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README.md
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---
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license: cc-by-4.0
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task_categories:
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- image-to-image
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- image-classification
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tags:
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- microscopy
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- electron-microscopy
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- HAADF-STEM
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- simulation
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- materials-science
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- crystallography
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- webdataset
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size_categories:
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- n<1K
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configs:
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- config_name: default
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data_files:
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- split: train
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path: "train-*.tar"
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---
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# Atomagined Dataset (WebDataset)
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Simulated atomic-resolution HAADF-STEM images from the [atomagined](https://github.com/MaterialEyes/atomagined) dataset. Each image is a 256x256 simulation of a unique ICSD crystal structure prototype viewed along a specific crystallographic direction, with various post-processing distortion conditions applied.
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## Dataset Description
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This is a WebDataset conversion of the atomagined proxy dataset (subset available via GitHub). The full dataset (~67,871 images) is hosted on the [Materials Data Facility](https://doi.org/10.18126/szeq-yde5). This version contains 299 samples from 61 unique structure/orientation combinations across three subsets: general simulations, retrieval targets, and retrieval choices.
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Each h5 file in the original data contains multiple distortion variants of the same simulation. These have been flattened so that each (structure, distortion) pair is an individual sample.
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## Format
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WebDataset format: 1 TAR shard, 76 MB total.
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Each sample in the shard contains:
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- `{idx:06d}.npy` — 256x256 float32 HAADF-STEM image
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- `{idx:06d}.json` — metadata
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### Metadata Fields
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| Field | Type | Description |
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|-------|------|-------------|
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| `ref_id` | string | Reference ID: `{ICSD_CollCode}.{uvw_encoding}` |
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| `subset` | string | Dataset subset: `general`, `targets`, or `choices` |
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| `distortion` | string | Distortion condition (e.g., `raw`, `stem00-clean`, `stem00-blur1`, `stem00-cnts2`) |
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| `width` | int | Image width (256) |
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| `height` | int | Image height (256) |
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| `min_value` | float | Minimum pixel intensity |
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| `max_value` | float | Maximum pixel intensity |
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| `mean_value` | float | Mean pixel intensity |
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| `std_value` | float | Standard deviation of pixel intensity |
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| `icsd_id` | string | ICSD collection code |
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| `chemical_name` | string | Systematic chemical name |
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| `chemical_formula` | string | Structural chemical formula |
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| `structure_type` | string | Crystal structure type |
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| `space_group` | string | Space group name |
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| `space_group_number` | string | International Tables space group number |
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| `uvw_orient` | string | Viewing direction [u,v,w] |
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| `hkl_orient` | string | Miller indices of the viewing plane |
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| `n_atoms_projected` | int | Number of atom columns in the projection |
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### Distortion Conditions
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| Code | Description |
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|------|-------------|
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| `raw` | Raw simulation output |
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| `stem00-clean` | Clean (no distortion) |
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| `stem00-blur{1,2}` | Gaussian blur (two levels) |
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| `stem00-cnts{1,2}` | Count noise / Poisson noise |
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| `stem00-scan{1,2}` | Scan distortion |
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| `stem00-bkgd{1,2}` | Background noise |
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| `stem00-dfct{1,2}` | Structural defects |
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| `stem00-blbk{1,2}` | Blur + background combined |
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| `stem01-comb1` | Combined distortion level 1 |
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| `stem02-comb2` | Combined distortion level 2 |
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## Usage
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```python
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import webdataset as wds
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import numpy as np
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from torch.utils.data import DataLoader
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url = "path/to/atomagined_wds/train-0000.tar"
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dataset = wds.WebDataset(url).decode()
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dataloader = DataLoader(dataset, batch_size=32, num_workers=2)
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for sample in dataloader:
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image = sample[".npy"] # 256x256 float32
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metadata = sample[".json"] # dict with ICSD info, distortion type, etc.
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```
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## Source
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Original data from [MaterialEyes/atomagined](https://github.com/MaterialEyes/atomagined). Full dataset on [Materials Data Facility](https://doi.org/10.18126/szeq-yde5).
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## Citation
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Schwenker, E. et al. *Image Matching for Computer Vision in Atomic-Resolution Electron Microscopy*, 2020.
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## License
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CC-BY-4.0
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train-0000.tar
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@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:faf1999d1c6d45716e1c007af51a9a26cc78a513622968ab2485baedec164c0a
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size 79063040
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