Add: [AI-ML] Image Classifier using Transfer Learning with MobileNetV2 - #51
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Tejas-Santosh-Nalawade merged 1 commit intoOct 20, 2025
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Features: - Pre-trained MobileNetV2 model with ImageNet weights (1000+ categories) - Beautiful Streamlit web interface with responsive design - Real-time image classification with top-5 predictions - Confidence scores with visual progress bars and color-coded indicators - Drag & drop image upload (JPG, PNG, JPEG support) - Automatic image preprocessing and normalization - Model information display (parameters, layers, inference time) - Transfer learning implementation for accurate predictions - Lightweight and fast inference (~30-50ms per image) - Comprehensive error handling and user feedback - Test script included for setup verification Tech Stack: Python, TensorFlow 2.x, Keras, MobileNetV2, Streamlit, Pillow, NumPy Use Cases: Object recognition, photo organization, content moderation, educational tool Categories: Animals, vehicles, food, objects, nature, instruments, sports, and 900+ more Architecture: MobileNetV2 with Inverted Residuals (3.5M parameters) Performance: ~71.8% Top-1 and ~90.8% Top-5 accuracy on ImageNet Contributor: vatsalgupta2004
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hi would appreciate a review on it |
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Features:
Tech Stack: Python, TensorFlow 2.x, Keras, MobileNetV2, Streamlit, Pillow, NumPy
Use Cases: Object recognition, photo organization, content moderation, educational tool
Categories: Animals, vehicles, food, objects, nature, instruments, sports, and 900+ more
Architecture: MobileNetV2 with Inverted Residuals (3.5M parameters)
Performance: ~71.8% Top-1 and ~90.8% Top-5 accuracy on ImageNet
Contributor: vatsalgupta2004