ernestoBocini/clip-microscope-imagenet

CLIP Microscope ImageNet Dataset

This dataset contains the top activating ImageNet images for each neuron in OpenAI's CLIP RN50x4 model, designed for use with neural network interpretability tools.

Dataset Structure

clip-microscope-imagenet/
├── neurons/                    # Top activating images per neuron
│   ├── neuron_0000/           # Images for neuron 0
│   │   ├── train_rank_00_act_0.8234_idx_12345.jpg
│   │   ├── val_rank_01_act_0.7891_idx_67890.jpg
│   │   └── ...
│   ├── neuron_0001/           # Images for neuron 1
│   └── ...
├── lucid/                     # Lucid-generated feature visualizations
│   ├── neuron_0000_lucid.png
│   ├── neuron_0001_lucid.png
│   └── ...
└── metadata/                  # Dataset metadata and statistics
    ├── neuron_metadata.json   # Detailed neuron information
    ├── dataset_summary.json   # High-level statistics
    └── neuron_summary.csv     # Tabular summary

Usage

This dataset is designed to work with the CLIP Microscope web application. You can access images directly via URLs:

# Base URL
BASE_URL = "https://huggingface.co/datasets/your-username/clip-microscope-imagenet/resolve/main"

# Access neuron images
neuron_image_url = f"{BASE_URL}/neurons/neuron_0123/train_rank_00_act_0.8234_idx_12345.jpg"

# Access lucid images
lucid_image_url = f"{BASE_URL}/lucid/neuron_0123_lucid.png"

Model Information

• Model: OpenAI CLIP RN50x4
• Layer: Image encoder blocks
• Total Neurons: 2560
• Images per Neuron: Up to 100 (top activating)
• Source Dataset: ImageNet (train and validation splits)

File Naming Convention

Neuron Images

{split}_rank_{rank:02d}_act_{activation:.4f}_idx_{original_index}.{ext}

• split: "train" or "val"
• rank: Ranking among top activations (00 = highest)
• activation: Neuron activation value
• original_index: Index in the original ImageNet dataset

Lucid Images

neuron_{neuron_id:04d}_lucid.png

Citation

If you use this dataset, please cite:

• The original CLIP paper: Radford et al., "Learning Transferable Visual Representations"
• ImageNet: Deng et al., "ImageNet: A Large-Scale Hierarchical Image Database"

License

This dataset follows the ImageNet license terms. Please ensure compliance with ImageNet's usage guidelines.