Updated 4 years ago
Lab 7 Working with a More Diverse Dataset
So, as part of the task you need to process your data -- not least resizing it to be uniform in shape.
You'll follow these steps:
- Explore the Example Data of Cats and Dogs
- Build and Train a Neural Network to recognize the difference between the two
- Evaluate the Training and Validation accuracy
A. Downloading and organising the images into directories
1. Let's start by downloading our example data, a .zip of 2,000 JPG pictures of cats and dogs, and extracting it locally in /tmp
.
NOTE: The 2,000 images used in this exercise are excerpted from the "Dogs vs. Cats" dataset available on Kaggle, which contains 25,000 images. Here, we use a subset of the full dataset to decrease training time for educational purposes.
!wget --no-check-certificate \
https://storage.googleapis.com/mledu-datasets/cats_and_dogs_filtered.zip \
-O /tmp/cats_and_dogs_filtered.zip
--2020-10-20 12:29:28-- https://storage.googleapis.com/mledu-datasets/cats_and_dogs_filtered.zip
Resolving storage.googleapis.com (storage.googleapis.com)... 108.177.127.128, 172.217.218.128, 173.194.69.128, ...
Connecting to storage.googleapis.com (storage.googleapis.com)|108.177.127.128|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: 68606236 (65M) [application/zip]
Saving to: ‘/tmp/cats_and_dogs_filtered.zip’
/tmp/cats_and_dogs_ 100%[===================>] 65.43M 50.0MB/s in 1.3s
2020-10-20 12:29:29 (50.0 MB/s) - ‘/tmp/cats_and_dogs_filtered.zip’ saved [68606236/68606236]