That means you’re using python 3. You may find other issues too, since the course was written for python 2.
One is for batchnorm, one without. They are saved in .keras/models in your home directory automatically.
In the lesson 1 notebook when creating the VGG model from scratch we use:
model = Sequential()
I’ve looked at the images in the data set, and they’re of different sizes and none seem to be 224 x 224.
Should the Cats and Dogs images be cropped to 224 x 224 prior to running them through the model? If so, what’s the best practice for standardizing images of various sizes?
Please help to to print the csv file after prediction, I am facing issue in printing the csv file .
Can someone share the code.
Please share the code for printing the csv file after prediction I am getting stuck in that place
Saving predictions to a CSV
Approach 1: import numpy as np
isdog = preds[:,1] filenames = batches.filenames ids = np.array([int(f[8:f.find('.')]) for f in filenames]) subm = np.stack([ids,isdog], axis=1) submission_file_name = 'submission1.csv' np.savetxt(submission_file_name, subm, fmt='%d,%.5f', header='id,label', comments='')
preds are the output of
Submission properties: Probabilities as answers; two classes
See the end of this notebook: https://github.com/fastai/courses/blob/master/deeplearning1/nbs/dogs_cats_redux.ipynb
Approach 2: import csv
filenames = test_batches.filenames ids = [filename.split('/').split('.') + ".ppm" for filename in filenames] classes = [np.argmax(prob) for prob in probs] pairs = zip(ids, classes) with open(results_path+"submission--lesson-1--vgg16--12-epochs--peak.csv", "w") as f: writer = csv.writer(f, delimiter=";") writer.writerows(pairs)
probs are the output of
Submission properties: Labels as answers; 43 classes
See the end of this notebook: https://github.com/MatthewKleinsmith/fast-ai-MOOC/blob/master/german-traffic-signs.ipynb
When doing the fine-tuning, why is validation accuracy higher than training accuracy?
How to improve my kaggle score.
I’m currently in the top 29%. Best results achieved by running 10 epochs and changing the maximum and minimum values for my “is_dog” probability to fit between .0455 and .0955.
Wondering … what can I do/try to improve the score?
@wgpubs There are more tips for improving Kaggle scores in later lessons, and you may want to return to this competition as you proceed with the course.
@Gelu74 That is because we are using dropout on the training set (throwing away some information so as to avoid overfitting), but not on the validation set (because we want to be as accurate as possible on the validation and test sets). We’ll talk more about this idea in Lesson 3.
@noodles Thanks for the heads up! I just found 3 links on the wiki that I updated. If you find more outdated links, could you please reply listing their locations.
@adamontherun Keras can resize images. This is set by the target_shape parameter in flow_from_directory. This function is being called from our get_batches method with target_shape=(224,224), so it is already being handled.
I also am encountering cPickle module not found error. I am running Python 3. Should I make sure to downgrade to Python 2 to avoid future issues, or can those issues be easily fixed as I get to them?
Thanks for the tip. That works for me too. I just hope there won’t be many more such issues since I’m also working with Python 3, which is apparently the cause of this problem.
Woops, I spoke too soon. In the blink of an eye, the error reappeared. I closed and re-opened Jupyter Notebook, but that didn’t work :-/
Even though I edited the utils.py file, it is still referring to the line which I had commented out
i.e. import cPickle as pickle
What’s going on??
C:\Users\Admin\Documents\Fast_AI\courses\deeplearning1\nbs\utils.py in ()
1 from future import division,print_function
2 import math, os, json, sys, re
----> 3 import cPickle as pickle
4 from glob import glob
5 import numpy as np
how long train the model ?
when run vgg.fit(), it has take two hours ,still in epoch .the train data is not so big . train data size = 200 images.
vgg.fit(batches, val_batches, nb_epoch=1)
something went wrong ?
That is quite strange… reloading jupyter should take care of it and reload(utils) should also take care of it. Maybe you’ve edited a different file or forgot to save?
Ahh! It’s a different error, I didn’t see it:
ImportError: No module named ‘bcolz’
How do I fix that?