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- README.dataset.txt +11 -0
- README.md +132 -0
- README.roboflow.txt +29 -0
- data.yaml +14 -0
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- test/labels/WIN_20220423_18_13_57_Pro_jpg.rf.39b4cbc5b7ff14b13249135daf569293.txt +50 -0
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README.dataset.txt
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# peanuts > release-640
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https://universe.roboflow.com/roboflow-100/peanuts-sd4kf
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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 [Melanie S. Capalungan, "B-Jay" Daguio, Isaac Balbuena, Reanne Joy Rafael](https://universe.roboflow.com/molds-onbk3/). To see the current project, which may have been updated since this version, please go here: https://universe.roboflow.com/molds-onbk3/peanuts-mckge/.
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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: "Peanuts Sd4Kf"
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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: 268
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- name: validation
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num_examples: 77
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- name: test
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num_examples: 42
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---
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# Peanuts Sd4Kf
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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 | 268 |
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| Validation | 77 |
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| Test | 42 |
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| **Total** | **387** |
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## Classes (2)
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- with mold
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- without mold
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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/peanuts-sd4kf",
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repo_type="dataset",
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local_dir="./peanuts-sd4kf"
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)
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```
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## Directory Structure
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```
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peanuts-sd4kf/
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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/peanuts-sd4kf)
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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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peanuts - v1 release-640
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==============================
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This dataset was exported via roboflow.com on April 3, 2023 at 9:51 PM 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 387 images.
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Peanuts 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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- with mold
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- without mold
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nc: 2
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path: .
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roboflow:
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license: CC BY 4.0
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project: peanuts-sd4kf
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url: https://universe.roboflow.com/roboflow-100/peanuts-sd4kf/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/WIN_20220423_18_13_57_Pro_jpg.rf.39b4cbc5b7ff14b13249135daf569293.jpg
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Git LFS Details
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test/images/WIN_20220423_18_14_01_Pro_jpg.rf.c42329f71fb89b7995ce938b7b0401dd.jpg
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Git LFS Details
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test/images/WIN_20220423_18_22_27_Pro--2-_jpg.rf.19efe0853baa67140b543a290050cd95.jpg
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Git LFS Details
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test/images/WIN_20220423_18_22_27_Pro_jpg.rf.3177a6d439d19d0ac2a6324daa1b7527.jpg
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Git LFS Details
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test/images/WIN_20220423_18_22_34_Pro--2-_jpg.rf.8939f7e170b2a4eba6c1dc705b217d04.jpg
ADDED
|
Git LFS Details
|
test/images/WIN_20220423_18_22_36_Pro--2-_jpg.rf.82503354a58b527f63a520eb36e4dff1.jpg
ADDED
|
Git LFS Details
|
test/images/WIN_20220423_18_22_38_Pro_jpg.rf.46decd0bbc373cb546b5b52029fd0622.jpg
ADDED
|
Git LFS Details
|
test/images/WIN_20220423_18_33_45_Pro--2-_jpg.rf.ddaeabd07c96d5f1bc1243a8e087f6f8.jpg
ADDED
|
Git LFS Details
|
test/images/WIN_20220423_18_33_46_Pro_jpg.rf.9897dddb2ecedd832145d42239441fff.jpg
ADDED
|
Git LFS Details
|
test/images/WIN_20220423_18_39_55_Pro--2-_jpg.rf.631cd4e876c355c4f8e0ce684edcd33f.jpg
ADDED
|
Git LFS Details
|
test/images/WIN_20220423_18_51_19_Pro_jpg.rf.375fac7886a3918c5c334245705490dd.jpg
ADDED
|
Git LFS Details
|
test/images/WIN_20220423_18_51_29_Pro--2-_jpg.rf.19f997ea95b629cd91314d55ae8819d5.jpg
ADDED
|
Git LFS Details
|
test/images/WIN_20220423_18_51_29_Pro_jpg.rf.c7fc82f043af7b4d108d76ced7b92428.jpg
ADDED
|
Git LFS Details
|
test/images/WIN_20220423_19_08_49_Pro_jpg.rf.9a9dd36e13a03888e58097a723dd9b83.jpg
ADDED
|
Git LFS Details
|
test/images/WIN_20220423_19_08_51_Pro_jpg.rf.3c06ca17c4a424778857aa46528d476d.jpg
ADDED
|
Git LFS Details
|
test/images/WIN_20220423_19_17_50_Pro_jpg.rf.c938fae3c8ed16f0ced666879aa9ec28.jpg
ADDED
|
Git LFS Details
|
test/images/WIN_20220423_19_17_52_Pro--2-_jpg.rf.a1b799a4b8054d2c6bb8024bebd570fc.jpg
ADDED
|
Git LFS Details
|
test/images/WIN_20220423_19_17_55_Pro_jpg.rf.9b962c504f456efcbf14420222f95eb8.jpg
ADDED
|
Git LFS Details
|
test/images/WIN_20220423_19_22_58_Pro_jpg.rf.0b31f0d3e9989440820c9012c2e25be0.jpg
ADDED
|
Git LFS Details
|
test/images/WIN_20220423_19_23_01_Pro_jpg.rf.eca2b96aec94998005bc222ac82c4de8.jpg
ADDED
|
Git LFS Details
|
test/images/WIN_20220423_19_30_15_Pro_jpg.rf.b94e3ad589e2fbd526c498971ecc1164.jpg
ADDED
|
Git LFS Details
|
test/images/WIN_20220423_19_30_19_Pro--2-_jpg.rf.54f93ef443237c43fe717023271a4354.jpg
ADDED
|
Git LFS Details
|
test/images/WIN_20220423_19_30_22_Pro--3-_jpg.rf.8691bd51ad693f9b21c143d1945b4603.jpg
ADDED
|
Git LFS Details
|
test/images/WIN_20220423_19_30_23_Pro--2-_jpg.rf.18578672e492fa38599f9826cb060d36.jpg
ADDED
|
Git LFS Details
|
test/images/WIN_20220502_18_26_47_Pro_jpg.rf.2e3b6c8e8d2934fdc55e8228964a9d5a.jpg
ADDED
|
Git LFS Details
|
test/images/WIN_20220502_18_26_49_Pro_jpg.rf.5300f175df21fd67246da9cb1909a7cd.jpg
ADDED
|
Git LFS Details
|
test/images/WIN_20220502_18_27_00_Pro_jpg.rf.a80cf201005e27d6b98b7b1e0a8a7305.jpg
ADDED
|
Git LFS Details
|
test/images/WIN_20220502_18_28_01_Pro_jpg.rf.423c22ff3c3d0b92bea88db875cb49ad.jpg
ADDED
|
Git LFS Details
|
test/images/WIN_20220502_18_29_50_Pro_jpg.rf.110a552f517b9f1bc810a1a515698f13.jpg
ADDED
|
Git LFS Details
|
test/images/WIN_20220502_18_30_11_Pro_jpg.rf.e5554173deff5307fd7dabb209d6ba51.jpg
ADDED
|
Git LFS Details
|
test/images/WIN_20220502_19_43_06_Pro_jpg.rf.29a9930915f36c837e0d18c8e45e0326.jpg
ADDED
|
Git LFS Details
|
test/images/WIN_20220502_19_43_13_Pro_jpg.rf.6201ff5cc1970302940395379f6ec947.jpg
ADDED
|
Git LFS Details
|
test/images/WIN_20220502_19_43_14_Pro_jpg.rf.7a9fc770f83648c622f2c75c22a7bc95.jpg
ADDED
|
Git LFS Details
|
test/images/WIN_20220502_19_43_22_Pro_jpg.rf.cbce5b7468e1be6e4bd2639748d8803e.jpg
ADDED
|
Git LFS Details
|
test/images/WIN_20220502_19_43_23_Pro_jpg.rf.d40938d5b4a8f57a87a2958647d3f779.jpg
ADDED
|
Git LFS Details
|
test/images/WIN_20220502_19_43_35_Pro_jpg.rf.cb2543aa2e9f1d08c044e3ddfcb96f07.jpg
ADDED
|
Git LFS Details
|
test/images/WIN_20220502_19_43_44_Pro_jpg.rf.588d8294e325e2638124e17eb7adbbdf.jpg
ADDED
|
Git LFS Details
|
test/images/WIN_20220502_19_43_46_Pro--2-_jpg.rf.f8b0f6be4a79f0fb58f6cfd66667235e.jpg
ADDED
|
Git LFS Details
|
test/images/WIN_20220502_19_43_49_Pro_jpg.rf.a4ebd4d7e3f796bed7bf1007c26f3de4.jpg
ADDED
|
Git LFS Details
|
test/images/WIN_20220502_19_43_51_Pro_jpg.rf.3e519d60594e7cb1e70f1fe177909fc8.jpg
ADDED
|
Git LFS Details
|
test/images/WIN_20220502_19_45_21_Pro--2-_jpg.rf.b4fc542e6e3c42ee005124c628b8c785.jpg
ADDED
|
Git LFS Details
|
test/images/WIN_20220502_19_45_39_Pro_jpg.rf.b8455d94c5952e1ed06d2296d6d40d05.jpg
ADDED
|
Git LFS Details
|
test/labels/WIN_20220423_18_13_57_Pro_jpg.rf.39b4cbc5b7ff14b13249135daf569293.txt
ADDED
|
@@ -0,0 +1,50 @@
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| 32 |
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0 0.24296875 0.62890625 0.04375 0.12265625
|
| 33 |
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0 0.17421875 0.63203125 0.046875 0.1171875
|
| 34 |
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|
| 35 |
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0 0.59921875 0.63359375 0.0421875 0.125
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| 36 |
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|
test/labels/WIN_20220423_18_14_01_Pro_jpg.rf.c42329f71fb89b7995ce938b7b0401dd.txt
ADDED
|
@@ -0,0 +1,50 @@
|
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| 20 |
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| 32 |
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|
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|
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|
| 38 |
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|
| 49 |
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|
| 50 |
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|
test/labels/WIN_20220423_18_22_27_Pro--2-_jpg.rf.19efe0853baa67140b543a290050cd95.txt
ADDED
|
@@ -0,0 +1,50 @@
|
|
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|
|
|
|
|
|
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|
| 1 |
+
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|
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|
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|
| 18 |
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|
| 19 |
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| 20 |
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|
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| 23 |
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|
| 25 |
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|
| 26 |
+
0 0.81171875 0.4875 0.03828125 0.10859375
|
| 27 |
+
0 0.18828125 0.48828125 0.046875 0.12578125
|
| 28 |
+
0 0.74375 0.4875 0.04140625 0.1140625
|
| 29 |
+
0 0.534375 0.4875 0.03984375 0.1109375
|
| 30 |
+
0 0.25625 0.4890625 0.04375 0.10859375
|
| 31 |
+
0 0.671875 0.61640625 0.0390625 0.1265625
|
| 32 |
+
0 0.7453125 0.621875 0.04140625 0.125
|
| 33 |
+
0 0.47109375 0.62265625 0.04375 0.128125
|
| 34 |
+
0 0.2578125 0.6234375 0.0421875 0.11953125
|
| 35 |
+
0 0.6109375 0.62421875 0.04140625 0.12421875
|
| 36 |
+
0 0.8109375 0.62734375 0.04296875 0.121875
|
| 37 |
+
0 0.40390625 0.628125 0.040625 0.1359375
|
| 38 |
+
0 0.19609375 0.63125 0.04375 0.11171875
|
| 39 |
+
0 0.53671875 0.63359375 0.0421875 0.12265625
|
| 40 |
+
0 0.328125 0.6390625 0.03984375 0.11953125
|
| 41 |
+
0 0.81484375 0.76953125 0.0453125 0.13359375
|
| 42 |
+
0 0.19609375 0.7703125 0.03828125 0.12421875
|
| 43 |
+
0 0.67578125 0.7703125 0.046875 0.14375
|
| 44 |
+
0 0.75 0.771875 0.0421875 0.13828125
|
| 45 |
+
0 0.47109375 0.77421875 0.0453125 0.1234375
|
| 46 |
+
0 0.5390625 0.775 0.0390625 0.121875
|
| 47 |
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0 0.40703125 0.77578125 0.0421875 0.1296875
|
| 48 |
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0 0.6125 0.7796875 0.04453125 0.14609375
|
| 49 |
+
0 0.26484375 0.78203125 0.04375 0.11640625
|
| 50 |
+
0 0.32890625 0.7890625 0.046875 0.1234375
|
test/labels/WIN_20220423_18_22_27_Pro_jpg.rf.3177a6d439d19d0ac2a6324daa1b7527.txt
ADDED
|
@@ -0,0 +1,50 @@
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|
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|
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|
| 1 |
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0 0.4640625 0.18515625 0.04453125 0.12578125
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| 2 |
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0 0.60859375 0.1875 0.040625 0.11640625
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| 3 |
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0 0.68046875 0.1890625 0.0453125 0.11953125
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| 4 |
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0 0.740625 0.1921875 0.03515625 0.115625
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0 0.5375 0.19296875 0.04140625 0.1140625
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0 0.19609375 0.196875 0.04375 0.11875
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0 0.25703125 0.19765625 0.0484375 0.11953125
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| 8 |
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0 0.3296875 0.19921875 0.04453125 0.12421875
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0 0.8046875 0.203125 0.0390625 0.10625
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| 10 |
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0 0.3953125 0.203125 0.0390625 0.10390625
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| 11 |
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0 0.19140625 0.328125 0.04140625 0.1171875
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0 0.53671875 0.3375 0.040625 0.13125
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0 0.26171875 0.33828125 0.04140625 0.1078125
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0 0.8046875 0.33984375 0.03828125 0.11015625
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0 0.33203125 0.340625 0.0421875 0.10078125
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0 0.46640625 0.340625 0.04453125 0.1109375
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| 17 |
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0 0.60625 0.340625 0.04296875 0.109375
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| 18 |
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0 0.74375 0.34140625 0.040625 0.115625
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| 19 |
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0 0.3953125 0.34140625 0.0421875 0.115625
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| 20 |
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0 0.6734375 0.34375 0.03828125 0.1234375
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| 21 |
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0 0.67578125 0.48125 0.03828125 0.13203125
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| 22 |
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0 0.471875 0.4828125 0.040625 0.11875
|
| 23 |
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0 0.6125 0.48359375 0.04140625 0.11171875
|
| 24 |
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0 0.328125 0.4859375 0.040625 0.11640625
|
| 25 |
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0 0.74375 0.48515625 0.04140625 0.115625
|
| 26 |
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0 0.1890625 0.48671875 0.04453125 0.128125
|
| 27 |
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0 0.40234375 0.48671875 0.04375 0.10390625
|
| 28 |
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0 0.81171875 0.48828125 0.03828125 0.109375
|
| 29 |
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0 0.5359375 0.48984375 0.03984375 0.10703125
|
| 30 |
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0 0.25625 0.48984375 0.04453125 0.10703125
|
| 31 |
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0 0.671875 0.615625 0.03984375 0.12578125
|
| 32 |
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0 0.7453125 0.62109375 0.040625 0.1234375
|
| 33 |
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0 0.4703125 0.6234375 0.04453125 0.125
|
| 34 |
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0 0.61171875 0.6234375 0.04140625 0.12265625
|
| 35 |
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0 0.2578125 0.625 0.0421875 0.11953125
|
| 36 |
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0 0.8109375 0.628125 0.04296875 0.11953125
|
| 37 |
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0 0.40390625 0.628125 0.040625 0.134375
|
| 38 |
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0 0.196875 0.63046875 0.04453125 0.1140625
|
| 39 |
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0 0.5359375 0.63359375 0.04140625 0.1234375
|
| 40 |
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0 0.328125 0.6375 0.03984375 0.11953125
|
| 41 |
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0 0.815625 0.76796875 0.0453125 0.1359375
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| 42 |
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0 0.67578125 0.76953125 0.046875 0.13984375
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| 43 |
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0 0.74921875 0.77109375 0.04296875 0.1390625
|
| 44 |
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0 0.196875 0.77109375 0.03984375 0.1203125
|
| 45 |
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0 0.47265625 0.77265625 0.04453125 0.1203125
|
| 46 |
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0 0.5390625 0.77578125 0.03828125 0.1203125
|
| 47 |
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0 0.40703125 0.7765625 0.04140625 0.125
|
| 48 |
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0 0.61328125 0.78125 0.04453125 0.14609375
|
| 49 |
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0 0.26484375 0.7828125 0.04375 0.11796875
|
| 50 |
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0 0.3296875 0.78828125 0.04453125 0.121875
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