https://github.com/maneprajakta/image_classification

All about Image classification problem 's solved during TensorFlow learning.
https://github.com/maneprajakta/image_classification

callbacks cnn image-classification image-processing tensorflow

Last synced: over 1 year ago
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All about Image classification problem 's solved during TensorFlow learning.

• Host: GitHub
• URL: https://github.com/maneprajakta/image_classification
• Owner: maneprajakta
• Created: 2020-07-01T14:04:34.000Z (almost 6 years ago)
• Default Branch: master
• Last Pushed: 2020-07-01T14:55:13.000Z (almost 6 years ago)
• Last Synced: 2025-02-27T18:07:08.875Z (over 1 year ago)
• Topics: callbacks, cnn, image-classification, image-processing, tensorflow
• Language: Jupyter Notebook
• Homepage:
• Size: 16.8 MB
• Stars: 6
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# Image_Classification




All about image classification problems solved using TensorFlow while learning TensorFlow.

-Dataset of every problem is included in folder







 1.Happy_or_sad_emoji: 
 

-Binary Classification


-A cnn with use of ImageDataGeneratorClass of tensorflow.


-Source dataset contains sad and happy dataset 40 images each train on them and used for prediction.

 


 


  2.Cat_or_Dog :
 

-Binary Classification


-A cnn with intermediate  representation of layers of model.


-Trying to get better validation accuracy using agumentation.


-Source data set conatains train and validation images seprate and each contain cat and dog seprate images . data : https://www.kaggle.com/c/dogs-vs-cats/


-Prediction







  3.Fashion_Mnist :
 

-Multiclass Classification.


-First without cnn than using cnn to get better accuracy .


-Using callback to stop training when desired acc reached.


-fashion_mnist from keras dataset.