Classifying cat and dog images using Kaggle dataset

Overview

PyTorch Image Classification

Classifies an image as containing either a dog or a cat (using Kaggle's public dataset), but could easily be extended to other image classification problems.

Dependencies:

  • PyTorch / Torchvision
  • Numpy
  • PIL
  • CUDA

Data

The data directory structure I used was:

  • project
    • data
      • train
        • dogs
        • cats
      • validation
        • dogs
        • cats
      • test
        • test

Performance

The result of the notebook in this repo produced a log loss score on Kaggle's hidden dataset of 0.04988 -- further gains can probably be achieved by creating an ensemble of classifiers using this approach.

Comments
  • Some questions on running other modules

    Some questions on running other modules

    1、'VGG' object has no attribute 'module' 2、Given input size: (128, 3, 3). Calculated output size: (1, -1, -1). Output size is too small. what i should do?thanks a lot.

    opened by lizxchen 3
  • multi-class training error

    multi-class training error

    I enjoyed the code that worked fine with a dog-cat dataset. However, by trying 4 classes, the following error showed up. Does it look like a code problem or a CUDA issue?

    main(mode="train") => Starting train on 'resnet50' model

    RuntimeError Traceback (most recent call last) in () ----> 1 main(mode="train")

    in main(mode, resume) 104 105 # train for one epoch --> 106 train(train_loader, model, criterion, optimizer, epoch) 107 108 # evaluate on validation set

    in train(train_loader, model, criterion, optimizer, epoch) 22 23 # measure accuracy and record loss ---> 24 prec1, prec1 = accuracy(y_pred.data, target, topk=(1, 1)) 25 losses.update(loss.data[0], images.size(0)) 26 acc.update(prec1[0], images.size(0))

    in accuracy(y_pred, y_actual, topk) 18 res = [] 19 for k in topk: ---> 20 correct_k = correct[:k].view(-1).float().sum(0) 21 res.append(correct_k.mul_(100.0 / batch_size)) 22

    RuntimeError: cuda runtime error (59) : device-side assert triggered at /b/wheel/pytorch-src/torch/lib/THC/generated/../generic/THCTensorMathReduce.cu:16

    opened by HIN0209 2
  • Bump bleach from 3.1.1 to 3.1.2

    Bump bleach from 3.1.1 to 3.1.2

    Bumps bleach from 3.1.1 to 3.1.2.

    Changelog

    Sourced from bleach's changelog.

    Version 3.1.2 (March 11th, 2020)

    Security fixes

    • bleach.clean behavior parsing embedded MathML and SVG content with RCDATA tags did not match browser behavior and could result in a mutation XSS.

      Calls to bleach.clean with strip=False and math or svg tags and one or more of the RCDATA tags script, noscript, style, noframes, iframe, noembed, or xmp in the allowed tags whitelist were vulnerable to a mutation XSS.

      This security issue was confirmed in Bleach version v3.1.1. Earlier versions are likely affected too.

      Anyone using Bleach <=v3.1.1 is encouraged to upgrade.

      https://bugzilla.mozilla.org/show_bug.cgi?id=1621692

    Backwards incompatible changes

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    opened by dependabot[bot] 1
  • Bump certifi from 2019.6.16 to 2022.12.7

    Bump certifi from 2019.6.16 to 2022.12.7

    Bumps certifi from 2019.6.16 to 2022.12.7.

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  • Bump jupyter-core from 4.5.0 to 4.11.2

    Bump jupyter-core from 4.5.0 to 4.11.2

    Bumps jupyter-core from 4.5.0 to 4.11.2.

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    4.11.1

    What's Changed

    Full Changelog: https://github.com/jupyter/jupyter_core/compare/4.11.0...4.11.1

    4.11.0

    What's Changed

    New Contributors

    Full Changelog: https://github.com/jupyter/jupyter_core/compare/4.10.0...4.11.0

    4.10.0

    What's Changed

    New Contributors

    Full Changelog: https://github.com/jupyter/jupyter_core/compare/4.9.2...4.10.0

    4.9.2

    What's Changed

    New Contributors

    Full Changelog: https://github.com/jupyter/jupyter_core/compare/4.9.1...4.9.2

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    Changes in jupyter-core

    5.0.0

    (Full Changelog)

    Major Changes

    Prefer Environment Level Configuration

    We now make the assumption that if we are running in a virtual environment, we should prioritize the environment-level sys.prefix over the user-level paths. Users can opt out of this behavior by setting JUPYTER_PREFER_ENV_PATH, which takes precedence over our autodetection.

    Migrate to Standard Platform Directories

    In version 5, we introduce a JUPYTER_PLATFORM_DIRS environment variable to opt in to using more appropriate platform-specific directories. We raise a deprecation warning if the variable is not set. In version 6, JUPYTER_PLATFORM_DIRS will be opt-out. In version 7, we will remove the environment variable checks and old directory logic.

    Drop Support for Python 3.7

    We are dropping support for Python 3.7 ahead of its official end of life, to reduce maintenance burden as we add support for Python 3.11.

    Enhancements made

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    ... (truncated)

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  • Bump pillow from 9.0.1 to 9.3.0

    Bump pillow from 9.0.1 to 9.3.0

    Bumps pillow from 9.0.1 to 9.3.0.

    Release notes

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    9.3.0

    https://pillow.readthedocs.io/en/stable/releasenotes/9.3.0.html

    Changes

    ... (truncated)

    Changelog

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    9.3.0 (2022-10-29)

    • Limit SAMPLESPERPIXEL to avoid runtime DOS #6700 [wiredfool]

    • Initialize libtiff buffer when saving #6699 [radarhere]

    • Inline fname2char to fix memory leak #6329 [nulano]

    • Fix memory leaks related to text features #6330 [nulano]

    • Use double quotes for version check on old CPython on Windows #6695 [hugovk]

    • Remove backup implementation of Round for Windows platforms #6693 [cgohlke]

    • Fixed set_variation_by_name offset #6445 [radarhere]

    • Fix malloc in _imagingft.c:font_setvaraxes #6690 [cgohlke]

    • Release Python GIL when converting images using matrix operations #6418 [hmaarrfk]

    • Added ExifTags enums #6630 [radarhere]

    • Do not modify previous frame when calculating delta in PNG #6683 [radarhere]

    • Added support for reading BMP images with RLE4 compression #6674 [npjg, radarhere]

    • Decode JPEG compressed BLP1 data in original mode #6678 [radarhere]

    • Added GPS TIFF tag info #6661 [radarhere]

    • Added conversion between RGB/RGBA/RGBX and LAB #6647 [radarhere]

    • Do not attempt normalization if mode is already normal #6644 [radarhere]

    ... (truncated)

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  • Bump nbconvert from 6.3.0 to 6.5.1

    Bump nbconvert from 6.3.0 to 6.5.1

    Bumps nbconvert from 6.3.0 to 6.5.1.

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    Release 6.5.1

    No release notes provided.

    6.5.0

    What's Changed

    New Contributors

    Full Changelog: https://github.com/jupyter/nbconvert/compare/6.4.5...6.5

    6.4.3

    What's Changed

    New Contributors

    Full Changelog: https://github.com/jupyter/nbconvert/compare/6.4.2...6.4.3

    6.4.0

    What's Changed

    New Contributors

    ... (truncated)

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  • Bump nbconvert from 5.5.0 to 6.3.0

    Bump nbconvert from 5.5.0 to 6.3.0

    Bumps nbconvert from 5.5.0 to 6.3.0.

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  • Bump mistune from 0.8.4 to 2.0.3

    Bump mistune from 0.8.4 to 2.0.3

    Bumps mistune from 0.8.4 to 2.0.3.

    Release notes

    Sourced from mistune's releases.

    Version 2.0.2

    Fix escape_url via lepture/mistune#295

    Version 2.0.1

    Fix XSS for image link syntax.

    Version 2.0.0

    First release of Mistune v2.

    Version 2.0.0 RC1

    In this release, we have a Security Fix for harmful links.

    Version 2.0.0 Alpha 1

    This is the first release of v2. An alpha version for users to have a preview of the new mistune.

    Changelog

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    Changelog

    Here is the full history of mistune v2.

    Version 2.0.4

    
    Released on Jul 15, 2022
    
    • Fix url plugin in &lt;a&gt; tag
    • Fix * formatting

    Version 2.0.3

    Released on Jun 27, 2022

    • Fix table plugin
    • Security fix for CVE-2022-34749

    Version 2.0.2

    
    Released on Jan 14, 2022
    

    Fix escape_url

    Version 2.0.1

    Released on Dec 30, 2021

    XSS fix for image link syntax.

    Version 2.0.0

    
    Released on Dec 5, 2021
    

    This is the first non-alpha release of mistune v2.

    Version 2.0.0rc1

    Released on Feb 16, 2021

    Version 2.0.0a6

    
    </tr></table> 
    

    ... (truncated)

    Commits
    • 3f422f1 Version bump 2.0.3
    • a6d4321 Fix asteris emphasis regex CVE-2022-34749
    • 5638e46 Merge pull request #307 from jieter/patch-1
    • 0eba471 Fix typo in guide.rst
    • 61e9337 Fix table plugin
    • 76dec68 Add documentation for renderer heading when TOC enabled
    • 799cd11 Version bump 2.0.2
    • babb0cf Merge pull request #295 from dairiki/bug.escape_url
    • fc2cd53 Make mistune.util.escape_url less aggressive
    • 3e8d352 Version bump 2.0.1
    • Additional commits viewable in compare view

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  • Bump numpy from 1.21.0 to 1.22.0

    Bump numpy from 1.21.0 to 1.22.0

    Bumps numpy from 1.21.0 to 1.22.0.

    Release notes

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    v1.22.0

    NumPy 1.22.0 Release Notes

    NumPy 1.22.0 is a big release featuring the work of 153 contributors spread over 609 pull requests. There have been many improvements, highlights are:

    • Annotations of the main namespace are essentially complete. Upstream is a moving target, so there will likely be further improvements, but the major work is done. This is probably the most user visible enhancement in this release.
    • A preliminary version of the proposed Array-API is provided. This is a step in creating a standard collection of functions that can be used across application such as CuPy and JAX.
    • NumPy now has a DLPack backend. DLPack provides a common interchange format for array (tensor) data.
    • New methods for quantile, percentile, and related functions. The new methods provide a complete set of the methods commonly found in the literature.
    • A new configurable allocator for use by downstream projects.

    These are in addition to the ongoing work to provide SIMD support for commonly used functions, improvements to F2PY, and better documentation.

    The Python versions supported in this release are 3.8-3.10, Python 3.7 has been dropped. Note that 32 bit wheels are only provided for Python 3.8 and 3.9 on Windows, all other wheels are 64 bits on account of Ubuntu, Fedora, and other Linux distributions dropping 32 bit support. All 64 bit wheels are also linked with 64 bit integer OpenBLAS, which should fix the occasional problems encountered by folks using truly huge arrays.

    Expired deprecations

    Deprecated numeric style dtype strings have been removed

    Using the strings "Bytes0", "Datetime64", "Str0", "Uint32", and "Uint64" as a dtype will now raise a TypeError.

    (gh-19539)

    Expired deprecations for loads, ndfromtxt, and mafromtxt in npyio

    numpy.loads was deprecated in v1.15, with the recommendation that users use pickle.loads instead. ndfromtxt and mafromtxt were both deprecated in v1.17 - users should use numpy.genfromtxt instead with the appropriate value for the usemask parameter.

    (gh-19615)

    ... (truncated)

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  • Bump notebook from 6.4.10 to 6.4.12

    Bump notebook from 6.4.10 to 6.4.12

    Bumps notebook from 6.4.10 to 6.4.12.

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  • Bump ipython from 7.7.0 to 7.16.3

    Bump ipython from 7.7.0 to 7.16.3

    Bumps ipython from 7.7.0 to 7.16.3.

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Owner
Robert Coleman
Robert Coleman
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