v1.0

🖼️ ImageClassify-CIFAR10 – v1.0 Release

📅 Release Date

April 20, 2025

---

🧠 Overview

This is the v1.0 release of ImageClassify-CIFAR10 — a deep learning-based image classification project that uses the CIFAR-10 dataset to accurately identify and categorize images across 10 distinct object classes.

---

✨ Key Features

🔍 CIFAR-10 Dataset Support

Trained on the CIFAR-10 dataset containing 60,000 32x32 color images across 10 categories:
airplane, automobile, bird, cat, deer, dog, frog, horse, ship, truck.

🧠 Deep Learning Model

• Built using Convolutional Neural Networks (CNNs).
• Trained and evaluated using TensorFlow/Keras.
• Achieves high classification accuracy on test data.

📈 Model Performance

• Detailed performance metrics including accuracy, loss, and confusion matrix.
• Real-time training graphs and validation curves.

🖼️ Image Prediction Interface

• Load a custom image and receive predicted label with confidence score.
• Preprocessing pipeline included for resizing and normalization.

---

⚙️ Tech Stack

• Language: Python
• Frameworks: TensorFlow / Keras
• Libraries: numpy, matplotlib, sklearn, PIL
• Dataset: CIFAR-10 (via keras.datasets)

---

🐛 Known Limitations

• Image input must be resized to 32x32 for predictions.
• Model accuracy may vary based on training epochs and batch size.
• Not optimized for deployment (v1.0 focuses on training and evaluation only).

---

🚀 What's Next (Planned for v1.1)

• Web-based interface for real-time image upload and prediction.
• Transfer learning with pre-trained models (e.g., ResNet, MobileNet).
• Model export as TensorFlow Lite for mobile inference.
• Support for CIFAR-100 and custom datasets.

---

🙌 Contributors

• Shashwat – Model design, training, evaluation, and visualization