Duplicate from PatSnap/design-fto-bench

Co-authored-by: duankai <kaneduan@users.noreply.huggingface.co>

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README.md

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+---
+license: cc-by-nc-4.0
+language:
+- en
+- zh
+tags:
+- patent
+- design-patent
+- freedom-to-operate
+- fto
+- image-retrieval
+- cross-modal
+- visual-similarity
+- information-retrieval
+- evaluation
+- benchmark
+task_categories:
+- image-to-image
+- image-classification
+pretty_name: PatSnap Design FTO Bench
+size_categories:
+- n<1K
+configs:
+- config_name: default
+  data_files:
+  - split: test
+    path: data/test.parquet
+dataset_info:
+  features:
+  - name: id
+    dtype: int64
+  - name: query_img_id
+    dtype: string
+  - name: query_pn
+    dtype: string
+  - name: query_img_path
+    dtype: image
+  - name: target_pns
+    sequence: string
+  - name: target_img_ids
+    sequence: string
+  - name: pair_name
+    dtype: string
+  - name: picture_type
+    dtype: string
+  - name: one_level_loc
+    dtype: string
+  - name: two_level_loc
+    dtype: string
+  - name: country
+    sequence: string
+  - name: version
+    dtype: string
+  splits:
+  - name: test
+    num_examples: 91
+---
+
+# PatSnap Design FTO Bench
+
+A Bench for evaluating **design patent Freedom-To-Operate (FTO)** retrieval systems on cross-modal image search. Each sample provides a query product image (or design patent figure) plus the ground truth set of target design patents that constitute infringement risk, as confirmed by patent invalidation proceedings.
+
+> 🐙 **GitHub mirror:** This dataset is also published as part of the [`patsnap/patent-bench`](https://github.com/patsnap/patent-bench/tree/main/design-fto-bench) monorepo, where you can find the reference metric scripts (`search_metrics.py`) and additional sub-Benches.
+
+## Dataset Overview
+
+| Property | Value |
+|----------|-------|
+| **Total samples** | 91 |
+| **Source** | Real patent invalidation proceedings |
+| **Jurisdictions** | CN (100% for the released subset) |
+| **Modality** | PNG images (product photo ↔ patent line drawing / photo) |
+| **Image directory** | `data/image/<jurisdiction>/<class>/<sub>/<pn>/<file>.png` (91 PNG files, ~6.8 MB) |
+| **Ground truth** | Patent pairs confirmed as infringement-equivalent through patent invalidation proceedings |
+| **Locarno (LOC) coverage** | All 26 first-level LOC classes |
+| **License** | CC BY-NC 4.0 |
+
+## Quick Start
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("PatSnap/design-fto-bench", split="test")
+print(f"Total samples: {len(ds)}")
+
+# Inspect one sample
+sample = ds[0]
+print(sample["query_pn"], sample["pair_name"])
+
+# query_img_path is a PIL Image (bytes embedded in the Parquet, no external lookup needed)
+img = sample["query_img_path"]
+print(f"Query image: {img.size}, mode={img.mode}")
+
+# Targets are the set of design patents whose images constitute infringement risk
+print(sample["target_pns"], sample["target_img_ids"])
+```
+
+## Data Fields
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `id` | int64 | Sample identifier |
+| `query_img_id` | string | Identifier of the query image |
+| `query_pn` | string | Publication number of the query patent (PatSnap standardized PN) |
+| `query_img_path` | string | Relative path to the query image under `data/image/` |
+| `target_pns` | list[string] | Ground truth target design-patent PNs that constitute infringement risk |
+| `target_img_ids` | list[string] | Image identifiers of the target patents |
+| `pair_name` | string | Pair identifier from the invalidation proceeding |
+| `picture_type` | string | Source of the GT pair (e.g. 无效 = invalidation proceeding) |
+| `one_level_loc` | string | First-level Locarno classification code |
+| `two_level_loc` | string | Second-level Locarno classification code (e.g. 14-03) |
+| `country` | list[string] | Country/jurisdiction codes of the sample |
+| `version` | string | Dataset version (e.g. 1.1) |
+
+## How to Use the Query
+
+The query input is the **query product image** at `data/image/<query_img_path>`. Each sample's `target_pns` lists the design patents that an FTO retrieval system should return.
+
+## Evaluation Metrics
+
+| Metric | Description |
+|--------|-------------|
+| **Hit Rate @ K** | % of samples with ≥1 GT patent in top K (K = 10, 50, 100, 200) |
+| **PRES @ N** | Patent Retrieval Evaluation Score (Magdy & Jones 2010, with miss-penalty correction): single score in `[0, 1]` jointly capturing how many GT patents are retrieved within top-N and how highly they are ranked. PRES = 1.0 means every GT patent appears at the top; PRES = 0 means none are found within N. Default N = 200. |
+
+The reference metric scripts (with `strict / leaderboard` mode by default and ranked-list schema validation) are available in the [`patsnap/patent-bench`](https://github.com/patsnap/patent-bench/blob/main/common/metrics/search_metrics.py) GitHub repo.
+
+### Scoring Grades (Hit Rate @ Top@100)
+
+| Grade | Hit Rate | Description |
+|-------|----------|-------------|
+| **A** | ≥ 90% | Excellent — suitable for direct professional use |
+| **B** | ≥ 75% | Good — effective as a high-efficiency screening tool |
+| **C** | ≥ 60% | Acceptable — requires human review of key results |
+| **D** | < 60% | Below standard — model improvement needed |
+
+## Distribution
+
+### By Jurisdiction
+
+| Jurisdiction | Count | Percentage |
+|--------------|-------|------------|
+| CN | 91 | 100% |
+
+> The v1.1 public release contains only invalidation-proceeding samples (CN). Future releases (v2) will incorporate cross-jurisdiction TRO data (US/EP/JP).
+
+### By Locarno Classification
+
+Coverage spans all 26 first-level LOC classes.
+
+## Limitations
+
+- **Retrieval-only Bench**: Evaluates the search/retrieval step only; does not cover infringement adjudication or court-ruling outcomes.
+- **GT based on invalidation proceedings**: This subset (v1.1) is restricted to CN invalidation-proceeding pairs. E-commerce infringement-complaint samples are retained internally for client confidentiality.
+- **Single-jurisdiction**: CN only in this release.
+- **Visual similarity ≠ legal infringement**: A retrieval system returning a top-1 hit does not constitute a legal infringement determination; results are inputs to professional FTO review.
+
+## Citation
+
+```bibtex
+@dataset{patsnap_design_fto_bench_2026,
+  title  = {PatSnap Design FTO Bench},
+  author = {PatSnap},
+  year   = {2026},
+  url    = {https://huggingface.co/datasets/PatSnap/design-fto-bench},
+  note   = {A Bench for evaluating design-patent freedom-to-operate image-retrieval systems}
+}
+```
+
+## License
+
+Released under [CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/) — research and non-commercial evaluation purposes only.
+
+## Try the Production System
+
+Experience the **PatSnap Design FTO AI Agent** — the commercial system referenced in this Bench.
+
+🔗 [Try it on PatSnap Eureka](https://eureka.patsnap.com/ip/checking/?from=benchmark_huggingface#/design-fto)