Create README.md

README.md

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+---
+language: en
+tags:
+- image-retrieval
+- oxford5k
+- paris6k
+- revisitop1m
+---
+
+# Dataset Card for RevisitOP (Oxford5k, Paris6k, RevisitOP1M)
+
+## Dataset Description
+
+**RevisitOP** provides popular benchmark datasets for large-scale image retrieval research:
+
+- **roxford5k**: Oxford 5k buildings dataset containing ~5,000 images.
+- **rparis6k**: Paris 6k buildings dataset with ~6,000 images.
+- **revisitop1m**: RevisitOP 1M distractor dataset with ~1 million distractor images.
+- **oxfordparis**: Combination of Oxford 5k and Paris 6k datasets.
+
+These datasets are widely used for evaluating image retrieval algorithms and contain real-world building photographs and distractors.
+
+## Dataset Features
+
+Each example contains:
+- `image` (`Image`): An image file (JPEG or PNG).
+- `filename` (`string`): The original filename of the image.
+- `dataset` (`string`): The source dataset the image belongs to (`roxford5k`, `rparis6k`, or `revisitop1m`).
+
+## Dataset Versions
+
+- Version 1.0.0
+
+## Example Usage
+
+Use the Hugging Face `datasets` library to load one of the configs:
+
+```python
+import datasets
+from aiohttp import ClientTimeout
+
+dataset_name = "randall-lab/revisitop"
+timeout_period = 500000  # very long timeout to prevent timeouts
+storage_options = {"client_kwargs": {"timeout": ClientTimeout(total=timeout_period)}}
+
+# These are the config names defined in the script
+dataset_configs = ["roxford5k", "rparis6k", "oxfordparis"]  # "revisitop1m" is large and may take a long time to load
+
+# test all of the dataset_configs specified above
+for i, config_name in enumerate(dataset_configs, start=1):
+    dataset = datasets.load_dataset(
+        path="revisitop.py",  # use local dataset script
+        name=config_name,
+        split="train",
+        trust_remote_code=True,
+        storage_options=storage_options,
+    )
+
+    example = dataset[243]  # Get first example
+    image = example["image"]
+    filename = example["filename"]
+    dataset_name = example["dataset"]
+    print(
+        f"[{i}] Loaded config '{config_name}' - example file: {filename}, dataset: {dataset_name}"
+    )
+    image.save(f"output_image_{i}.jpg", format="JPEG")
+```
+
+## Dataset Structure
+
+- The datasets consist of images downloaded and extracted from official URLs hosted by the Oxford Visual Geometry Group and the RevisitOP project.
+- The `roxford5k` and `rparis6k` datasets come from `.tgz` archives.
+- The `revisitop1m` dataset consists of 100 `.tar.gz` archives with JPEG images as distractors.
+- The combined `oxfordparis` dataset merges the Oxford and Paris sets.
+
+## Dataset Citation
+
+If you use this dataset, please cite the original paper:
+
+```bibtex
+@inproceedings{Radenovic2018RevisitingOP,
+  title={Revisiting Oxford and Paris: Large-Scale Image Retrieval Benchmarking},
+  author={Filip Radenovic and Ahmet Iscen and Giorgos Tolias and Yannis Avrithis and Ondrej Chum},
+  year={2018}
+}
+```
+
+## Dataset Homepage
+
+[RevisitOP project page](http://cmp.felk.cvut.cz/revisitop/)
+