Its a twenty minutes video and yet feels like five minutes, it is one of the KZbin tutorial that you don't get bored and stay focus.
@sajansudhir18593 жыл бұрын
Can't move to next video without appreciate your commitment and hard work towards beginner level coders.
@ALFER382 жыл бұрын
Watching this video clarified how data augmentation is used. Very good job!
@DigitalSreeni2 жыл бұрын
Glad it was helpful!
@baibhavchakraborty15602 жыл бұрын
I have to do a college project on GAN image augmentation. Couldn't understand how to do. You came to my rescue. Thank you, Sir
@harishgoud36284 жыл бұрын
most underrated channel , love ur work
@DigitalSreeni4 жыл бұрын
I appreciate that. Please help spread the word to your buddies.
@marydayanaa91304 жыл бұрын
Thank you so much sir. Very good explanation. I have just started watching all your videos.
@angus21704 ай бұрын
Awesome video! The explanations were great, clear and concise and I found it very beneficial. Thank you :)
@DigitalSreeni4 ай бұрын
Glad it was helpful!
@Thoughts_of_a_900_ELO3 жыл бұрын
Greatest youtube lecturer I have ever witnessed 🌝👌
@DigitalSreeni3 жыл бұрын
Glad you think so!
@fadilyassin46613 жыл бұрын
you said you hope we learn some thing new , hell yes your so good in explaining , I did not see all of your tutorials i hope I can to me they are a refrence to many thhings in machine learning unless you understand the building blocks of ML you can't do any real work you and some few others are doing this amazingly big thank you
@omidgholami-v7u Жыл бұрын
The best learning tensorflow Thank you
@asif19633 жыл бұрын
I am new in DCNN. Moreover, I am working on image data augmentation and I have been writing code of augmentation. Moreover, I have 5 classes in the dataset i.e. Grass, Flower, Fruits, Dust, and Leaves Thus, the train set in is also consist of 8 classes. However, after augmentation, all of the augmented data has been store in the train folder but it does not store in their individual class. Besides that, I have been applied the directory manually for example: directory = ('/content/dataset/train/Grass'), save_to_dir = ('/content/dataset/train/Grass') Unfortunately, it does not work, and augmented images, not generated. Therefore, it is possible to store the augmented data in a similar folder where before augmented data exist (raw data folder)? if it can be possible individually (one by one class) that will be also very helpful for me.
@nguyenhai54553 жыл бұрын
A 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.
@FanFanlanguageworld17073 жыл бұрын
Hello, 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 ?
@AlexDerBar Жыл бұрын
I know I'm like a year late to this comment but if anyone still sees this, batch size inside the flow method is used when passing the generator directly to the model.fit() method when training a model. In that case the generator makes the decision on how many images it should generate per epoch/batch. That's my understanding at least.
@ashilshah3376 Жыл бұрын
@@AlexDerBar thank you it helped :)
@souravjha21463 жыл бұрын
Man your explanation is reallly good....thanks
@mamoon723 жыл бұрын
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.
@ShubhamKumar-xy6kj2 жыл бұрын
you got solution for mentioned query?
@vimalshrivastava59513 жыл бұрын
Very informative video with clear explanation....!!!!
@saikrishnavadali053 жыл бұрын
Amazing video!!! Sreeni is the best in AI!!! Very very helpful video..
@DigitalSreeni3 жыл бұрын
Glad it was helpful!
@limzisin262 жыл бұрын
Thanks Sir. This video helped me a lot in my final year project!
@DigitalSreeni2 жыл бұрын
Great to hear!
@wabisabi66802 жыл бұрын
i 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
@naveenfernando18523 жыл бұрын
Hi Sir, How can we perform data augmentation when the dataset contains with imbalance data. Class A : 2000 images, Class B: 5000, Class C: 1000 images .. When we use flow_from_directly it augment all these images without any weight balancing Also in cases like this(multi class imbalance data) how can we customize the number of augmented images per class.. Because at the end, to create a accurate ml model we should input equal number of samples from each class right. Thanks and best regards.
@DigitalSreeni3 жыл бұрын
Please watch my video on the topic of imbalanced data. kzbin.info/www/bejne/rIClk36ErM5pfdE kzbin.info/www/bejne/jILYe6l9id91ndk
@saranbdsravi2 жыл бұрын
thank 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.
@darasingh89373 жыл бұрын
Dude, you just became my guru! Thank you!
@DigitalSreeni3 жыл бұрын
Glad to hear it!
@skullgaming59619 ай бұрын
I want to the augmented images to be saved in their respective class folders, how can i do that.
@saeedag44683 жыл бұрын
You are an amazing teacher.. subscribed!
@wi716303 жыл бұрын
hi, 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,))
@NisarAhmad-ch3kc Жыл бұрын
It means your program in not reading images from folder. You can also read images using cv2.
@archimittal3810 Жыл бұрын
Hii,I am facing the same issue...Could you please tell me how did you rectify this error?
@refreshyourlife30992 жыл бұрын
Hi sir, please i have question, how i can saved augmented images with a specify named?
@mihretdesta9153 Жыл бұрын
hey sir how do you balance imbalanced image datasets for multi-class image classification using deep learning
@divyaramesh11462 жыл бұрын
I 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
@swathimenon23454 жыл бұрын
Thank you for this video. Can you please help to know how to augment images that have multiple label classes already labelled. e.g. one image with different labels like traffic signal, speakers, traffic signs and lights. how to augment image with multiple labels?
@EkaterinaGolubeva-pr9ih Жыл бұрын
Thanks ! 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 ?
@helimehuseynova66313 жыл бұрын
Hello, 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?
@sabaal-jalal37103 жыл бұрын
I am working in a project with around 9k MRI images(including augmented images), my question is can I still use my MacBook Air normal CPU for deep learning image classification, or should I buy GPU? please advice... Thanks
@DigitalSreeni3 жыл бұрын
MacBook Air CPU and resources is not enough for deep learning. I am not aware of Nvidia GPU that just fits into a MacBook which means you need a new system with GPU and this can be expensive. The best way is to try Google Colab and work with their free GPU.
@sabaal-jalal37103 жыл бұрын
@@DigitalSreeni Thank you... I will try that.
@ShubhamKumar-xy6kj2 жыл бұрын
when generated from the folder,how to retrieve the labels of each image
@ravinirala99903 жыл бұрын
what is use of batch_size = 16, it created 21 augmented image
@ankitagrawal10463 жыл бұрын
Sir, In last you have taken two folders of image and then augmented it but after augmentation if I want to save the augmented images in two different folders, how can we do that?
@_ishraqaldagamseh76643 жыл бұрын
Great job but how can use this data in deep learning algorithms, or how can distinguish between the two classes to these data
@toninehme3 жыл бұрын
Thanks for this videos my dear!!! Can you explain which methods are used for NUMERICALS data augmentation?
@muhammadroshan73154 жыл бұрын
sir should which fill_mode should we apply to segmentation mask of image (consisting of each pixel value corresponding to class with no background)
@mehrnazmrz47033 жыл бұрын
That was awesome. Thank you very much for such a good tutorial.
@zakirshah78954 жыл бұрын
hello teacher. I hope so you are doing well, Sir i just applied data augmentation on my dataset (just some simple augmentation) but when i see the output images it also changes the contrast and brightness of the images too i don't know why can you help me
@mohammadmaaz7313 жыл бұрын
I am doing image augmentation in google colab, so do i need to save images in my google drive?
@ademyoussef4092 жыл бұрын
clear and smooth explanation! Thank you!
@cuthbertruseruka44612 жыл бұрын
Thank you for the training. You are amazing.
@aomo52932 жыл бұрын
Have y made a video showing how to work local images ?
@zakirshah78954 жыл бұрын
Sir can you please make video on Test time augmentation for trained model
@guidolippolis54363 жыл бұрын
Hi 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
@DigitalSreeni3 жыл бұрын
It depends on what size these 53 images are, if they are 256x256 then the dataset size is too small for deep learning. If they are 1024x1024 and if the size of your objects are relatively small and you have many of them, then you can divide each image into 256x256. I assume you are referring to semantic segmentation. You may get decent results with traditional machine learning (e.g., Random Forest, XGBoost, etc.). Do not forget to consider using pretrained networks as feature extractors. I did videos on these topics, for example, videos 194 and 195.
@guidolippolis54363 жыл бұрын
@@DigitalSreeni Yes, I'm referring to semantic segmentation. I have 53 images of people's eyes, they were captured by a medical device and they are 952x940 (or vice versa, I don't remember). My task is to create a segmentation model of the 3 regions: pupil, iris and infrared rays (which are projected to the pupil by the eye tracking device). Then, I have to calculate the pupil, iris and infrared diameters
@danm73775 ай бұрын
Can you work on detecting Parkinson disease using spirals drawing? it's my first project, and I have a dataset of 260 images only. I am not sure if I do data augmnetation on diseased person only or on healthy to
@DigitalSreeni4 ай бұрын
I have seen this dataset on Kaggle. You definitely need data augmentation as your dataset is small. Data augmentation should be applied to both classes (Parkinson's and healthy) to maintain balance in the dataset. This helps prevent bias in the model.
@danm73774 ай бұрын
@@DigitalSreeni thank you! I hope it works. It’s my first time building a model and I have deadline for 20 September :(
@ewananmo24044 жыл бұрын
@DigitalSreeni Sir, I am trying to augment video data. I have extracted the frames from the video. In order for my data to make sense, I have to apply the same augmentation to all of the frames of a video. Can you please tell me how can I achieve that with ImageDataGenerator?
@DigitalSreeni4 жыл бұрын
Fix the seed for augmentation, it performs same operations on each image/frame.
@muhammad529 Жыл бұрын
i 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
@poojithpoosa21093 жыл бұрын
Can we use data augmentation for transfer learning and extract feature from the data then use it to classify using other ml model?
@DigitalSreeni3 жыл бұрын
Data augmentation just transforms your input images. Therefore, you can treat them like any other regular image and use same approaches that you used for un-augmented images.
@blblist4 жыл бұрын
First of all, thanks! Secondly, should not we expect the augmented data to be organised in two folders (one for each class as the original data is)? I mean, the augmentation aims to have more training data and how this will be possible if the generated samples are not labelled?
@DigitalSreeni4 жыл бұрын
This video shows how augmentation is done and please do watch my video 150 where I warned about issues with keras for semantic segmentation. In that video I showed how you can save images and labels separately. In general, you define augmentation method and augment images of multiple classes along with labels based on the application.
@blblist4 жыл бұрын
@@DigitalSreeni Thank you so much, that's kind of you!
@reegee83214 жыл бұрын
Hello, thanks for this video, quite helpful. I would like to perform augmentation on my target(labels). This are not images but different classes of my images. How can that work. Or can my newly generated images automatically create classes on their own?
@DigitalSreeni4 жыл бұрын
Doesn't make any difference if your input is images or non-images. For images you have the luxury of generating new data just by rotation and other operations. For non-image data you think of what makes sense and apply that transformation. For example, you can randomly copy some data or drop some data.
@reegee83214 жыл бұрын
@@DigitalSreeni Thanks for the prompt response. But how do I perform augmentation on this type of data? It's a csv file (labels)
@mahalekshmianil26913 жыл бұрын
Best Explanation,sir
@DigitalSreeni3 жыл бұрын
Thanks and welcome
@nur__bijoy3 жыл бұрын
well explained. Instead of saving all augmented images within a directory, I want to save augmented images into respective classes. How can I do that?
@DigitalSreeni3 жыл бұрын
Not sure what you mean, to your hard drive as different classes in various directories?
@govtjobs7063 Жыл бұрын
Sir please make vedio for augmentation of mri dataset....
@saimahaider17834 жыл бұрын
It was really helpful. Keep going.
@DigitalSreeni4 жыл бұрын
Glad to hear that
@lilianetalba47322 жыл бұрын
Thanks God this Channel😭, i'm a health data scientist and i really need to learn how to programming better
@DigitalSreeni2 жыл бұрын
Learning to code is fun and it is not difficult, if you put in some initial effort. Good luck.
@lilianetalba47322 жыл бұрын
@@DigitalSreeni thanks sir
@adamt73673 жыл бұрын
Hi! 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!
@exploringMyself9984 жыл бұрын
Can you explain the significance of using batch_size in flow?
@DigitalSreeni4 жыл бұрын
Please watch this video: kzbin.info/www/bejne/j17dpKqma76rnJI
@hcmftm78623 жыл бұрын
dear i cant load my image any help please
@LimLiYih3 жыл бұрын
Hey sir, really need your help. What if I want to do data augmentation together with PCA? Hope will get your reply!!!!! Thanks a lot
@DigitalSreeni3 жыл бұрын
I never tried it as I never felt the need. But if you would like to perform augmentation with PCA then just do your PCA analysis first and redefine your X based on PCA. Then you can just augment the normal way using SMOTE or ADASYN. The keras way of augmentation is applicable to images but for structured data you can use one of the above to synthetically create new data.
@nadeemnadeemakhtar48523 жыл бұрын
Hello Sir.. Sir I am using ur code for my augmentation task.. But my images are grayscale.. And hence it is creating an error on SIZE..
@nadeemnadeemakhtar48523 жыл бұрын
If u can help me.. It would be a great pleasure
@nadeemnadeemakhtar48523 жыл бұрын
When I read images from my dataset.. It always generates an erro on rank 4..and doesn't dusplay channel dimension... How to resolve this.. Kindly help me
@منةالرحمن3 жыл бұрын
hello! am i the only one who found not image and mask matching it does not pick the right mask befor augmenting please help !!!!!!!!!!!!!
@منةالرحمن3 жыл бұрын
found it ^_^ take a look on your augmented file if ever you had the same issue i can share with y what i changed
@fatemehahmadpour7112 жыл бұрын
How convert Keras ImageDataGenerator into Numpy Array? image and label
@DigitalSreeni2 жыл бұрын
Image data generator object give you a batch of images each time you call it. To walk through these batches of images you can use .__next__
@RiaD5053 жыл бұрын
not working on large dataset ..
@yogeshrohit31473 жыл бұрын
Omg 🔥🔥 this is it , what I wanted 💖
@sabaal-jalal37103 жыл бұрын
Thanks Sir... very useful
@DigitalSreeni3 жыл бұрын
Always welcome
@truongminh85713 жыл бұрын
best tutorial ever! great!
@DigitalSreeni3 жыл бұрын
Glad you think so!
@ashilshah3376 Жыл бұрын
Thank you so much, helped a lot !!!!
@liwensong80373 жыл бұрын
thank you so much, this is amazing!
@gauravjha89864 жыл бұрын
that is very good explanation
@DigitalSreeni4 жыл бұрын
Thank you.
@iftiyarkhan73104 жыл бұрын
great explanation
@DigitalSreeni4 жыл бұрын
Glad it was helpful!
@iftiyarkhan73104 жыл бұрын
@@DigitalSreeni Hope to get more real-life projects examples with your great explanation. glad to be a part of your channel.