https://github.com/kmohamedalie/cat_and_dog_image_recognition

Image Recognition
https://github.com/kmohamedalie/cat_and_dog_image_recognition

cats-and-dogs-classification computer-vision convolutional-neural-networks deep-learning image-classification keras tensorflow

Last synced: 9 days ago
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Image Recognition

• Host: GitHub
• URL: https://github.com/kmohamedalie/cat_and_dog_image_recognition
• Owner: Kmohamedalie
• License: mit
• Created: 2023-04-20T21:20:02.000Z (over 2 years ago)
• Default Branch: master
• Last Pushed: 2023-08-20T08:13:39.000Z (about 2 years ago)
• Last Synced: 2025-01-02T15:32:20.278Z (10 months ago)
• Topics: cats-and-dogs-classification, computer-vision, convolutional-neural-networks, deep-learning, image-classification, keras, tensorflow
• Language: Jupyter Notebook
• Homepage:
• Size: 12.1 MB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# Cat_and_Dog_Image_Recognition

Applying Deep learning(CNN) to recognise images of cats and dogs. Inspired by two of my classmates **pet lovers** Sophia and Ekin.

**Libraries**

**Keras:** Keras 

**Tensorflow:** Tensorflow 

For more try the following challenge on Kaggle:

Create your own network: Youtube


**Kaggle:**  Competition 

**Google Developers Demo:**  Demo

![image](https://user-images.githubusercontent.com/63104472/233629479-358fe179-2e56-4256-bd36-66481553ae4d.png)

![image](https://user-images.githubusercontent.com/63104472/233629833-4b86a81b-00a0-42dc-8e36-f4976c5206e4.png)

## Output: 

**Data:** Cats and Dogs 

**Validation accurary:** 79.65%

**Training time:** 28.6 ms 

**Resources:** Google Colab Standard GPU

**Model Architecture:** 2Cov, 2MaxPool, Flatten, Dense, Final output 




## **Regularized output:** 


Please Check out the REGULARIZED - Augmented  Cat_and_Dog_Image_Recognition notebook for more.


**Data:** Cats and Dogs 


**Validation accurary:** 72.75% 

**Training time:** 45min 44s with magic function(%%time). 


**Resources:** Google Colab Standard TPU


**Model Architecture:** Cov, MaxPool, Droupout, Flatten, Dense, Final output 





### Final image prediction:

![image](https://user-images.githubusercontent.com/63104472/233628964-29719a68-9984-4ea4-8456-280703433e64.png)