Upload Inception-V1-Microscope-Dataset-README.md

Inception-V1-Microscope-Dataset-README.md

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+---
+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}
+}
+```
+