Комментарии:
Thank you so much, helped a lot !!!!
Ответить❤
ОтветитьThe best learning tensorflow
Thank you
Please reply to me, sir ...
Ответитьhey sir how do you balance imbalanced image datasets for multi-class image classification using deep learning
Ответитьthanks a lot
Ответитьi have a folder in google drive which contains subfolders of images. I want to augment all these subfolders to the count of that folder which contain maximum images. i want to store all these augmented images in separate folder
ОтветитьVery Helpful !!
ОтветитьSir please make vedio for augmentation of mri dataset....
ОтветитьThanks ! What if we have a later version of tensorflow and keras, should we downgrade our version to run your code ? How would we do that ? Otherwise, is there another way to have the same result ?
ОтветитьHave y made a video showing how to work local images ?
ОтветитьI have to do a college project on GAN image augmentation.
Couldn't understand how to do.
You came to my rescue.
Thank you, Sir
Thanks sir
ОтветитьThanks God this Channel😭, i'm a health data scientist and i really need to learn how to programming better
ОтветитьI am getting value error when i am doing for directory. It is telling, i must have rank 4 and passed an array with shape. What should i do sir
ОтветитьHow convert Keras ImageDataGenerator into Numpy Array? image and label
Ответитьi have this Problem how can i do this after Augmentation with image generator save the image to his labels in the main Dataset (Multiclass dog-car-..) besucs wen i save the imags after use the function ImageDataGenerator I saw in the folder where the pictures are saved all the pictures are mixed together, because here I don't have a folder where cat alone and cars alone ... but was befor Augmentation all in his class
thanks for your answer
Thank you for clear explanations! So lucky I found your channel, subscribed
Ответитьwhen generated from the folder,how to retrieve the labels of each image
Ответитьthank you for covering the various class label options namely single class, multi class within their respective folders.
what if i had all the image classes within the same folder?
grateful if you could give me pointers on how i can apply augmentation to the image of the weaker class.
does the algorithm differentiate between weaker and dominant classes?
my setting is all images in one folder and labels within a csv.
Hi sir, please i have question, how i can saved augmented images with a specify named?
Ответитьgood
ОтветитьPLEASE HELP ME
ОтветитьThanks Sir. This video helped me a lot in my final year project!
ОтветитьThank you for the training. You are amazing.
ОтветитьWatching this video clarified how data augmentation is used. Very good job!
Ответитьclear and smooth explanation! Thank you!
ОтветитьThanks a lot
ОтветитьThank you.
ОтветитьHi! This is the best tutorial I have come across, I have 1 small issue I was hoping you could help me with! When I am training a folder of images, instead of augmenting and saving 64 photos, its saving over 500 photos, its saving each image 5 times over.
Any ideas?
Thanks!
first of all thankyou sir for another great video..❤
2nd of all i have a question if we are augmenting a multi class problem how can we save augmented images in different class/folders because i saw you save augmented images from to folders in a single folder which will be very difficult to separate manually if i am working with a big dataset ?
Thankyou in advance.
what is use of batch_size = 16, it created 21 augmented image
ОтветитьVery informative video with clear explanation....!!!!
ОтветитьGreat job but how can use this data in deep learning algorithms, or how can distinguish between the two classes to these data
ОтветитьHello, I am working with pytorch and I use resnet18 model for my dataset. I increased number of images for my dataset. I still get lower accuracy. What can i do for increasing accuracy of model?
Ответитьhi, when i run this code for multiple images
i = 0
for batch in datagen.flow(x, batch_size=16,
save_to_dir='augmented',
save_prefix='aug',
save_format='png'):
i += 1
if i > 20:
break
i received an error
ValueError: ('Input data in `NumpyArrayIterator` should have rank 4. You passed an array with shape', (0,))
Dude, you just became my guru! Thank you!
ОтветитьCan we use data augmentation for transfer learning and extract feature from the data then use it to classify using other ml model?
ОтветитьHello, it's little confusing with the batch_size and i>20, which one defines the nb of image augmented? what's the role of batch_size ?
Ответитьdear i cant load my image any help please
ОтветитьHi Sreenivas, I'm creating a segmentation model using traditional machine learning and my dataset is composed by 53 images. Since I think I have to use half of the dataset as train dataset and the other half as test dataset, how can I improve the performance of the model? I can't use data augmentation because I have few images, according to what you said in the video. Thanks in advance
ОтветитьBest Explanation,sir
ОтветитьA greate video ! But I have a question. When you augmented the input images, What about the mask of those images, Did you also augment the masks base on those augmented images ? My project is semantic segmentation.
Ответитьbest tutorial ever! great!
ОтветитьYou are an amazing teacher.. subscribed!
ОтветитьThanks for this videos my dear!!! Can you explain which methods are used for NUMERICALS data augmentation?
ОтветитьThat was what exactly I wanted
ОтветитьThat was awesome. Thank you very much for such a good tutorial.
ОтветитьMan your explanation is reallly good....thanks
Ответить