Image Classifier with TensorFlow (CIFAR-10)

A simple deep learning project using a Convolutional Neural Network (CNN) trained on the CIFAR-10 dataset. It classifies custom images (like cars, trucks, cats, etc.) using a pre-trained TensorFlow model.

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Dataset

• CIFAR-10: 60,000 images across 10 categories
• Classes: Plane, Car, Bird, Cat, Deer, Dog, Frog, Horse, Ship, Truck

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Technologies Used

• Python
• TensorFlow / Keras
• OpenCV
• NumPy
• Matplotlib

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Project Structure

image-classifier-tensorflow/ ├── classifier.py # Main prediction script ├── Image Classification/ │ ├── image_classifier.keras # Pretrained model │ ├── car.jpg # Sample test image ├── README.md

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How It Works

• Loads CIFAR-10 dataset (optional for reference)
• Loads pre-trained .keras model
• Reads and resizes a custom image (e.g., car.jpg)
• Normalizes the image
• Runs prediction and displays the predicted class

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How to Run

git clone https://github.com/mahiyafatema/image-classifier-tensorflow.git
cd image-classifier-tensorflow
pip install tensorflow opencv-python matplotlib numpy
python classifier.py

### Make sure your .keras model file and image (car.jpg) are in the correct folder as specified in the script.

## Example Output
Prediction is Car


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If you want, I can generate this as a markdown file for you to upload — or help you add a section like "Future Improvements" or "Contact Info." Would you like that?