the most no-nonsense straight to the point video on resnet video, keep up the good work!
@literacy_012 жыл бұрын
Great Resource. As the rookie in the Machine Learning field, this is really practical exercise for the one who wants to integrate ResNet (Not only this, but also other model as he mentions in here) model to the Sequential layers.
@prathyushaa83263 жыл бұрын
I've been trying to implement resnet for days, finally this has helped me. Thank you so much :)
@milafii73472 жыл бұрын
Do you know how to get an output or repreaentation of the extracted features?
@matildabich6603 ай бұрын
bro i learned this for 1 semester and you just explained it in 10 minutes....and i understand it. how
@fabiofiestas85832 жыл бұрын
Thank you very much, I've trying to implement ResNet for a long time, this video really helped me. Please upload more videos :)
@keithwetton19379 ай бұрын
Thanks for this, it was very helpful. I just had to change the import lines to deal with a newer version of keras.
@josemariovalenciahenao15302 жыл бұрын
Thanks to this video I discovered your amazing channel! Thank you Nachiketa, You are the man! Thanks a lot for all your efforts, trully appreciated from the other side of the world. Please keep this amazing job, God bless you my friend.
@NachiketaHebbar2 жыл бұрын
Means a lot, thanks!
@alexisbaladon798 Жыл бұрын
Thank you so much for the content! This really helped me understand how to fine-tune a model in one of my projects :)
@mikilmku1554 Жыл бұрын
Hi, how can I save the model? When I do resnet_model.save('name_model.h5') it gives me an error. I searched information about it but I do not know how to solve It. The error is: Layer ModuleWrapper was created by passing non-serializable argument values in `__init__()`, and therefore the layer must override `get_config()` in order to be serializable. Please implement `get_config()`.
@herberthipolito9941 Жыл бұрын
Thanks for the video!! It was really handy for my project!!
@shariqueansari99212 жыл бұрын
Thanks Bhai kafi din se pareshan tha me Resnet ko le kr
@Liz_871 Жыл бұрын
Hey, great video, thank you very much for the explanation and material. I needed to put the loss function to "sparse_categorical_crossentropy" because otherwise it said shape value error.
@sahilsharma7501 Жыл бұрын
Exactly, I just came here to comment on this, but you already did 😆
@OleksiiLysenko-b2w Жыл бұрын
Thanks a lot for your advice! You saved me!
@mums2109 Жыл бұрын
Thank you for this! Wonderful explanation
@adibamaniyar741 Жыл бұрын
Your teaching is very good👍
@harvardyard793 жыл бұрын
I'm confused why there is only training and validation. Why is there not also a testing dataset? Isn't validation data used to optimize hyperparameters only? It seems you're using the validation data to evaluate accuracy. Is this normal?
@milinduprabhash12162 ай бұрын
Thank you Bro that's very useful
@rahulvansh23903 жыл бұрын
A suggestion: There are very less opportunities for Machine learning engineer, data scientist, deep Learning engineer, ai engineer even though it's highly demanded. I highly recommend to focus on opening of such roles in good companies/ startups. Every youtube focusing on software engineering or sde roles openings, please give priority to such roles as well. Also please share interview experience of people who got such roles as a FRESHERS in good companies on campus or off campus. Thank you 😊🙏🏻
@maaleem90 Жыл бұрын
Brother iam very displeased with you. What kind of explanation is that. Who does that. How can your explanation be so easy to understand. Iam displeased coz why didn't I see your videos till this time. But now iam happy that i got someone who explains like others understand. Congrats for a new subscriber.
@NachiketaHebbar Жыл бұрын
You had me in the first half :)
@maaleem90 Жыл бұрын
@@NachiketaHebbar brother, that's a style of talk I adopted if I want someone not just to listen to me but also reply. brother again, thanks for your knowledge sharing .
@vikneshrajan58302 жыл бұрын
I'm getting an error saying "This model has not yet been built. Build the model first by calling `build()` or calling `fit()` with some data, or specify an `input_shape` argument in the first layer(s) for automatic build." what should I do?
@rajashehryar20028 ай бұрын
You got a subscriber buddy. Very well....
@EliseGreen-tz2qe2 ай бұрын
Thank you awesome video very helpful!
@321-youvrajsinghgaur3 Жыл бұрын
Plz Plz plz tell how to save this model in .h5 format!!!!!!!
@taha_acoustica16004 ай бұрын
this was so helpful, thank you so much!
@RAHULAGRAWAL-zo4iy5 ай бұрын
@NachiketaHebbar Hello, I found the error in this line, please do the needful asap. history = resnet_model.fit( train_ds, validation_data=val_ds, epochs=20 ) Error: ValueError: Shapes (None, 1) and (None, 5) are incompatible
@marcospallone45152 жыл бұрын
Easy and effective! Top!
@mahdifarhadi7982 жыл бұрын
Thank you , Can you write a code in keras.application and the weights aren't 'imagenet' ?
@ahmetberkay93363 ай бұрын
hello my friend. i am planning to use resnet50 for my project. basically the project is about birads classification. i have dataset which has around 3000 images and 3 classes (birads2, birads4, birads5). i want this model to classify the mammography pictures as birads classification. i tried to fine tune this model but it didn't really work. do you have any suggestions or hints for me to tune this model for such a detailed and complicated birads classification?
@saisingireddy23593 ай бұрын
Same case brother I used efficientnetb3 for hand gesture classification but its initial accuracy is around 20 and rising so slowly any suggestions 😢?
@Paattiil3 жыл бұрын
hi make a video on anamoly detection. using python on time series data. to detect node tampering
@danielsw70112 жыл бұрын
I would like to ask a question. When you split the data into training and validation. Why did you split it into 2 different parts, it makes me think that there's a chance that there are the same images in both training and validation, which makes the result higher than it's should be. Usually, people use the 'split folders' and 'split validation test set' and it's confirmed that there will be no double images that will affect the result of the models.
@normalhuman62602 жыл бұрын
the seed value makes sure that a certain pattern is used to select validation and training data
@adib10322 жыл бұрын
Thanks for the content!
@harishgoud36282 жыл бұрын
my network is starting with 43% accuracy in epoch unlike 70% which is in ur code , any idea why so but model is able to learning and val acuracy is at 40/50 range
@morffisTFT3 жыл бұрын
Mr Hebbar, your content is amazing! Please continue with the great work!
@NachiketaHebbar3 жыл бұрын
Thanks a lot!
@clotildamariamathias74162 жыл бұрын
I want to implement with Xception..... What changes should be done
@mishkathossain298411 ай бұрын
Vaya why didn't you applied anything on testing?? How much the model works on testing dataset??
@DrShaziaSaqib2 жыл бұрын
thank you awesome, God bless you
@ahmedhope2 жыл бұрын
i'm using the same code and the same dataset as yours but i get this error plz help NameError Traceback (most recent call last) in () 2 history = resnet_model.fit( 3 train_ds, ----> 4 validation_data=val_ds, 5 epochs=epochs) NameError: name 'val_ds' is not defined
@ishita5132 Жыл бұрын
It's a name error. You must have done something wrong in naming, maybe capitalised a letter or something while writing val_ds at the two places.. Check on that once
@MUHAMMADALI-qk9xs Жыл бұрын
Hi, can you help me with what changes in the above code I should do if I have two classes malicious and non_malicious and a dataset of GRAYSCALE images?
@waqasmazhar12602 жыл бұрын
Fab explanation✌
@computer_vision Жыл бұрын
lets test your knowledge :) 1.is it possible to use transfer learning on VIT(vision transformer model ) ? 2. suppose I trained a mobilenetv2 model , now I want to use this pre-train weights on vgg16 model for transfer learning is it possible to do so .? if not explain why ?
@sagnikdutta72066 ай бұрын
Question: Why do you need Flatten() even though the last layer of Resnet50 is a GlobalAverage layer?
@rutwikmore74626 ай бұрын
exactly I have also same doubt
@compmaestro2 жыл бұрын
Hi, thanks for this wonderful video. Can you please explain how can we use some data for test purpose (like you divided dataset into training and validation data) to evaluate the model's performance. Thanks
@riyaarora2384 Жыл бұрын
J0
@achininisansala5124 Жыл бұрын
please tell me how to get ROC curve when I implement my code in this pattern without doin train test split
@hiahpsasmlte75552 жыл бұрын
is there a way to save my progress on training ? has anyone tried it with this architecture? and great video!
@nathanmcnaughton4468 Жыл бұрын
I have a dataframe with each row as an image and the columns as the pixels, would that be the same?
@MG-tc5bo Жыл бұрын
When I try this with other datasets I get "Shapes (None, 1) and (None, 4) are incompatible"
@jujuvil70132 жыл бұрын
Hi bro i couldn't download resnet50 in pycharm since it is asking for old version of python . What should i do
@ganesha42812 жыл бұрын
how we can use the transfer learning model for time series IMU Sensor data?
@vivekrajeevv71644 ай бұрын
Can you give the test accuracy
@lauris21325 ай бұрын
Thank you!
@kapedalex1996 Жыл бұрын
Keras wants you to use sparse_categorical_crossentropy. Otherwise there will be errors today
@nourelislamzouar2490 Жыл бұрын
I was unable to make his code work until I saw your comment, thank you so much man!
@vedachintha11 ай бұрын
It is very important to understand the data you are using before choosing the components of your neural network. The code in the video is correct since it utilizes label_mode="categorical" in conjunction with the categorical cross-entropy loss function. If you intend to use the sparse_categorical_cross_entropy loss function, you must specify label_mode="int". This is especially important because it appears that the data used in the video may not be identical to the data available to us (I did not verify this). The categorical cross-entropy loss function requires one-hot encoding for each class. For example, if there are three classes, A, B, and C, this loss function will work only if the class labels are encoded as [1, 0, 0], [0, 1, 0], and [0, 0, 1], respectively. This encoding is achieved by using the label_mode="categorical" argument. On the other hand, sparse_categorical_cross_entropy does not require such encoding and assigns integers (e.g., 1, 2, 3) to classes A, B, and C. This loss function is preferable when dealing with a large number of classes, such as in predicting words in a vocabulary, as it conserves memory resources A comprehensive introduction to loss functions can be found here: machinelearningmastery.com/how-to-choose-loss-functions-when-training-deep-learning-neural-networks/
@chaymaebenhammacht1618 Жыл бұрын
Hello thaank u so much for this model but its not working on mu own dataset i dont know why exactly
@feignedganger Жыл бұрын
Is it possible to load zip file from local file explorer ? I am getting error no file found.
@ayeshakhatun3114 Жыл бұрын
please help me ...i have followed the same code but getting error at the fit function... it shows " ValueError: Shapes (None, 3) and (None, 4) are incompatible"
@AkshayRakate Жыл бұрын
Make sure you are using a number of neurons in softmax layer = number of categories
@shivammaheshwari15982 жыл бұрын
Nachiketa, from where we can download pretrained weights ?
@soroveakterkakon91652 жыл бұрын
How can i implemented confusion matrix in this code?plz help me
@DivyasriJampana Жыл бұрын
can u post how to plot confusion matrix for this code
@hiluu4 ай бұрын
Hi, i have a question. In the video at 8:25, you said it slightly overfitting. Can you help me what to do to resolve the overfitting problem? I have the same issue like in the video? I'm new to this, hope you help me. Thanks!
@saisingireddy23593 ай бұрын
Try to add dropout and batch normalization and you can even try l2 and l1 regularizers too😊
@AswathyG-wt3rq5 ай бұрын
which version of TenssorFlow are you using here?
@shreearmygirl98782 жыл бұрын
Hi, Hebbar pl can u send th videos for creating our own dataset using satellite images fro classification
@seme_K Жыл бұрын
Please do a video on Densenet-121
@vyas81373 жыл бұрын
Bro could you make a video on 'complete roadmap for becoming computer vision engineer'?
@NachiketaHebbar3 жыл бұрын
Will try to make one on it soon
@abhishekagarwal7752 Жыл бұрын
code is not working. ( ValueError: Shapes (None, 1) and (None, 5) are incompatible)
I corrected the below error , The code in blog and in video are different , I corrected code according video and it is working , but one error is getting below code snippet.. can you reslove the error import matplotlib.pyplot as plt plt.figure(figsize=(10, 10)) for images, labels in train_ds.take(1): for i in range(6): ax = plt.subplot(3, 3, i + 1) plt.imshow(images[i].numpy().astype("uint8")) plt.title(class_names[labels[i]]) plt.axis("off")
@NachiketaHebbar3 жыл бұрын
What error are you getting in this
@sejalloya99 Жыл бұрын
need help with the confusion matrix!
@顏劭宇-j6v2 жыл бұрын
thanks❤
@syedzoofa87112 жыл бұрын
It's showing me the error at resnet_model.add(pretrained_model)
@anirudhbmitta65972 жыл бұрын
How to use two transfer learning models on a single model
@varungupta41262 жыл бұрын
Hey how I can add my own custom dataset in this code
@anthonieschaap162510 ай бұрын
The code has error: "ValueError: Shapes (None, 1) and (None, 5) are incompatible"
@anthonieschaap162510 ай бұрын
I fixed it with using "label_mode='categorical'," in he val_ds and trains_ds. Then got error "only integer scalar arrays can be converted to a scalar index" but could be solved by using: plt.figure(figsize=(10, 10)) for images, labels in train_ds.take(1): for i in range(6): ax = plt.subplot(3, 3, i + 1) plt.imshow(images[i].numpy().astype("uint8")) plt.title(class_names[np.argmax(labels[i])]) # Convert tensor to integer plt.axis("off")
@unio79749 ай бұрын
I got this exact error, thank you so much!@@anthonieschaap1625
@maxborn7400 Жыл бұрын
Thanks for the great video and explaining everything in detail. I copied your github code, and it was running fine, until this part: resnet_model.add(Dense(5, activation='softmax')) I got an error: ValueError: Shapes (None, 1) and (None, 5) are incompatible. There's a long Traceback for it, but this seemed to be an issue with the output image, so I changed that very last layer to: resnet_model.add(Dense(1, activation='softmax')) Now the training runs, but the accuracy is really bad, around 0.25! Any resolution here? I don't know exactly why the output layer had to be mapped to a (None, 1) shape.
@tony-iy5xf Жыл бұрын
***Do not change your last layer to resnet_model.add(Dense(1, activation='softmax')) your NN needs to recognize between 5 classes(like in this video example). ***Try to use loss='sparse_categorical_crossentropy' in yourmodel.compile() function. That problem appears because your labels are in numbers(0,1,2,3...) not in one hot encoding.
@maxborn7400 Жыл бұрын
@@tony-iy5xf Thanks, that fixed it, and training epochs reached 1.0000. Why did the code work for you, when you had loss='categorical_crossentropy'? Because I just copied your code from github, and there the loss was set to that method.
@doggydoggy578 Жыл бұрын
@@tony-iy5xf This. Anyone who have trouble should listen to this guy
@rahul-kz6sc6 ай бұрын
Why my model predict wrong
@durgaprasadkakarla5311 Жыл бұрын
giving an error as name resolution in kaggle kernal
@NamanShah-m3h Жыл бұрын
Great stuff I just had a doubt if you could help with that When I am trying to reproduce your code I am running into an error in the model.fit() cell of code The error I am getting is "ValueError: Shapes (None, 1) and (None, 5) are incompatible" Can you please help me resolve this
@dhruvil8 Жыл бұрын
Hii naman , did you find the solution to this ? I've got the same problem
@hubertmsuya8071 Жыл бұрын
@@dhruvil8 use sparse_categorical_crossentropy
@Roomii Жыл бұрын
@@hubertmsuya8071 it doesnt work
@puneetkaur7725 Жыл бұрын
Hello sir , your website is unavailable, how i get code now??
@sairamadithya96503 жыл бұрын
Nice work...missing the hair
@NachiketaHebbar3 жыл бұрын
Thanks and yes, i miss them too
@anthonynguyen20273 жыл бұрын
nice vid
@MySmithereens Жыл бұрын
hello can anyone help me, i get error when i implement that code
@personunknown582 жыл бұрын
I'm trying this code on my custom dataset and I'm getting a lengthy error "ValueError: Shapes (None, 1) and (None, 3) are incompatible" with the mentioned line in the end.
@AkshayRakate2 жыл бұрын
set label_mode='categorical' in val_ds and train_ds
@tesnymeseddiki65732 жыл бұрын
@@AkshayRakate thanks
@abhishekbourai18322 жыл бұрын
@@AkshayRakate Thanks for your help brother. The Epochs are executing but the images are not Printing it seems now. ERROR: 'only integer scalar arrays can be converted to a scalar index'
@ayeshakhatun3114 Жыл бұрын
@@AkshayRakate bt it does not help for me.. still i have the same error...could u plz help me
@AkshayRakate Жыл бұрын
@@ayeshakhatun3114 what is the error ?
@jmg95092 жыл бұрын
1:18 - Imports
@kangqinyip2742 Жыл бұрын
Can anyone can share this code to me because the link he provide cannot work or cannot access it saying site unvailabel
@NachiketaHebbar Жыл бұрын
I have updated the github link in the video description.
@clotildamariamathias74162 жыл бұрын
ValueError: Shapes (none, 1) and (none, 5) are incompatible
@clotildamariamathias74162 жыл бұрын
Just replace loss='categorical_crossentropy' to loss='sparse_categorical_crossentropy' It works fine 👍
@arifemreakansel99282 жыл бұрын
model.add(Dense(number of classes, activation='softmax')) do this changes
@onewhoflutters4866 Жыл бұрын
Where can I reach you? I have some questions.
@hrissaspogs32979 ай бұрын
ya3tik douda mahlek ama zokomok l loss function 8alta
@nitisarath Жыл бұрын
validation accuracy not getting better help
@kangqinyip2742 Жыл бұрын
Can someone share the code for this tutorial I need it very badly
@NachiketaHebbar Жыл бұрын
I have updated the video description with the source code link
@kangqinyip2742 Жыл бұрын
Dude can you send this the code in github
@anuragkulkarni49912 жыл бұрын
i need help
@nibhanapuri44763 жыл бұрын
please solve the below error
@ronnybergmann75693 жыл бұрын
in his blog the following block before the plt.figure is missing. class_names = train_ds.class_names print(class_names) It is shown in the video, however.
@brainbox50583 жыл бұрын
Kannada davna??
@abdullahmohan91072 жыл бұрын
in this line history = resnet_model.fit(train_ds, validation_data=val_ds, epochs=4) I got error as ----> 1 history = resnet_model.fit(train_ds, validation_data=val_ds, epochs=4) ValueError: Shapes (None, 1) and (None, 5) are incompatible
@anmiiii2 жыл бұрын
Try adding label_mode = "categorical" as a parameter when initiating the train_ds and val_ds