| --- |
| pretty_name: Inception V1 Microscope Data |
| tags: |
| - computer-vision |
| - interpretability |
| - feature-visualization |
| dataset_info: |
| - config_name: activation_maximization |
| features: |
| - name: model |
| dtype: string |
| - name: layer |
| dtype: string |
| - name: channel |
| dtype: int32 |
| - name: neuron_id |
| dtype: string |
| - name: original_filename |
| dtype: string |
| - name: image |
| dtype: image |
| splits: |
| - name: train |
| num_bytes: 1408434214 |
| num_examples: 5804 |
| download_size: 2518344881 |
| dataset_size: 1408434214 |
| - config_name: dataset_examples |
| features: |
| - name: model |
| dtype: string |
| - name: layer |
| dtype: string |
| - name: channel |
| dtype: int32 |
| - name: neuron_id |
| dtype: string |
| - name: rank |
| dtype: int16 |
| - name: activation_score |
| dtype: float32 |
| - name: source_image_id |
| dtype: string |
| - name: full_image |
| dtype: image |
| - name: crop_image |
| dtype: image |
| splits: |
| - name: conv2d0 |
| num_bytes: 8843639 |
| num_examples: 640 |
| - name: conv2d1 |
| num_bytes: 8867534 |
| num_examples: 640 |
| - name: conv2d2 |
| num_bytes: 25732765 |
| num_examples: 1920 |
| - name: mixed3a |
| num_bytes: 34633461 |
| num_examples: 2560 |
| - name: mixed3b |
| num_bytes: 63885612 |
| num_examples: 4800 |
| - name: mixed4a |
| num_bytes: 64855685 |
| num_examples: 5080 |
| - name: mixed4b |
| num_bytes: 63178857 |
| num_examples: 5120 |
| - name: mixed4c |
| num_bytes: 63797176 |
| num_examples: 5120 |
| - name: mixed4d |
| num_bytes: 63804127 |
| num_examples: 5280 |
| - name: mixed4e |
| num_bytes: 97750616 |
| num_examples: 8320 |
| - name: mixed5a |
| num_bytes: 99572465 |
| num_examples: 8320 |
| - name: mixed5b |
| num_bytes: 122531881 |
| num_examples: 10240 |
| download_size: 726255360 |
| dataset_size: 717453818 |
| configs: |
| - config_name: activation_maximization |
| data_files: |
| - split: train |
| path: activation_maximization/train-* |
| - config_name: dataset_examples |
| data_files: |
| - split: conv2d0 |
| path: dataset_examples/conv2d0-* |
| - split: conv2d1 |
| path: dataset_examples/conv2d1-* |
| - split: conv2d2 |
| path: dataset_examples/conv2d2-* |
| - split: mixed3a |
| path: dataset_examples/mixed3a-* |
| - split: mixed3b |
| path: dataset_examples/mixed3b-* |
| - split: mixed4a |
| path: dataset_examples/mixed4a-* |
| - split: mixed4b |
| path: dataset_examples/mixed4b-* |
| - split: mixed4c |
| path: dataset_examples/mixed4c-* |
| - split: mixed4d |
| path: dataset_examples/mixed4d-* |
| - split: mixed4e |
| path: dataset_examples/mixed4e-* |
| - split: mixed5a |
| path: dataset_examples/mixed5a-* |
| - split: mixed5b |
| path: dataset_examples/mixed5b-* |
| --- |
| |
| # Inception V1 Microscope Data |
|
|
| This dataset powers the [Inception V1 |
| Microscope](https://huggingface.co/spaces/akankshanc/inception-v1-microscope), |
| an interactive interface for exploring visual features learned by individual |
| neurons in Inception V1. |
|
|
| It combines two complementary interpretability views: |
|
|
| 1. **Activation maximization:** one synthesized visualization optimized to |
| strongly activate each neuron. |
| 2. **Top dataset examples:** the ten ImageNet examples producing the strongest |
| recorded activations for each neuron, paired with crops associated with the |
| activating regions. |
|
|
| These visualizations are evidence about model behavior, not definitive semantic |
| labels for neurons. |
|
|
| ## Dataset scale |
|
|
| The production release covers **5,804 neurons across 12 layers**. |
|
|
| | Layer | Channels | Activation visualizations | Ranked FULL/CROP pairs | |
| | --- | ---: | ---: | ---: | |
| | `conv2d0` | 64 | 64 | 640 | |
| | `conv2d1` | 64 | 64 | 640 | |
| | `conv2d2` | 192 | 192 | 1,920 | |
| | `mixed3a` | 256 | 256 | 2,560 | |
| | `mixed3b` | 480 | 480 | 4,800 | |
| | `mixed4a` | 508 | 508 | 5,080 | |
| | `mixed4b` | 512 | 512 | 5,120 | |
| | `mixed4c` | 512 | 512 | 5,120 | |
| | `mixed4d` | 528 | 528 | 5,280 | |
| | `mixed4e` | 832 | 832 | 8,320 | |
| | `mixed5a` | 832 | 832 | 8,320 | |
| | `mixed5b` | 1,024 | 1,024 | 10,240 | |
| | **Total** | **5,804** | **5,804** | **58,040** | |
|
|
| Each ranked pair contains two images, giving **116,080 natural-image and crop |
| records**, in addition to the 5,804 synthesized activation visualizations. |
|
|
| ## Configurations |
|
|
| ### `activation_maximization` |
| |
| This configuration contains one row per neuron. |
| |
| | Field | Type | Description | |
| | --- | --- | --- | |
| | `model` | string | Model identifier (`inception_v1`) | |
| | `layer` | string | Selected layer | |
| | `channel` | int32 | Zero-indexed channel number | |
| | `neuron_id` | string | Stable layer/channel identifier | |
| | `original_filename` | string | Source visualization filename | |
| | `image` | image | Activation-maximization visualization | |
|
|
| The configuration uses the split name `train` as a Hugging Face storage label. |
| These records are visualizations and are not a model-training set. |
|
|
| ### `dataset_examples` |
| |
| This configuration uses one split per layer and contains ten rows per neuron. |
| Each row keeps the full source image and its crop together. |
| |
| | Field | Type | Description | |
| | --- | --- | --- | |
| | `model` | string | Model identifier (`inception_v1`) | |
| | `layer` | string | Selected layer | |
| | `channel` | int32 | Zero-indexed channel number | |
| | `neuron_id` | string | Stable layer/channel identifier | |
| | `rank` | int16 | Rank from 1 through 10 within the neuron | |
| | `activation_score` | float32 | Raw response used for within-neuron ranking | |
| | `source_image_id` | string | ImageNet source identifier | |
| | `full_image` | image | Full natural image | |
| | `crop_image` | image | Crop associated with the activating region | |
|
|
| ## Example |
|
|
| ```python |
| from datasets import load_dataset |
| |
| activation = load_dataset( |
| "akankshanc/inception-v1-microscope-data", |
| "activation_maximization", |
| split="train", |
| ) |
| |
| mixed4a_examples = load_dataset( |
| "akankshanc/inception-v1-microscope-data", |
| "dataset_examples", |
| split="mixed4a", |
| ) |
| |
| neuron = mixed4a_examples.filter( |
| lambda row: row["channel"] == 254 |
| ).sort("rank") |
| |
| print(neuron) |
| ``` |
|
|
| ## Methodology |
|
|
| ### Activation maximization |
|
|
| Each synthesized image was produced by optimizing a parameterized input to |
| increase the response of one selected Inception V1 channel. The resulting image |
| provides a visual hypothesis about patterns that strongly excite that neuron |
| under the chosen optimization procedure. |
|
|
| ### Dataset examples |
|
|
| Natural images were scored for each neuron. The ten highest-scoring examples |
| were retained and ordered by raw activation score. Each full image was paired |
| with a precomputed crop associated with its strongly activating region. |
|
|
| ## Validation |
|
|
| The release was checked for: |
|
|
| - 5,804 activation-maximization rows; |
| - exactly ten ranked example pairs per neuron; |
| - expected row counts for all 12 layer splits; |
| - matching model, layer, channel, and neuron identifiers; |
| - complete rank sets from 1 through 10; |
| - presence of both FULL and CROP image fields; |
| - correct first and last records at every layer boundary; and |
| - image URL availability through the Hugging Face Dataset Viewer API. |
|
|
| ## Intended use |
|
|
| This dataset is intended for non-commercial research and educational work on: |
|
|
| - neural-network interpretability; |
| - feature visualization; |
| - qualitative analysis of convolutional representations; |
| - interpretability interfaces and teaching demonstrations; and |
| - comparisons between synthesized features and natural-image evidence. |
|
|
| ## Limitations |
|
|
| - A visualization is an interpretability aid, not a definitive neuron label or |
| complete causal explanation. |
| - Activation-maximization results depend on the checkpoint, objective, |
| parameterization, regularization, and optimization procedure. |
| - Top examples characterize the evaluated image collection and may not cover |
| every pattern that activates a neuron. |
| - Crops can omit contextual information that contributes to the full-image |
| response. |
| - Raw activation scores are suitable for ranking examples within a neuron but |
| should not be compared directly across layers or channels. |
| - The natural-image examples inherit biases and coverage limitations from |
| ImageNet. |
|
|
| ## Data provenance and terms |
|
|
| The natural-image examples are derived from ImageNet and are provided for |
| non-commercial research and educational interpretability work. ImageNet does |
| not own the copyright in the underlying images; individual images may remain |
| subject to their original copyright and applicable ImageNet access terms. This |
| repository does not relicense those source images. |
|
|
| Review the [ImageNet terms of |
| access](https://www.image-net.org/download.php) before downloading, |
| redistributing, or repurposing the natural-image examples. |
|
|
| ## References |
|
|
| - Szegedy, C. et al. **Going Deeper with Convolutions.** CVPR 2015. |
| [Paper](https://arxiv.org/abs/1409.4842) |
| - Deng, J. et al. **ImageNet: A Large-Scale Hierarchical Image Database.** |
| CVPR 2009. [ImageNet](https://www.image-net.org/) |
| - Olah, C. et al. **The Building Blocks of Interpretability.** Distill, 2018. |
| [Article](https://distill.pub/2018/building-blocks/) |
| - OpenAI. **OpenAI Microscope.** |
| [Project](https://microscope.openai.com/) |
|
|
| ## Citation |
|
|
| ```bibtex |
| @misc{devkar_inception_v1_microscope_data_2026, |
| author = {Akanksha Devkar}, |
| title = {Inception V1 Microscope Data}, |
| year = {2026}, |
| howpublished = {Hugging Face Dataset}, |
| url = {https://huggingface.co/datasets/akankshanc/inception-v1-microscope-data} |
| } |
| ``` |
|
|
|
|
