained gesture why? any idea

[@aryanrana-o6n]

can you please share the changed code

[@mohamedlhachimi2933]

i think guys to solve this problem we had to tell the collect data script to save just frames where he could detect our hands else we will store bad models that will ends with this getting errors like "inhomogeneous shapes" , i actually try to solved this problem by not moving my hand when collecting data and making my model else you can try this code to check your images that are stored This script will only print the paths of the images that are deleted due to no hands being detected. It won't display any image windows. ##########################################" import os import cv2 import mediapipe as mp def process_and_show(image_path, mp_drawing): mp_hands = mp.solutions.hands hands = mp_hands.Hands() # Read the image image = cv2.imread(image_path) image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) # Detect hands and landmarks results = hands.process(image_rgb) if not results.multi_hand_landmarks: print(f"Deleted image: {image_path}") # Delete the image with no hands detected os.remove(image_path) # Path to your data folder containing subfolders data_folder = "data" mp_drawing = mp.solutions.drawing_utils mp_drawing_styles = mp.solutions.drawing_styles # Iterate through subfolders for folder_name in os.listdir(data_folder): folder_path = os.path.join(data_folder, folder_name) if os.path.isdir(folder_path): print(f"Checking images in folder: {folder_name}") # Iterate through images in the folder for filename in os.listdir(folder_path): if filename.endswith(".jpg") or filename.endswith(".png"): image_path = os.path.join(folder_path, filename) process_and_show(image_path, mp_drawing)

[@pawnidixit1084]

I understood the problem but can't really put it in the program. could you explain it please?

[@clementdethoor5533]

Just add in create_dataset : if (len(data_aux) == 42): data.append(data_aux) labels.append(dir_)

[@shwetaevangeline]

Thank you so much, sir for this wonderful project. I've completed my term project easily with the help of your video. Loved how we can create our own data instead of getting it from somewhere else.

[@malesaketh8952]

Can u pls help me out? Please

[@aryanrana-o6n]

Really Thank you sir. Great Project you helped me a lot to learn many things. After multiple errors solving finally i succeeded in making full project.

[@ComputerVisionEngineer]

Glad the content is helpful! 😃🙌

[@thesoftwareguy2183]

Sir!! You have my respect I have really learned lots of things in your whole video . Just keep making this ML/DL Project videos , that you have done like implementing from scratch any exciting ML/DL project. Just Keep Going Sir!!! Thankyou So much!!✨✨✨✨✨✨❤❤❤❤❤❤

[@ComputerVisionEngineer]

Thank you for your support! 😃🙌💪

[@moMo-zu4ds]

Having trouble with my ML project now, but so happy to find your video. Thanks for all the work!!

[@vignesh.v4247]

The best tutorial ever!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

[@artiste9357]

Thanks a lot! I really appreciate keeping this under an hour as well :))

[@ivanvijandi2052]

Mas argentino imposible jsjs, Gran video!

[@sudarsonbharathwaaj1412]

Thanks a lot bro, I watched many videos and i wasted a lot of time and finally found your video and done my project.

[@ComputerVisionEngineer]

You are welcome! Glad it was helpful! 😃

[@RohanVector]

Please send your github link please

[@RohanVector]

I got lot of error bro please please please please

[@1hpxalphaop741]

srsly like the best video, now i can train my custom hand gestures etc. even, thank youu❤❤

[@paradisofernando97]

i love all that, you are very clearly and simply 😍😍

[@ComputerVisionEngineer]

Thank you! Glad you enjoyed it! 😃💪

[@mariamartinez4860]

why does it close when you put another hand?

[@LEDAT-AI]

Hello, I have watched your video and found it very informative. However, I was wondering if you could make a video for recognizing different characters for a sequence of movements, for example, the letter "J" or "Z." Thank you for your video.

[@ComputerVisionEngineer]

I will try to. 🙌

[@abdulbarisoylemez2817]

thank you my teacher, great a video , i tried it myself, I did it :)

[@ComputerVisionEngineer]

You are welcome! 😃 Glad you enjoyed it!! 🙂🙌

[@emnahamdi-wq4mz]

Hi! Great tutorial thank you. I have a question: does this program have data augmentation? and did u calculate the sensibility and accuracy of the program?

[@kane_jester]

sir , the projects get closed if more hands are placed in the real-time video , i know that randomforest classifier uses only certain features , is there a way so that the program doesnt close if more hands are in the video

[@Yousef_Osman2000]

how do i get that function 18:10 ?

[@hayatlr3000]

great tutorial so helpful for my pfe project i actually have to do hand recognition identification biometric only but the hand contour you explained so well the part "this is the most important thing" and I really need help when it comes to the approach of how i can solve this if it? is possible for you to help me by doing a video of it ?cause its the first time for me working with python i usually work with Matlab. thank you again for this video

[@ComputerVisionEngineer]

Hey Hayat, I am glad you found it helpful! 😄 Do you mean making a video about how to be strategic when starting a project and choose the most promising approach? Sure, I can do a video about problem solving strategies! 😃🙌

[@luongtranle2979]

Do you have file word report ?

[@sourabhchandra1740]

Hlo Sir, very nice video.... I also want to make a similar project ... But there will a bit difference.. I want to generate the entire subtitle for people who can't speak using their hand gestures during video conferencing in real time. Can you please guide me with the same ... Bcoz I completely a beginner. Your help will be appreciated. Thanks in advance. 😀

[@ComputerVisionEngineer]

Hey Sourabh, it sounds like a complex and very cool project! I would start by saving all the symbols you detect, its confidence score, and the duration of time you detect them so you can analyze this info later on. This is going to help you to understand the problem a little better and also it is going to help you to define rules in order to achieve your goal. 😃💪

[@Abhaykumar-bu7ei]

Hi Sourabh were you able to make it if yes could you please share some update or code for the same

[@000HASNAIN_AHMED]

Thank you sir for this video

[@RohanVector]

Some hand sign have two hand ,than what we can do that situation ?

[@fragileaf1778]

The camera crashes when I show more than one hand. Can you tell me how it can be fixed?

[@senpaihere6512]

hehe subscribed, tysm for this it was very helpful

[@saurabhmishra7487]

The app crashes when using both hands. How can I fix this?

[@touchwood8404]

The mediapipe library is giving error in installation what should I do?

[@fruitpnchsmuraiG]

did you figure it out?

[@MoominMoomin-f2b]

Hello!! Can you tell me which ML algorithm did you use in this?

[@arif-emre-yaman]

another great project

[@ComputerVisionEngineer]

Thank you, Arif! I am happy you enjoyed it. 😃🙌

[@nilayguler8397]

Thanks a lot! I really appreciate keeping this under an hour as well :)) We are trying to implement this model in Flutter to develop a mobile app. How can we create Flutter integration ?

[@UtsavKuntalwad]

Hello, i was adding new alphabets to the dataset and got this error , unable to solve : " File "D:\Major project\.Major Project\code\train_classifier.py", line 11, in data = np.asarray(data_dict['data']) ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (400,) + inhomogeneous part."

[@tvrtkokaurinovic7370]

did you fix this error?

[@raziehahmadi4185]

Thanks for your good tutorial How to act for the rest of the letters?

[@iinfinixvilla389]

Hola from India sir, Sir i enjoyed your video very much. sir, I have a small doubt can you tell me how to check and the accuracy of the model being trained.

[@martinsilungwe2725]

I have just subscribed, Currently working on a similar project, fingers crossed I'm at a right place..😂

[@ComputerVisionEngineer]

🤞😀 Good luck with your project, Martin! 🙌

[@martinsilungwe2725]

@@ComputerVisionEngineer Sir i have an error "ValueError: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2. ", what can be the problem, im trying to classfy all the alphabet letters, your help will be highly appreciated.

[@ประหยัดจันอังคาร-ฬ9จ]

Great Video

[@zeroboom4]

I have tried it with arabic Sign language,and it did not working correctly, I get one letter almost every time and it's wrong letter, any ideas that can help me train the model. I got the dataset from kaggle.

[@frankleonardoluquelineros9389]

Really great video tutorial! Why did you choose scikt learn and not Yolo? How many changes would you have to make to use Yolo?

[@ComputerVisionEngineer]

Do you mean using Yolo for object detection instead of mediapipe + Scikit learn? It can be done. You just need to train it. I did it with mediapipe + Scikit learn only for simplicity, and I think it also results in a more robust classifier. 🙌

[@szmasclips1774]

Great video but How do you do the collecting images part of the code?

[@abdallahsamir2707]

Hello, I have watched your video and found it very informative. However, I was wondering what is the limitation of this project?

[@ComputerVisionEngineer]

Hey, limitation in terms of possible symbols? I would say any static symbol made with only one hand.

[@vamsianurag3415]

Hi, while going through this code i'm getting model_dict = pickle.load(open('./model.p', 'rb')) FileNotFoundError: [Errno 2] No such file or directory: './model.p' and I didn't find any model.p file in your repository

[@ComputerVisionEngineer]

Hey, you can create the model yourself following the steps I describe in the video. 😃🙌

[@sandanuwan4441]

I am new to AI. I just want to know are we using Natural Language, Machine Learning and computer vision.

[@jeet611_]

life saver.

[@tihbohsyednap8644]

Hello sir, Kindly solve this error for me ----> ValueError: With n_samples=1, test_size=0.2 and train_size=0.8, the resulting train set will be empty. Adjust any of the aforementioned parameters.

[@ComputerVisionEngineer]

Hey, would you please copy paste the full description of the error you get?

[@AkshatManohar]

Hi, I am getting an error that ./data/.DS_Store is not a directory and is not found.

[@ComputerVisionEngineer]

Hey, what file / line triggers this error?

[@miladsayedi59]

can we make this project with pose detection models like openpose or deeppose? and what is the difference

[@makiizenin]

Hello sir, I got a one problem. I made the same with you and my code is worked but it only showed at least 5 mins for capturing then the camera will shutdown automatically and got some errors. :((((

[@NarutoTamilan007]

Sir what is your python version

[@livelife846]

Who can I add more sign because it's getting error when I try to add more signs

[@tihbohsyednap8644]

Sir kindly help me with this error . . ValueError: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2.

[@tihbohsyednap8644]

Sir kindly help me with this error. I am working on this project as my final year project and I have to extend it as my major project work.

[@mohamedlhachimi2933]

i think guys to solve this problem we had to tell the collect data script to save just frames where he could detect our hands else we will store bad models that will ends with this getting errors like "inhomogeneous shapes" , i actually try to solved this problem by not moving my hand when collecting data and making my model else you can try this code to check your images that are stored This script will only print the paths of the images that are deleted due to no hands being detected. It won't display any image windows. ##########################################" import os import cv2 import mediapipe as mp def process_and_show(image_path, mp_drawing): mp_hands = mp.solutions.hands hands = mp_hands.Hands() # Read the image image = cv2.imread(image_path) image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) # Detect hands and landmarks results = hands.process(image_rgb) if not results.multi_hand_landmarks: print(f"Deleted image: {image_path}") # Delete the image with no hands detected os.remove(image_path) # Path to your data folder containing subfolders data_folder = "data" mp_drawing = mp.solutions.drawing_utils mp_drawing_styles = mp.solutions.drawing_styles # Iterate through subfolders for folder_name in os.listdir(data_folder): folder_path = os.path.join(data_folder, folder_name) if os.path.isdir(folder_path): print(f"Checking images in folder: {folder_name}") # Iterate through images in the folder for filename in os.listdir(folder_path): if filename.endswith(".jpg") or filename.endswith(".png"): image_path = os.path.join(folder_path, filename) process_and_show(image_path, mp_drawing)

[@Oof_the_gamer]

what si the data.pickle?

[@kiranmahapatra8716]

Sir please help............during training it shows value error..data = np.asarray(data_dict['data']) ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (199,) + inhomogeneous part......for 3 class

[@SohamKaranjkar]

i got the same error, were you able to solve it?

[@krzysztofgalek5276]

Did u solve it?

[@e2mnaturals442]

i was able to sort it using padding if you want me to explain more, i will be glad to

[@Elenas1178]

@@e2mnaturals442 please explain

[@preetirathod5244]

​@@e2mnaturals442can u please explain it

[@travisfernandes5387]

how to make this project on web based like on react or flask

[@locphan1221]

thanks

[@hamzak2883]

First of all i want to thank you for this tutorial. I want actually to make a program for sign language but i am confused about the Dataset and how to process the Data which i will maybe get as Videos or Images. can you maybe give me some advice.

[@ComputerVisionEngineer]

Sure. Do you think you can take an approach as I do in the video?

[@harshasshet6755]

I am getting plots for every data set size which i have taken is it fine bcs i have plt.savefig function, annotated it so that the plt for every dataset size is saved in main data directory

[@prathamupadhyay1265]

How can I get accuracy for the letters predicted? Basically I want live accuracy for the letters that are predicted , since if you show any random hand gesture it will always predict some random letter, so it will be much better if you could also show live accuracy .Is it possible can u guide me a little bit through this?

[@ComputerVisionEngineer]

Try using the method 'predict_proba' instead of 'predict'. You wil get a probability vector for all the classes. Taking the largest number will give you the confidence value you are looking for. 💪💪

[@prathamupadhyay1265]

@@ComputerVisionEngineer Thanks a lot you are amazing !!! 😃

[@yashanchule9641]

@@prathamupadhyay1265 bhai if u dont mind kya app apke code ki zip file mujhe share kar skte hai, coz im getting many errors and i have tried many steps but kuch ho nahi raha hai. PLZ!!!!!!

[@yashanchule9641]

plz bhai

[@054_vishwadhimar4]

@@yashanchule9641 GitHub link is there..or have you tried that too?!

[@darrellardhanihidayat555]

Hi sir, i got some error at inference_classifier.py, the errors says: Line 36, in H, W, _= frame.shape AttributeError: ‘NoneType’ object has no attribute ‘shape’ Thank you for the help🙏🏻

[@RohanVector]

It's fully working for you now? Because I cannot able to run the first step please help mee

[@RohanVector]

In collect_img is cv2.imshow(frame) is error bro kindly help me

[@RohanVector]

Error name :size.width>0 && size.height>0 in function 'cv::imshow'

[@manasayjoseph1075]

can you please show the err @@RohanVector

[@saivaraprasadmandala8558]

Change the line to -> cap = cv2.VideoCapture(0)... Previously it was -> cap = cv2.VideoCapture(2)@@RohanVector

[@Om-id1qr]

Great tutorial! Can you tell me how can I do this for Indian Sign Language which uses 2 hands?

[@ComputerVisionEngineer]

I am looking at the Indian sign language alphabet and I see some characters are done with 2 hands and others with 1 hand. In order to do something based on landmarks as we did on this video you would have to train 2 classifiers, one of them taking as input the landmarks of one hand only (as we did on the video) and the other classifier taking as input the landmarks of both hands. Then some logic to apply one classifier or the other one depending on how many hands appear on the frame. Or, you can just follow a different approach and train an image classifier taking the crop of the hand/s. 💪🙌

[@v5j7bxb]

Hi ! Have you completed working on this project? Did it worked ?

[@mahmudsherbhai2325]

hi I am a 15 year old and i want to do this for my school tech convention. What program are you using to code this

[@ranjanadevi7965]

Hello while executing your codes when i was keeping the number of objects grater than 4 thn trainclassifier was unable to generate model.p file in my device can you help me out to solve this issue

[@jonrexzelvalloyas6294]

great project! may i ask what algorithm is used in your sign language?

[@ComputerVisionEngineer]

Hey, thank you! I am using mediapipe as a hand detector and landmark detector and a Random Forest classifier as sign classifier. 🙌

[@arptv4962]

Hello ! Thank you for the porject. Is anybody knows how to fix this error: H, W, _ = frame.shape AttributeError: 'NoneType' object has no attribute 'shape'. I have done all the steps before until the last program, however, it looks like it doesn't see images or something? have anybody had the same problem?

[@ahamedkhalifa8377]

change VideoCapture(2) -> VideoCapture(0)

[@dinem0023]

in all hand gesture im getting only L what could be the reason can anyone tell me

[@sivaips680]

model p file is missed on the folder

[@adn4779]

@ComputerVisionEngineer ValueError: X has 84 features, but RandomForestClassifier is expecting 42 features as input..I am getting this error when i run the inference_clasifier.py model...What change should i make in the code.....

[@shwetaevangeline]

If you're getting this, that means you're showing something else that isn't in the data. Only show what you've captured. Or else simply increase number of classes and take different pictures from different angles.

[@mohamedlhachimi2933]

i think guys to solve this problem we had to tell the collect data script to save just frames where he could detect our hands else we will store bad models that will ends with this getting errors like "inhomogeneous shapes" , i actually try to solved this problem by not moving my hand when collecting data and making my model else you can try this code to check your images that are stored This script will only print the paths of the images that are deleted due to no hands being detected. It won't display any image windows. ##########################################" import os import cv2 import mediapipe as mp def process_and_show(image_path, mp_drawing): mp_hands = mp.solutions.hands hands = mp_hands.Hands() # Read the image image = cv2.imread(image_path) image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) # Detect hands and landmarks results = hands.process(image_rgb) if not results.multi_hand_landmarks: print(f"Deleted image: {image_path}") # Delete the image with no hands detected os.remove(image_path) # Path to your data folder containing subfolders data_folder = "data" mp_drawing = mp.solutions.drawing_utils mp_drawing_styles = mp.solutions.drawing_styles # Iterate through subfolders for folder_name in os.listdir(data_folder): folder_path = os.path.join(data_folder, folder_name) if os.path.isdir(folder_path): print(f"Checking images in folder: {folder_name}") # Iterate through images in the folder for filename in os.listdir(folder_path): if filename.endswith(".jpg") or filename.endswith(".png"): image_path = os.path.join(folder_path, filename) process_and_show(image_path, mp_drawing)

[@luciferani8279]

Do not give 2 hands at the same on your camera

[@CanalIFES]

why do you use and random forest classifier algorithm? maybe it is better for it? could i try with a pretrained model to get better results?

[@ComputerVisionEngineer]

No particular reason why I used a Random Forest, I think pretty much any other classifier would have a similar performance in this case.

[@CanalIFES]

@@ComputerVisionEngineer Thanks felipe!!

[@essiebx]

doesnt this work when you use labeled dataset

[@MEGHAJJADHAV]

How can we make a confusion matrix for the model that was made?

[@e2mnaturals442]

hi were you able to solve this? i used import matplotlib.pyplot as plt import seaborn as sns # class names class_names = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O', 'P', 'Q', 'R', 'S', 'T', 'U', 'V', 'W', 'X', 'Y', 'Z'] # Plot the confusion matrix plt.figure(figsize=(15, 15)) sns.heatmap(conf_matrix, annot=True, fmt='d', cmap='Blues', xticklabels=class_names, yticklabels=class_names) plt.title('Confusion Matrix') plt.xlabel('Predicted') plt.ylabel('True') plt.show()

[@NourashAzmineChowdhury]

Sir i am getting this error: [ERROR:0@0.045] global obsensor_uvc_stream_channel.cpp:156 cv::obsensor::getStreamChannelGroup Camera index out of range Traceback (most recent call last): File "D:\sign-language-detector-python-master\collect_imgs.py", line 25, in cv2.imshow('frame', frame) cv2.error: OpenCV(4.7.0) D:\a\opencv-python\opencv-python\opencv\modules\highgui\src\window.cpp:971: error: (-215:Assertion failed) size.width>0 && size.height>0 in function 'cv::imshow' while running collect_imgs.py can you help solve it. can provide me the model or data set you have used . it will be help for me

[@ComputerVisionEngineer]

Try this: go to line 13 and change it by 'cap = cv2.VideoCapture(0)'.

[@mdemike1781]

If you train it in a specific place ex: your bedroom would this work like with the background of your kitchen or different place?

[@ComputerVisionEngineer]

Yes, by the way we are doing it in this tutorial, it should work if you change the background. 🙌

[@mohamedlhachimi2933]

@@ComputerVisionEngineer i think guys to solve this problem we had to tell the collect data script to save just frames where he could detect our hands else we will store bad models that will ends with this getting errors like "inhomogeneous shapes" , i actually try to solved this problem by not moving my hand when collecting data and making my model else you can try this code to check your images that are stored This script will only print the paths of the images that are deleted due to no hands being detected. It won't display any image windows. ##########################################" import os import cv2 import mediapipe as mp def process_and_show(image_path, mp_drawing): mp_hands = mp.solutions.hands hands = mp_hands.Hands() # Read the image image = cv2.imread(image_path) image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) # Detect hands and landmarks results = hands.process(image_rgb) if not results.multi_hand_landmarks: print(f"Deleted image: {image_path}") # Delete the image with no hands detected os.remove(image_path) # Path to your data folder containing subfolders data_folder = "data" mp_drawing = mp.solutions.drawing_utils mp_drawing_styles = mp.solutions.drawing_styles # Iterate through subfolders for folder_name in os.listdir(data_folder): folder_path = os.path.join(data_folder, folder_name) if os.path.isdir(folder_path): print(f"Checking images in folder: {folder_name}") # Iterate through images in the folder for filename in os.listdir(folder_path): if filename.endswith(".jpg") or filename.endswith(".png"): image_path = os.path.join(folder_path, filename) process_and_show(image_path, mp_drawing)

[@itzbumblebee6694]

do you have research paper of this project?

[@ComputerVisionEngineer]

Hi, no, I do not. 🙌

[@pawanrajbhar6377]

data = np.asarray(data_dict["data"]) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (296,) + inhomogeneous part. can u help me where i going wrong ?

[@foru1854]

bro did you corrected the error pls can you tell me how you did it??

[@saivaraprasadmandala8558]

For those who faces the error where it can't convert the 'data' values from dictionary data_dict, just make sure that in photo samples you are giving the full hand because if not, there will be inconsistent data and the lists will not have the same lenght inside the data_dict['data']. Do again the photos retrieve part and all should be fine

[@saivaraprasadmandala8558]

For those who faces the error where it can't convert the 'data' values from dictionary data_dict, just make sure that in photo samples you are giving the full hand because if not, there will be inconsistent data and the lists will not have the same lenght inside the data_dict['data']. Do again the photos retrieve part and all should be fine@@foru1854

[@lolalikee]

Can the project created by exported to an .exe? Im worried because of the pickle file.

[@saivaraprasadmandala8558]

Error: Traceback (most recent call last): File "h:\Mini Project\Mallikarjun Project\sign-language-detector-python-master\sign-language-detector-python-master\inference_classifier.py", line 7, in model_dict = pickle.load(open('./model.p', 'rb')) ^^^^^^^^^^^^^^^^^^^^^^^ FileNotFoundError: [Errno 2] No such file or directory: './model.p' Could u help me out in fixing this error sir!!!!.

[@maanyerewalter9748]

Am from Ghana

[@harshasshet6755]

I am facing wierd problem actually i have altered your project for all 26 alphabets but whatever I show I am getting wrong alphabets

[@luciferani8279]

What is your error?

[@abhikpanda1581]

The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2. The above error is coming . Can anybody pls help me out?

[@ArjunSharma-ix1gk]

did you solve it?

[@Envyro1]

when you crop the image to just show the sign does that mean anyone can sign the alphabet and it will show what sign they are doing?

[@ComputerVisionEngineer]

Once the model is trained, anyone can sign the alphabet and it will show what sign they are doing.

[@Pommesperfektion]

is anywhere your dataset online?

[@ComputerVisionEngineer]

Hey, the dataset I used in this tutorial is not available. But you can create your own dataset following the steps I provide in the video. 😃🙌

[@tharas3368]

Can i get the document of this peoject please 🙏it's my humble request please

[@ocelottes]

Very cool, i have a question. How can i test de accuracy of the detection?

[@ComputerVisionEngineer]

Do you mean the accuracy of the hand detection?

[@ocelottes]

@@ComputerVisionEngineer yes

[@ComputerVisionEngineer]

@@ocelottes it is mediapipe hand detection, if you want to test it's accuracy you would need to take another hand detector to compare mediapipe detections against

[@caio_pohlmann]

How could you make the project recognize two hands?

[@ComputerVisionEngineer]

Hey, take a look at our discord server, a member of our community has shared the code to train using 2 hands 💪🙌

[@LincolinARanee]

@@ComputerVisionEngineer Kindly share your discord server

[@MateResuelve18]

Is the program you are using called pycharm?

[@ComputerVisionEngineer]

Yes. 🙌

[@Swathi-oo2be]

ValueError: X has 84 features, but RandomForestClassifier is expecting 42 features as input. ???? Please help me

[@martinsilungwe2725]

Did you get any solutions for the error??

[@ad-0307]

Hello! If you have found a solution to this error, would you mind assisting me with it as well?

[@SriramK-eq6sq]

Just add an "if" condition in the interference classifier.py file before detecting. if len(data_aux) == 42: # Adjust this number based on the expected features prediction1 = model2.predict([np.asarray(data_aux)]) print("Predicted Value (Model 1):", prediction1[0]) predicted_character1 = labels_dict[int(prediction1[0])] cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 0, 0), 4) cv2.putText(frame, predicted_character1, (x1, y1 - 10), cv2.FONT_HERSHEY_SIMPLEX, 1.3, (0, 0, 0), 3, cv2.LINE_AA)@@ad-0307

[@michaenrangelgiraldo5428]

Hello, thank u for tutorial, that was amazing but i have an error when y run the classifier: ValueError: X has 42 features, but RandomForestClassifier is expecting 84 features as input. how can i fix that error?

[@uzairkabeer]

@michaenrangelgiraldo5428 Okay so, I'm assuming that you are getting this error when predicting for that I just put an if condition like: if (len(data_aux) != 84) And with in that if condition I predict the values. I myself don't know whats causing this error but my assumption is it has something to do with the both left and right hand landmarks (42+42=84). Nevertheless, this solves this issue hope it will help you too.

[@alexday4949]

Can you try this code: desired_length = 4200 # Pad data_aux with zeros to achieve the desired length while len(data_aux) < desired_length: data_aux.extend([0.0, 0.0]) # Truncate data_aux if it exceeds the desired length data_aux = data_aux[:desired_length]

[@mohamedlhachimi2933]

i think guys to solve this problem we had to tell the collect data script to save just frames where he could detect our hands else we will store bad models that will ends with this getting errors like "inhomogeneous shapes" , i actually try to solved this problem by not moving my hand when collecting data and making my model else you can try this code to check your images that are stored This script will only print the paths of the images that are deleted due to no hands being detected. It won't display any image windows. ##########################################" import os import cv2 import mediapipe as mp def process_and_show(image_path, mp_drawing): mp_hands = mp.solutions.hands hands = mp_hands.Hands() # Read the image image = cv2.imread(image_path) image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) # Detect hands and landmarks results = hands.process(image_rgb) if not results.multi_hand_landmarks: print(f"Deleted image: {image_path}") # Delete the image with no hands detected os.remove(image_path) # Path to your data folder containing subfolders data_folder = "data" mp_drawing = mp.solutions.drawing_utils mp_drawing_styles = mp.solutions.drawing_styles # Iterate through subfolders for folder_name in os.listdir(data_folder): folder_path = os.path.join(data_folder, folder_name) if os.path.isdir(folder_path): print(f"Checking images in folder: {folder_name}") # Iterate through images in the folder for filename in os.listdir(folder_path): if filename.endswith(".jpg") or filename.endswith(".png"): image_path = os.path.join(folder_path, filename) process_and_show(image_path, mp_drawing)

[@AnupamMoharana]

Expected 84 features, but got 42 This error pops up every time

[@ComputerVisionEngineer]

Hey Anupam, seems like you are training the classifier with twice the features as you use in inference. Are you training the classifier using gestures from one hand only?

[@AnupamMoharana]

@@ComputerVisionEngineer Yeah I used 1 hand only i will try with both

[@ashokreddy6602]

i'm getting same error how to resolve it and i used one hand only

[@pirson910]

@@ashokreddy6602 u probably had to collect again the images

[@rajsingh8495]

can we make an android app for this???

[@sherwingeorge6959]

What python version have you used in this project?

[@ComputerVisionEngineer]

Python 3.7 if not mistaken

[@akihitonarihisago4276]

has anyone tried to implement this for more than 20 classes?

[@franciscolopez7830]

chilean spanish?? good tutorial

[@ComputerVisionEngineer]

Hi, thank you! My home country is Uruguay. 🙌

[@sageloveswipha]

Hello please I need help, I have a question

[@oterotube13]

help!: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (7960,) + inhomogeneous part. Need to something to remove the bad part from the pickle file.

[@OsazeOgedegbe]

hello I am having the same problem. Could be share your solution if you find one. Thank you!

[@mohamedlhachimi2933]

i think guys to solve this problem we had to tell the collect data script to save just frames where he could detect our hands else we will store bad models that will ends with this getting errors like "inhomogeneous shapes" , i actually try to solved this problem by not moving my hand when collecting data and making my model else you can try this code to check your images that are stored This script will only print the paths of the images that are deleted due to no hands being detected. It won't display any image windows. ##########################################" import os import cv2 import mediapipe as mp def process_and_show(image_path, mp_drawing): mp_hands = mp.solutions.hands hands = mp_hands.Hands() # Read the image image = cv2.imread(image_path) image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) # Detect hands and landmarks results = hands.process(image_rgb) if not results.multi_hand_landmarks: print(f"Deleted image: {image_path}") # Delete the image with no hands detected os.remove(image_path) # Path to your data folder containing subfolders data_folder = "data" mp_drawing = mp.solutions.drawing_utils mp_drawing_styles = mp.solutions.drawing_styles # Iterate through subfolders for folder_name in os.listdir(data_folder): folder_path = os.path.join(data_folder, folder_name) if os.path.isdir(folder_path): print(f"Checking images in folder: {folder_name}") # Iterate through images in the folder for filename in os.listdir(folder_path): if filename.endswith(".jpg") or filename.endswith(".png"): image_path = os.path.join(folder_path, filename) process_and_show(image_path, mp_drawing)

[@ahanatola6522]

Can anybody please tell using this same process can we create it for all 26 alphabet

[@TheDreamsandTears]

did you get it?

[@nitishsaini63]

raise ValueError( ValueError: The least populated class in y has only 1 member, which is too few. The minimum number of groups for any class cannot be less than 2. please any can resolve this error

[@ArjunSharma-ix1gk]

did you solve it?

[@MarkEugeneDulay-oi5iu]

how many classes or folders of data can i do with this?

[@ComputerVisionEngineer]

Potentially, there is no limit with the number of categories you can train your classifier in.

[@MarkEugeneDulay-oi5iu]

@@ComputerVisionEngineer i'm having an error that says ValueError: X has 84 features, but RandomForestClassifier is expecting 42 features as input" do you have any fix for this? im sorry, chatgpt aint helpful enough

[@ROHANKUMAR_]

sir,can you please provide all image as used in this project

[@ComputerVisionEngineer]

Hey Rohan, in this video I used my webcam to collect images, I show you the process in the 'data collection' chapter. You can collect the images yourself for your project following the same approach! 😃🙌

[@rutujakothale3829]

i'm getting this error, please help Traceback (most recent call last): File "d:\sign lang\testing.py", line 27, in H, W, _ = frame.shape AttributeError: 'NoneType' object has no attribute 'shape' INFO: Created TensorFlow Lite XNNPACK delegate for CPU.

[@rentaroiino1789]

were you able to find a solution to your problem?

[@legion4924]

Hello sir, in this project can uses for 2 hands?

[@ComputerVisionEngineer]

Hey, yeah sure the project can be adapted for 2 hands. 🙌

[@legion4924]

@@ComputerVisionEngineer okay sir thank u🙏

[@УльянаМедведева-б5и]

Hello everyone, please tell me, maybe someone knows why when you run the test you get this error: "ValueError: X has 84 features, but RandomForestClassifier is expecting 42 features as input". how can i fix this? Thanks in advance for the answer!

[@fruitpnchsmuraiG]

hey did it work then?

[@УльянаМедведева-б5и]

​@@fruitpnchsmuraiG Yes, the program starts, detects the gesture, but after a minute it shuts down and gives the above error

[@mohamedlhachimi2933]

i think guys to solve this problem we had to tell the collect data script to save just frames where he could detect our hands else we will store bad models that will ends with this getting errors like "inhomogeneous shapes" , i actually try to solved this problem by not moving my hand when collecting data and making my model else you can try this code to check your images that are stored This script will only print the paths of the images that are deleted due to no hands being detected. It won't display any image windows. ##########################################" import os import cv2 import mediapipe as mp def process_and_show(image_path, mp_drawing): mp_hands = mp.solutions.hands hands = mp_hands.Hands() # Read the image image = cv2.imread(image_path) image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) # Detect hands and landmarks results = hands.process(image_rgb) if not results.multi_hand_landmarks: print(f"Deleted image: {image_path}") # Delete the image with no hands detected os.remove(image_path) # Path to your data folder containing subfolders data_folder = "data" mp_drawing = mp.solutions.drawing_utils mp_drawing_styles = mp.solutions.drawing_styles # Iterate through subfolders for folder_name in os.listdir(data_folder): folder_path = os.path.join(data_folder, folder_name) if os.path.isdir(folder_path): print(f"Checking images in folder: {folder_name}") # Iterate through images in the folder for filename in os.listdir(folder_path): if filename.endswith(".jpg") or filename.endswith(".png"): image_path = os.path.join(folder_path, filename) process_and_show(image_path, mp_drawing)

[@RaviRavi-wq8pv]

Sir in collect data..camera is not opening..🥺

[@ComputerVisionEngineer]

You may need to change the camera id. Try changing the line 13 to cap = cv2.VideoCapture(0).

[@manhimself4560]

cv2.VideoCapture(0) is for main camera and (2) is for alternative camera