Fastai is a deep learning library for Python. It is built on top of PyTorch, and provides high level API to various common deep learning applications and data types. For more information see: https://docs.fast.ai or https://github.com/fastai
Questions tagged [fastai]
18 questions
4
votes
2 answers
Is it advisable to use a model which is underfit but gives very high accuracy?
I am training a model for a single-label classification task in Vision. In this training, I am using oversampling of all the classes, and MixUp augmentation, along with rotation and dihedral transformations to augment data.
What happens is, the…
truth
- 280
- 1
- 8
3
votes
1 answer
How to specify version for dependencies so that each one is compatible and stays within a size limit?
I am trying to deploy a web app to Heroku. The free tier is limited to 500 MB.
I am using my resnet34 model as a .pkl file.
I create model with it using the fastai library.
This project requires torch and torchvision as dependencies.
But not…
truth
- 280
- 1
- 8
2
votes
2 answers
Face recognition - How to make an image classifier with large number of classes?
I am planning to make an image classifier that identifies the face of every player in the English Premier League. I have a couple of questions (since until now I have only worked with small or academic datasets).
My questions:
How do I download…
Shawn
- 173
- 1
- 4
1
vote
2 answers
How imagenet mean and std derived?
To use pre-trained models it is a preferred practice to normalize the input images with imagenet standards.
mean=[0.485, 0.456, 0.406] and std=[0.229, 0.224, 0.225].
How are these parameters derived?
Wickkiey
- 299
- 3
- 10
1
vote
1 answer
fastai - using 'untar_data' function in kaggle kernel
I have recently started with fastai lesson 1 and I am using kaggle to run the course notebooks. While going through the ‘lesson1-pets’ notebook we use untar_data(URLs.PETS) to get the data.
What I want to understand is where does this data get…
boredaf
- 161
- 1
- 8
1
vote
2 answers
Classification with a lot of the classes
I’m trying to make model which will classify text into about 500 different classes. I think that I have to customize architecture of the Pooling Classifier which looks now like this:
(1): PoolingLinearClassifier(
(layers): Sequential(
(0):…
maliniaki
- 71
- 3
1
vote
0 answers
Improve performance of my CNN model
I am working on an image classification problem.
There are 876 images in the training and 600 in the test dataset.
It is a multi class classification for plants.
Since this is my first CNN problem, I started working with tensorflow and keras to…
Akshat Shreemali
- 11
- 1
1
vote
1 answer
Arguments in python fast.ai function that are not in the function definition?
I have been coming across function calls that use arguments that are not in the function definition. I would like to know how that works (i.e. how the compiler interprets this).
For example, this function call:
…
user637140
- 201
- 1
- 5
0
votes
1 answer
How to handle imbalanced NLP text data set e.g. some classes only have 2 records
I am working on a dataset with around 2000 records.
Around 80% records have their the categorical labels.
There are around 200 categories, some categories got more than 20 records; whereas others only have TWO....
Considering this is a text dataset,…
Franva
- 133
- 6
0
votes
2 answers
Fast AI Lesson 4 - MNIST. Confused about multiplying weights by pixels?
I’m on lesson 4 of the Fast AI "Deep Learning for Coders" course, and have been back through the same lesson a few times now but I don’t think I’m quite getting a few things. I want to have an understanding of what’s going on before moving on.
This…
Andrew
- 101
- 1
0
votes
0 answers
AttributeError: normalize using fastai
I'm trying to use fastai to train a model but I am getting this error when I try to normalize my data using imagenet stats.
Can someone pls help me with it?
#build fastai dataset loader
np.random.seed(42)
#fastai automatically factors the ./train…
Soumya
- 1
0
votes
1 answer
Bad performance with CNN for basic image classification task
how are you doing?
I'm playing around with CNN in FastAI.
My model with 2 millions parameters only has around 80% accuracy. I also tried with Data normalization, Batch normalization, Label smoothing, Mixup but the results are still capped at 80-81%…
0
votes
0 answers
The best approach and library for time-series similarity
I have a time-series classification problem with IoT signals. The training dataset has seven target signals.
I used tsai as a fastai/torch library, and I achieved satisfying results.
However, in a production environment, there is a larger number of…
AbelAI
- 3
- 2
0
votes
0 answers
How to improve neural network for face classification?
I generated 700 1024x1024 images of female faces using an API. I labelled them either as attractive or unattractive.
The neural net should learn which face I find attractive and which not. But the accuracy is worse than a random guess.
To crop the…
0
votes
0 answers
How to use a Swin Transformer with metric learning?
Using timm's implementation of Swin Transformer, how does one generate an embedding vector?
I would like to use timm's SwinTransformer class to generate an embedding vector for use with metric learning (sub-center ArcFace).
What I've tried:
To…
Larry OBrien
- 111
- 4