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README.md

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+---
+language:
+- en
+pretty_name: SnapBench
+tags:
+- multimodal
+- image-text-retrieval
+- retrieval
+- robustness
+- benchmark
+size_categories:
+- 10K<n<100K
+configs:
+- config_name: queries
+  data_dir: queries
+  default: true
+- config_name: gallery
+  data_dir: gallery
+---
+
+Source repository: <https://github.com/zrchen03/SnapBench>
+
+# SnapBench: Benchmarking Snap-and-Ask Multimodal Retrieval for Mobile Interactions
+
+SnapBench is a benchmark for **snap-and-ask** mobile interactions: a user captures a photo and asks a short English question. Each query pairs an image with text; the gallery contains image–caption pairs to retrieve from. The benchmark includes a clean split plus text and image perturbations to simulate real-world query degradation.
+
+| | |
+|---|---|
+| Queries | 1,145 (image + text) |
+| Gallery | 9,085 items (image + caption) |
+| Conditions | 54 (1 clean + 8 text + 45 image perturbations) |
+
+This repository ships the clean benchmark in the standard Hugging Face `ImageFolder` format. It includes the clean query and gallery images, retrieval annotations, and perturbation metadata. It does not include evaluation code.
+
+---
+
+## What Is Included
+
+| Component | Location | Status |
+|---|---|---|
+| Query metadata | `queries/test/metadata.jsonl` | included |
+| Query images | `queries/test/images/` (1,145) | included |
+| Gallery metadata | `gallery/test/metadata.jsonl` (9,085 items) | included |
+| Gallery images | `gallery/test/images/` (9,059 unique images) | included |
+| Text perturbations | `queries/test/metadata.jsonl` → `text_perturbations` | included |
+| Image perturbation specifications | `queries/test/metadata.jsonl` → `image_perturbations` | included |
+| Image perturbation files | 15 types × 3 severity levels × 1,145 queries | **generate locally from the source repository** |
+
+---
+
+## Setup
+
+Install Hugging Face Datasets:
+
+```bash
+pip install datasets
+```
+
+Load the two dataset configurations from the Hub:
+
+```python
+from datasets import load_dataset
+
+queries = load_dataset("yefd/SnapBench", "queries", split="test")
+gallery = load_dataset("yefd/SnapBench", "gallery", split="test")
+```
+
+To load a local copy of this repository:
+
+```python
+from datasets import load_dataset
+
+queries = load_dataset(".", "queries", split="test")
+gallery = load_dataset(".", "gallery", split="test")
+```
+
+The `file_name` field in each `metadata.jsonl` file is automatically exposed as an `image` column by the Hugging Face `ImageFolder` builder.
+
+---
+
+## Build the Full Benchmark
+
+This Hugging Face version already includes the clean benchmark (queries, gallery, and text perturbations). The image perturbation specifications are stored in the `image_perturbations` field of every query. Use the scripts in the source repository to generate all image-perturbed query images locally.
+
+### Step 1. Generate image perturbations
+
+Clone and set up the source repository:
+
+```bash
+git lfs install
+git clone https://github.com/zrchen03/SnapBench.git SnapBench_raw
+cd SnapBench_raw
+git lfs pull
+pip install -r requirements.txt
+export BENCH_IMAGES_DIR=$(pwd)/bench_images
+```
+
+Generate 15 perturbation types × 3 severity levels (sev1 / sev2 / sev3) × 1,145 queries = **51,675 images**:
+
+```bash
+python benchmark/gen_image_perturbations.py
+```
+
+Output:
+
+```
+bench_images/perturbed/{type}/sev{1,2,3}/{query_id}.jpg
+```
+
+Preview the workload without writing files:
+
+```bash
+python benchmark/gen_image_perturbations.py --dry-run
+```
+
+To export the generated images as an additional Hugging Face configuration:
+
+```bash
+python benchmark/export_hf_dataset.py --include-perturbed --overwrite
+```
+
+### Step 2. (Optional) Regenerate text perturbations
+
+Text perturbations are already stored in `queries/test/metadata.jsonl`. Only rerun this in the source repository if you need to rebuild them:
+
+```bash
+python benchmark/gen_text_perturbations.py \
+  --gpu 0 --chunk-in chunk_0.json --chunk-out result_0.json
+```
+
+---
+
+## Data Layout
+
+```
+SnapBench/
+├── README.md
+├── queries/
+│   └── test/
+│       ├── metadata.jsonl
+│       └── images/          # 1,145 query images
+└── gallery/
+    └── test/
+        ├── metadata.jsonl
+        └── images/          # 9,059 unique gallery images
+```
+
+The dataset exposes two configurations, both with a `test` split:
+
+- `queries`: clean query images and text, positive and hard-negative gallery IDs, and all text/image perturbation metadata.
+- `gallery`: image–caption retrieval candidates. It has 9,085 items backed by 9,059 unique image files because some images have more than one caption.
+
+Important fields:
+
+- Query image: `queries/test/metadata.jsonl` → `file_name` (loaded as `image`)
+- Query text: `text`
+- Positive gallery items: `positive_gallery_ids`
+- Hard negatives: `hard_negative_gallery_ids`
+- Gallery image: `gallery/test/metadata.jsonl` → `file_name` (loaded as `image`)
+- Gallery caption: `caption`