Datasets:

lsnu
/

circuitgen-datasets-private

open-schematics_hf: reconstructed graph connectivity instead of emitting empty-member nets
netlistify_schematic_images_hf: demoted partial/noisy component-layout supervision unless graph and visual component types match exactly
ams-net.github.io: fixed graph-side transistor typing and demoted partial/noisy component-layout supervision unless graph and visual component types match exactly

This file still documents the raw source dataset structure below; it does not replace the per-version derived CGDSL README under derived/cgdsl/20260307-081439-fix-open-netlistify-ams-overlay/README.md.

1) Open Schematics (two mirrors)

Paths:

/mnt/c/users/luiss/circuitgen/open-schematics
/mnt/c/users/luiss/circuitgen/datasets/open-schematics_hf

Both have the same structure:

open-schematics[_hf]/
  README.md
  .gitattributes
  open-schematics.png
  data/
    train-00000-of-00078.parquet
    ...
    train-00077-of-00078.parquet

Key facts:

78 parquet shards.
Per-row parquet schema:
- schematic: string (schematic source text, typically KiCad)
- image: struct{bytes: binary, path: string} (rendered image bytes + filename)
- components_used: list<string>
- json: string
- yaml: string
- name: string
- description: string
- type: string (example: .kicad_sch)

How to treat:

Primary supervised pair for generation: schematic (or graph derived from it) -> image.bytes.
json, yaml, and components_used are auxiliary metadata/features.

2) Netlistify HF dataset (gated dataset, now pulled)

Path:

/mnt/c/users/luiss/circuitgen/datasets/netlistify_schematic_images_hf

Structure:

netlistify_schematic_images_hf/
  README.md
  .gitattributes
  comoponent_id.txt
  images.zip
  components.zip
  pkl.zip
  sp.zip

Inside archives:

images.zip -> images/circuit<ID>.jpg (100001 entries incl. folder entry)
components.zip -> components/circuit<ID>.txt
pkl.zip -> pkl/circuit<ID>.pkl
sp.zip -> sp_folder_after/circuit<ID>.sp

Canonical sample key:

Integer <ID> in filename (circuit0, circuit1, ...).
Join all modalities by matching this <ID>.

Observed formats:

components/circuit<ID>.txt: YOLO-like component lines + orientation token, e.g.
- <class_id> <x_center> <y_center> <width> <height> <orientation>
pkl/circuit<ID>.pkl: Python dict; keys are net names (net0, gnd, ...), values are lists of line segments like [x1, y1, x2, y2] (normalized coords).
sp_folder_after/circuit<ID>.sp: SPICE/HSPICE text netlist.

How to treat:

Main pair for your task: .sp (graph) + .pkl (net geometry hints) -> .jpg.
components can be used as auxiliary symbol supervision.

3) AMSNet 1.0 (repo + zip + extracted)

Path:

/mnt/c/users/luiss/circuitgen/datasets/ams-net.github.io

Top-level:

ams-net.github.io/
  amsnet_1.0-20240412T024532Z-001.zip        # valid dataset zip
  amsnet_1.0/                                # extracted
    amsnet_1.0/
      0/
      1/
      ...
      733/                                   # 734 circuit folders total
  AMSNet_1_1.ipynb
  README.md
  LICENSE
  index.html
  amsnet_1.0-from-blob.zip                   # HTML artifact from blob URL (ignore)

Per-circuit folder pattern (<N>/):

<N>.cir
<N>.jpg
<N>_bbox.json
<N>_cpnt.jpg
<N>_net.jpg

Observed *_bbox.json format:

JSON object; keys are class+orientation buckets (e.g. nmos_90, resistor_0, net-black_100, ...).
Values are lists of bboxes, each like [xmin, ymin, xmax, ymax].

How to treat:

Core pair for generation: <N>.cir -> <N>.jpg.
<N>_cpnt.jpg, <N>_net.jpg, and <N>_bbox.json are auxiliary supervision.

4) CI2N datasets

Path:

/mnt/c/users/luiss/circuitgen/datasets/ci2n_datasets

Structure:

ci2n_datasets/
  device_identification/
    <ID>.png
    <ID>.json
  device_orientation/
    train_amp_d/{d,l,r,u}/...
    train_amp_m/{0,1}/...
    train_bjt_d/{d,l,r,u}/...
    train_bjt_m/{0,1}/...
    train_diode/{d,l,r,u}/...
    train_mos/{d,l,r,u}/...
    train_switch/{d,l,r,u}/...
    train_voltagelines/{d,l,r,u}/...
  jumper_identification/
    images/{train,val}/...
    labels/{train,val}/...
  validation/
    images/<ID>.png
    golden/<ID>.json
    calc_ged.py
    utils_ged.py

Validation JSON observed keys:

ckt_netlist
ckt_type

How to treat:

Best as auxiliary detection/graph-eval data, not a single unified netlist->render benchmark.

5) Digitize-HCD (zip downloaded, not extracted)

Path:

/mnt/c/users/luiss/circuitgen/datasets/digitize-hcd/Digitize-HCD Dataset.zip

Zip top-level:

Digitize-HCD Dataset/
  Component Symbol and Text Label Data/
    Circuit Diagram Images/circuit_<ID>.jpg
    component_annotations.json
    text_annotations.json
  Component Port Location Data/
    <17 class folders>/
      Input Images/
      Output Heatmaps/
      XY Coordinates/

Observed 17 component class folders under Component Port Location Data:

BJT-NPN, BJT-PNP, Capacitor, Diode, GND, I-AC, I-DC, Inductor, MOSFET-N, MOSFET-P, Op-Amp, Resistor, V-AC, V-DC, V-DC (one-port), Wire Crossover, Zener Diode.

How to treat:

Symbol/text/port localization dataset (handwritten domain).
Not a direct netlist->render pair dataset.

6) SPICE netlist corpus (no paired images)

Path:

/mnt/c/users/luiss/circuitgen/datasets/spice-datasets

Structure:

spice-datasets/
  kicad_github/      # mostly .cir / .cir2 / .cir3
  ltspice_demos/     # .net
  ltspice_examples/  # .net
  README.md
  LICENSE.txt

How to treat:

Topology/netlist source corpus only (good for graph sampling/pretraining).
No direct rendered-image pairing inside this dataset.

7) Netlistify GitHub repo (tooling repo, not the HF dataset)

Path:

/mnt/c/users/luiss/circuitgen/datasets/Netlistify

Structure (top-level):

Netlistify/
  main.py
  main_config.py
  testing.py
  Model.py
  requirements.txt
  final_test/
  Visualizer/
  ...

How to treat:

Code/training pipeline repository.
Use for scripts/model logic, not as a raw dataset directory.

8) CGHD repo clone (metadata only in this checkout)

Path:

/mnt/c/users/luiss/circuitgen/datasets/cghd

Current structure:

cghd/
  .gitattributes
  classes.json
  README.md
  LICENSE

Notes:

.gitattributes marks image extensions as Git LFS-tracked.
This checkout does not currently contain the actual large image/annotation payload.

How to treat:

Metadata/reference only unless full data is later fetched.

9) AMSNet2.0 website repo clone (project page assets)

Path:

/mnt/c/users/luiss/circuitgen/datasets/AMSNet2.0.github.io

Structure:

AMSNet2.0.github.io/
  index.html
  test.html
  static/
    css/
    images/
    js/
    pdfs/
    videos/

How to treat:

Website/project-page assets only.
No dataset payload in this checkout.

10) Placeholder folder from pre-auth attempt

Path:

/mnt/c/users/luiss/circuitgen/datasets/netlistify_schematic_images

Structure:

netlistify_schematic_images/
  README.md

How to treat:

Placeholder from earlier gated-access attempt; not the real downloaded dataset.
Use netlistify_schematic_images_hf/ instead.

11) CGHD full payload from Zenodo (downloaded + extracted)

Path:

/mnt/c/users/luiss/circuitgen/datasets/cghd_zenodo

Structure:

cghd_zenodo/
  cghd-zenodo-4.zip
  extracted/
    README.md
    classes.json
    classes_color.json
    classes_discontinuous.json
    consistency.py
    drafter_1/
    ...
    drafter_22/
      annotations/
      images/
      instances/
      segmentation/
      spice/            # present for some drafters/samples

Observed size/details:

cghd-zenodo-4.zip is ~2.3 GB.
extracted/ is ~2.4 GB.
extracted/ currently contains 4700 files.

How to treat:

This is the actual full CGHD payload to use for training/eval.
Primarily handwritten symbol/box/segmentation supervision with some SPICE netlist coverage.

12) CGHD HF mirror snapshot (partial local pull)

Path:

/mnt/c/users/luiss/circuitgen/datasets/cghd_hf

Structure currently present:

cghd_hf/
  .cache/huggingface/
  README.md
  classes.json
  classes_color.json
  classes_discontinuous.json
  classes_ports.json
  consistency.py
  drafter_-1/
  drafter_0/

Notes:

This local copy is partial due HF rate-limited snapshot attempts during pull.
Prefer cghd_zenodo/extracted/ as canonical CGHD data.

How to treat:

Reference/partial mirror only.

13) CircuitSense-6k (HF clone)

Path:

/mnt/c/users/luiss/circuitgen/datasets/Circuitsense-6k_hf

Structure:

Circuitsense-6k_hf/
  .gitattributes
  q1/
    q1_image.png
    q1_netlist.txt
    q1_question.txt
    q1_ta.txt
  q2/
  ...

Observed details:

Git-tracked files: 25197.
Current local checkout completeness: missing=0 (all tracked files present).
Directory count with q<ID>/: 6299.
Example netlist format is SPICE-like plain text lines.
Question files ask transfer-function-style queries; q*_ta.txt holds answer text.

How to treat:

Useful paired supervision: q*_netlist.txt + q*_image.png.
QA fields are auxiliary tasks/features.

14) CircuitSense TransferFunction-only subset (HF clone)

Path:

/mnt/c/users/luiss/circuitgen/datasets/CircuitSense-100-TF_hf

Structure:

CircuitSense-100-TF_hf/
  .gitattributes
  q<ID>/
    q<ID>_image.png
    q<ID>_netlist.txt
    q<ID>_question.txt
    q<ID>_ta.txt

Observed details:

Git-tracked files: 397.
Current local checkout completeness: missing=0.

How to treat:

Small TF-focused subset; good for quick sanity checks/evaluation.

15) CircuitVQA (HF clone)

Path:

/mnt/c/users/luiss/circuitgen/datasets/circuitvqa_hf

Structure:

circuitvqa_hf/
  .gitattributes
  images/*.jpg
  mapping_report.json
  train.jsonl
  val.jsonl
  test.jsonl

Observed details:

Git-tracked files: 5432.
Current local checkout completeness: missing=0.
Image count (images/*.jpg): 5425.
mapping_report.json indicates total=115582 QA rows and matched=115582.
JSONL rows include fields:
- image, question, answer, qtype, symbol.

How to treat:

Circuit visual QA supervision (count/value/position/symbol reasoning).
Not a direct netlist->render benchmark by itself.

16) CircuitVQADesc (HF clone)

Path:

/mnt/c/users/luiss/circuitgen/datasets/circuitvqadesc_hf

Structure:

circuitvqadesc_hf/
  .gitattributes
  images/*.jpg
  mapping_report.json
  train.jsonl
  val.jsonl
  test.jsonl

Observed details:

Git-tracked files: 5430.
Current local checkout completeness: missing=0.
Image count (images/*.jpg): 5425.

How to treat:

Same family as CircuitVQA; auxiliary circuit reasoning/description supervision.

17) LTspice SPICE<->ASC paired datasets (HF clones)

Paths:

/mnt/c/users/luiss/circuitgen/datasets/ltspice-spice-circuits_hf
/mnt/c/users/luiss/circuitgen/datasets/ltspice-spice-circuits-no-aug_hf

Shared structure:

ltspice-spice-circuits*_hf/
  README.md
  .gitattributes
  data/
    train-00000-of-00001.parquet
    test-00000-of-00001.parquet

Parquet schema:

netlist: string
asc: string (LTspice schematic text format)

Observed split sizes:

ltspice-spice-circuits_hf: train 53000, test 2790.
ltspice-spice-circuits-no-aug_hf: train 7866, test 414.

How to treat:

Strong text-to-text grounded dataset for schematic layout representation learning.
Good source for parser pretraining and graph-aware intermediate objectives.

18) Masala-CHAI repo + external payloads

Path:

/mnt/c/users/luiss/circuitgen/datasets/Masala-CHAI

Structure now present:

Masala-CHAI/
  README.md
  main.py
  Dataset/
    data_1/
    data_2/
    data_3/
    data_4/
    data_5/
  external_downloads/
    masala-chai-dataset.zip
    hough-assets.zip
  dataset_payload/
    masala-chai-dataset-new/
      images/img<ID>.jpg
      spice/spice<ID>.txt
      captions/cap<ID>.txt
  hough_payload/
    hough/htlcnn/...

Observed counts (external dataset payload):

images/: 6371 files.
spice/: 6069 files.
captions/: 6403 files.

Notes:

The three modalities are not identical in count; join by numeric <ID> intersection.
Repo Dataset/data_* folders are additional image collections from project sources.

How to treat:

spice + images are useful for netlist-conditioned tasks.
captions can support multimodal/description-side supervision.

19) Lessons in Electric Circuits source packs (textbook assets)

Path:

/mnt/c/users/luiss/circuitgen/datasets/lessons-in-electric-circuits

Structure:

lessons-in-electric-circuits/
  liechtml.tar.gz
  liecsrc.tar
  liectiny.tar
  extracted_html/
    AC/ DC/ Devel/ Digital/ Exper/ Ref/ Semi/
  extracted_src/
    AC/ DC/ Devel/ Digital/ Exper/ Ref/ Semi/ bin/
  extracted_tiny/
    AC/ DC/ Devel/ Digital/ Exper/ Ref/ Semi/ bin/

Observed counts:

extracted_html/: 4034 files.
extracted_src/: 98 files.
extracted_tiny/: 98 files.
Image assets inside extracted_html/ (png/jpg/jpeg/gif/svg): 3632.

How to treat:

Style/reference corpus for textbook-like circuit figures.
Not directly paired with machine-readable netlists in this dump.

20) kicad-library (CircuitSnips platform repo clone)

Path:

/mnt/c/users/luiss/circuitgen/datasets/kicad-library

Structure:

kicad-library/
  README.md
  package.json
  src/
  public/
  scripts/
  supabase/
  ...

Observed notes:

This is the web/platform codebase clone.
This checkout currently has 0 .kicad_sch files.
The scraped corpus referenced in the README is not embedded as raw dataset files in this repo clone.

How to treat:

Tooling/reference repository only unless separate circuit payload export is added.