Datasets:
Upload washroom-rf1fa from RF100
Browse filesThis view is limited to 50 files because it contains too many changes. See raw diff
- README.dataset.txt +11 -0
- README.md +140 -0
- README.roboflow.txt +29 -0
- data.yaml +22 -0
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README.dataset.txt
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# washroom > release-640
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https://universe.roboflow.com/roboflow-100/washroom-rf1fa
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Provided by a Roboflow user
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License: CC BY 4.0
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This dataset was originally created by [Anshul Rankawat, Kapil Verma, Shubhankar Rawat, Manisa Mondal, Pranav Arora](https://universe.roboflow.com/imagetaggingworkspace/). To see the current project, which may have been updated since this version, please go here: https://universe.roboflow.com/imagetaggingworkspace/washroom-image-tagging.
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This dataset is part of [RF100](https://rf100.org), an [Intel-sponsored](https://www.intel.com/) initiative to create a new object detection benchmark for model generalizability.
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Access the RF100 Github repo: https://github.com/roboflow-ai/roboflow-100-benchmark
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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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- object-detection
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tags:
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- roboflow
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- roboflow-100
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- rf100
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- yolo
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- libreyolo
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- real-world
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- computer-vision
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- bounding-box
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pretty_name: "Washroom Rf1Fa"
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size_categories:
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- 1K<n<10K
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dataset_info:
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features:
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- name: image
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dtype: image
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- name: label
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dtype: string
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splits:
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- name: train
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num_examples: 1885
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- name: validation
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num_examples: 775
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- name: test
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num_examples: 318
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---
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# Washroom Rf1Fa
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This dataset is part of the **Roboflow 100** benchmark, a diverse collection of 100 object detection datasets spanning 7 imagery domains.
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## Dataset Description
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- **Source:** [Roboflow 100](https://github.com/roboflow/roboflow-100-benchmark)
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- **Category:** Real World
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- **License:** CC-BY-4.0
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- **Format:** YOLO (LibreYOLO compatible)
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- **Mirrored on:** 2026-01-20
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## Dataset Statistics
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| Split | Images |
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|-------|--------|
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| Train | 1,885 |
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| Validation | 775 |
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| Test | 318 |
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| **Total** | **2,978** |
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## Classes (10)
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- bathtub
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- c
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- geyser
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- mirror
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- showerhead
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- sink
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- toilet
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- towel
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- washbasin
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- wc
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## Usage
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### With LibreYOLO
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```python
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from libreyolo import LIBREYOLO
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# Load a model
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model = LIBREYOLO(model_path="libreyoloXnano.pt")
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# Train on this dataset
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model.train(data='path/to/data.yaml', epochs=100)
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```
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### Download from HuggingFace
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```python
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from huggingface_hub import snapshot_download
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# Download the dataset
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snapshot_download(
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repo_id="Libre-YOLO/washroom-rf1fa",
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repo_type="dataset",
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local_dir="./washroom-rf1fa"
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)
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```
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## Directory Structure
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```
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washroom-rf1fa/
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├── data.yaml # Dataset configuration
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├── README.md # This file
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├── train/
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│ ├── images/ # Training images
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│ └── labels/ # Training labels (YOLO format)
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├── valid/
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│ ├── images/ # Validation images
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│ └── labels/ # Validation labels
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└── test/
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├── images/ # Test images (if available)
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└── labels/ # Test labels
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```
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## Label Format
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Labels are in YOLO format (one `.txt` file per image):
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```
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<class_id> <x_center> <y_center> <width> <height>
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```
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All coordinates are normalized to [0, 1].
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## Citation
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If you use this dataset, please cite the Roboflow 100 benchmark:
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```bibtex
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@misc{rf100_2022,
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Author = {Floriana Ciaglia and Francesco Saverio Zuppichini and Paul Guerrie and Mark McQuade and Jacob Solawetz},
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Title = {Roboflow 100: A Rich, Multi-Domain Object Detection Benchmark},
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Year = {2022},
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Eprint = {arXiv:2211.13523},
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}
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```
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## License
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This dataset is released under the **CC-BY-4.0** license.
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Please check the original source for any additional terms.
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## Acknowledgments
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- Original dataset from [Roboflow Universe](https://universe.roboflow.com/roboflow-100/washroom-rf1fa)
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- Part of the [Roboflow 100 Benchmark](https://www.rf100.org/)
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- Sponsored by Intel
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README.roboflow.txt
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washroom - v1 release-640
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==============================
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This dataset was exported via roboflow.com on March 2, 2023 at 6:28 AM GMT
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Roboflow is an end-to-end computer vision platform that helps you
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* collaborate with your team on computer vision projects
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* collect & organize images
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* understand and search unstructured image data
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* annotate, and create datasets
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* export, train, and deploy computer vision models
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* use active learning to improve your dataset over time
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For state of the art Computer Vision training notebooks you can use with this dataset,
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visit https://github.com/roboflow/notebooks
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To find over 100k other datasets and pre-trained models, visit https://universe.roboflow.com
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The dataset includes 2978 images.
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Washroom are annotated in YOLOv8 format.
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The following pre-processing was applied to each image:
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* Auto-orientation of pixel data (with EXIF-orientation stripping)
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* Resize to 640x640 (Stretch)
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No image augmentation techniques were applied.
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data.yaml
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names:
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- bathtub
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- c
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- geyser
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- mirror
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- showerhead
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- sink
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- toilet
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- towel
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- washbasin
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- wc
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nc: 10
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path: .
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roboflow:
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license: CC BY 4.0
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project: washroom-rf1fa
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url: https://universe.roboflow.com/roboflow-100/washroom-rf1fa/dataset/1
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version: 1
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workspace: roboflow-100
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test: test/images
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train: train/images
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val: valid/images
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test/images/aws_wr_img_104_jpg.rf.1e4e9582fffa7684df475e03db8e9728.jpg
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Git LFS Details
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test/images/aws_wr_img_105_jpg.rf.7d73cb64d560a1564077ee4cc195b102.jpg
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Git LFS Details
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test/images/aws_wr_img_106_jpg.rf.97810fbbc21e7131893fa898f2f87a34.jpg
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Git LFS Details
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test/images/aws_wr_img_110_jpg.rf.0903b87d9a45369f5f91898627bf29ee.jpg
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Git LFS Details
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test/images/aws_wr_img_111_jpg.rf.ba716e4e5ffa97aac156c519d3951669.jpg
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Git LFS Details
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test/images/aws_wr_img_113_jpg.rf.2286160981689188ccb73f0731e9aa7b.jpg
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Git LFS Details
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test/images/aws_wr_img_120_jpg.rf.1bfa06e7c68f84a97ad6992dc1feb285.jpg
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Git LFS Details
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test/images/aws_wr_img_1_jpg.rf.8c7a1cb3c4e3676d5d19a7afc82ca78f.jpg
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Git LFS Details
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test/images/aws_wr_img_259_jpg.rf.0f0ac9a33692c982b287d77e91758ef6.jpg
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Git LFS Details
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test/images/aws_wr_img_266_jpg.rf.fc8963910fca4244b85de672027764fd.jpg
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Git LFS Details
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test/images/aws_wr_img_267_jpg.rf.c5cc33fcbd58a1b8ffdabc4101ceeffb.jpg
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Git LFS Details
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test/images/aws_wr_img_270_jpg.rf.910c36edb840bd23ba89056f7694f738.jpg
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Git LFS Details
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test/images/aws_wr_img_272_jpg.rf.dbfb6248b8394665dfc603a5dc644f70.jpg
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Git LFS Details
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test/images/aws_wr_img_273_jpg.rf.ec4cc5217da19f67c069ea4728c091f5.jpg
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Git LFS Details
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test/images/aws_wr_img_298_jpg.rf.87726d10a4c42768563fbdcc95164d37.jpg
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Git LFS Details
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test/images/aws_wr_img_299_jpg.rf.1cc27e9ed22f217f740f984ed4503070.jpg
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Git LFS Details
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test/images/aws_wr_img_2_jpg.rf.3dcbb9709763162b39dad91c82bdbdc1.jpg
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Git LFS Details
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test/images/aws_wr_img_305_jpg.rf.c860875ec0637e82e13f17ce5014625c.jpg
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Git LFS Details
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test/images/aws_wr_img_310_jpg.rf.246b0bb19ee4b7647e13b00111be0436.jpg
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Git LFS Details
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test/images/aws_wr_img_311_jpg.rf.bf280dd462a39d8221dba7dcf0aec7d5.jpg
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Git LFS Details
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test/images/aws_wr_img_312_jpg.rf.cd68b945f45349bf2ba47996be7bfbf6.jpg
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Git LFS Details
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test/images/aws_wr_img_313_jpg.rf.0adfcdf72fa535792847de4cefff9b80.jpg
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Git LFS Details
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test/images/aws_wr_img_338_jpg.rf.5f8587e1e8e0a152c07464dfeae955bb.jpg
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Git LFS Details
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test/images/aws_wr_img_339_jpg.rf.c93f447d3d2497d15cfb560554427b43.jpg
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Git LFS Details
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test/images/aws_wr_img_3_jpg.rf.d6d64bbda7fb3551b6c0c075f337c720.jpg
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Git LFS Details
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test/images/aws_wr_img_448_jpg.rf.cd0a28f96bcd3e1302479c4ac8704f83.jpg
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Git LFS Details
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test/images/aws_wr_img_450_jpg.rf.beafbaf8d7c7f875554bd4cc6a88a0d1.jpg
ADDED
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Git LFS Details
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test/images/aws_wr_img_461_jpg.rf.ae59dc0016c656bffa3bd21c2652b205.jpg
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Git LFS Details
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test/images/aws_wr_img_463_jpg.rf.342047c6c49c8dd8ff173d234ef9893f.jpg
ADDED
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Git LFS Details
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test/images/aws_wr_img_474_jpg.rf.efebbec41866360fbe54dc6b6f965c0a.jpg
ADDED
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Git LFS Details
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test/images/aws_wr_img_477_jpg.rf.69a160ad66a7171f46578b30ab30b89e.jpg
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Git LFS Details
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test/images/aws_wr_img_478_jpg.rf.fc3599aacd910ccf0830dbbe94f68cfc.jpg
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Git LFS Details
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test/images/aws_wr_img_488_jpg.rf.0c23a8fd668e020d2b94e1f2929ddcb1.jpg
ADDED
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Git LFS Details
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test/images/aws_wr_img_493_jpg.rf.e6e0f0e2b8698011bb6202e75bead790.jpg
ADDED
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Git LFS Details
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test/images/aws_wr_img_500_jpg.rf.04486f42cc58662bff46e02400ca5535.jpg
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Git LFS Details
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test/images/aws_wr_img_501_jpg.rf.3e635dfb79570b7fb1d61ebcf537ece1.jpg
ADDED
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Git LFS Details
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test/images/aws_wr_img_502_jpg.rf.1f8ff98c0e8ff5be141118431aac2996.jpg
ADDED
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Git LFS Details
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test/images/aws_wr_img_503_jpg.rf.d13c10419f3761fa7cebe57e7e979629.jpg
ADDED
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Git LFS Details
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test/images/aws_wr_img_514_jpg.rf.bc77ca769cfb76b58cdae4f57a9d41a6.jpg
ADDED
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Git LFS Details
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test/images/aws_wr_img_515_jpg.rf.98e4488375e31efbed976190ff5243ae.jpg
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Git LFS Details
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test/images/aws_wr_img_516_jpg.rf.d9b57b8b933781ecb2e88483743b150d.jpg
ADDED
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Git LFS Details
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test/images/aws_wr_img_518_jpg.rf.8eddef3d7c5b280b4b77e1859a6b9236.jpg
ADDED
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Git LFS Details
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test/images/aws_wr_img_528_jpg.rf.70d7395419677e2fa19b1d422eb9ba7f.jpg
ADDED
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Git LFS Details
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test/images/aws_wr_img_529_jpg.rf.57f37439636e50cd074a46367f1da824.jpg
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Git LFS Details
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test/images/aws_wr_img_52_jpg.rf.a46b59664c231ea48e4157a09dabd2be.jpg
ADDED
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Git LFS Details
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test/images/aws_wr_img_61_jpg.rf.078037f3f86d5e5cf16f975ad00c413c.jpg
ADDED
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Git LFS Details
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