https://github.com/haseebulhassan437/classification-cats-vs-dogs-using-kesras..
https://github.com/haseebulhassan437/classification-cats-vs-dogs-using-kesras..
Last synced: 4 months ago
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- Host: GitHub
- URL: https://github.com/haseebulhassan437/classification-cats-vs-dogs-using-kesras..
- Owner: HaseebUlHassan437
- Created: 2025-05-10T14:17:06.000Z (5 months ago)
- Default Branch: main
- Last Pushed: 2025-05-10T15:09:59.000Z (5 months ago)
- Last Synced: 2025-05-10T15:35:11.862Z (5 months ago)
- Language: Jupyter Notebook
- Size: 296 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
---
# Cats vs Dogs Image Classification using Keras 🐱🐶
This project demonstrates how to build a **Convolutional Neural Network (CNN)** using **Keras** to classify images of **cats** and **dogs**. It uses the popular **Dogs vs Cats dataset** from Kaggle and trains a binary image classifier from scratch.
---
| File | Description |
| :------------------------------------------------------------------------------------------------------------------------------------------------------------- | :-------------------------------------------------------------------------------------------------------------------------------- |
| [`cats_vs_dog_classification.ipynb`](https://github.com/HaseebUlHassan437/classification-cats-vs-dogs-using-kesras/blob/main/cats_vs_dog_classification.ipynb) | The main notebook for loading data, preprocessing images, building a CNN, training, and evaluating model accuracy on test images. |
---
## 📦 Dataset
**Kaggle Dogs vs Cats Dataset**
📎 [Click here to access the dataset](https://www.kaggle.com/datasets/salader/dogs-vs-cats)
* Consists of **25,000 labeled images** (12,500 cats & 12,500 dogs).
* Balanced dataset for binary classification.
---
## 🧠 Model Overview
* **Framework**: TensorFlow + Keras
* **Architecture**: Custom-built CNN with:
* Convolutional layers
* MaxPooling layers
* Dropout for regularization
* Dense layers for final classification
* **Loss Function**: Binary Crossentropy
* **Optimizer**: Adam
* **Metrics**: Accuracy
---
## 🛠️ Requirements
* Python 3.x
* Libraries:
* `tensorflow`
* `keras`
* `matplotlib`
Install with:
```bash
pip install tensorflow keras matplotlib
```
---
## 🚀 How to Run
1. **Clone the repository**:
```bash
git clone https://github.com/HaseebUlHassan437/classification-cats-vs-dogs-using-kesras.git
cd classification-cats-vs-dogs-using-kesras
```
2. **Download the dataset** from [Kaggle](https://www.kaggle.com/datasets/salader/dogs-vs-cats) and extract it into your working directory.
3. **Open the notebook** in Jupyter or Google Colab and follow the step-by-step code to train and test the model.
---
## 📈 Results
* Achieved high validation accuracy using basic CNN architecture.
* Visualized predictions and loss/accuracy graphs for evaluation.
---
## 📚 Learning Objectives
* Understand the full workflow of image classification with CNNs.
* Learn how to preprocess and augment image datasets.
* Gain hands-on experience with Keras for binary classification.
---
## 👨💻 Author
**Haseeb Ul Hassan**
GitHub: [@HaseebUlHassan437](https://github.com/HaseebUlHassan437)
---
## 📜 License
Licensed under the **MIT License** — feel free to use and adapt this project.
---
Let me know if you want a **Colab badge**, or I can also add **model performance graphs** to the README.