HSinghHuggingFace/resnet50-image-classifier

ResNet50 Image Classifier

This Streamlit application uses a ResNet50 model trained on the ImageNet-1K dataset to classify images into 1000 different categories.

How to Use

1. 1.Click the "Choose an image..." button or drag and drop an image
2. 2.The model will automatically process your image
3. 3.View the top 5 predictions with their confidence scores

Model Details

• —Architecture: ResNet50
• —Dataset: ImageNet-1K
• —Input Size: 224x224 pixels
• —Number of Classes: 1000

Example Predictions

The model can identify various objects, animals, and scenes, including:

• —Common animals (dogs, cats, birds)
• —Everyday objects
• —Vehicles
• —Natural scenes
• —And many more!

Technical Details

• —Built with PyTorch and Streamlit
• —Uses standard ImageNet preprocessing
• —Runs inference on CPU
• —Displays confidence scores as progress bars

Note

For best results, use clear, well-lit images with a single main subject.