https://github.com/smsraj2001/cat-dog-image-classification

A Machine learning project on Cat v/s Dog image classification using CNN, VGG-16 and VGG-19 in Python
https://github.com/smsraj2001/cat-dog-image-classification

cnn-classification deep-learning google-colab image-classification image-processing kaggle-dataset keras-tensorflow machine-learning matplotlib numpy-library python310 recognizes-images tensorflow2 test-train-split vgg vgg16 vgg19

Last synced: 1 day ago
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A Machine learning project on Cat v/s Dog image classification using CNN, VGG-16 and VGG-19 in Python

• Host: GitHub
• URL: https://github.com/smsraj2001/cat-dog-image-classification
• Owner: smsraj2001
• Created: 2022-12-28T14:57:27.000Z (about 2 years ago)
• Default Branch: main
• Last Pushed: 2022-12-31T17:54:31.000Z (about 2 years ago)
• Last Synced: 2024-11-08T19:12:22.799Z (about 2 months ago)
• Topics: cnn-classification, deep-learning, google-colab, image-classification, image-processing, kaggle-dataset, keras-tensorflow, machine-learning, matplotlib, numpy-library, python310, recognizes-images, tensorflow2, test-train-split, vgg, vgg16, vgg19
• Language: Jupyter Notebook
• Homepage:
• Size: 50.6 MB
• Stars: 1
• Watchers: 2
• Forks: 2
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# CAT-DOG-IMAGE-CLASSIFICATION

A Machine learning (Deep Learning) project on ```Cat v/s Dog image classification``` using ```CNN```, ```VGG-16``` and ```VGG-19``` in Python.

- ```Link to the dataset``` : https://download.microsoft.com/download/3/E/1/3E1C3F21-ECDB-4869-8368-6DEBA77B919F/kagglecatsanddogs_5340.zip

- The Dataset consists of 12500 images of Cat and 12500 images of Dog.

## IMPORTANT NOTE

- It is advised to run the notebook in ```Google colab```, as colab provides ```GPU``` which lessens the training time of the algorithm.

- Also colab is inbuilt with all of the required python pip packages, thereby saving your time to install these packages on your local system.

- To run the notebook in your native pc, just change the paths of image folders accordingly.

- To use the ```TestImages```, upload the test images folders to your drive and give the path accordingly.

- A brief description of all the 3 algorithms namely ```CNN```, ```VGG-16``` and ```VGG-19``` are available in the presentations uploaded. (Both part 1 and part 2). Explanation on methods to approach the problem, result analysis of all the 3 algorithms are provided in these presentations as well.

- All the codes are documented for deeper understanding.

#### ```NOTE``` : For any queries/corrections, please feel free to mail : [email protected]