Datasets:
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, an interactive interface for exploring visual features learned by individual neurons in Inception V1.
It combines two complementary interpretability views:
- Activation maximization: one synthesized visualization optimized to strongly activate each neuron.
- 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
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 before downloading, redistributing, or repurposing the natural-image examples.
References
- Szegedy, C. et al. Going Deeper with Convolutions. CVPR 2015. Paper
- Deng, J. et al. ImageNet: A Large-Scale Hierarchical Image Database. CVPR 2009. ImageNet
- Olah, C. et al. The Building Blocks of Interpretability. Distill, 2018. Article
- OpenAI. OpenAI Microscope. Project
Citation
@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}
}