Datasets:
Upload flir-camera-objects from RF100
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- README.dataset.txt +11 -0
- README.md +134 -0
- README.roboflow.txt +29 -0
- data.yaml +16 -0
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- test/images/FLIR_00282_jpeg_jpg.rf.248cfa2dcc60eb41050c1b17e7bfd37e.jpg +3 -0
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README.dataset.txt
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# flir camera objects > release-640
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https://universe.roboflow.com/roboflow-100/flir-camera-objects
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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 [Ruud Krinkels](https://universe.roboflow.com/thermal-imaging-0hwfw/). To see the current project, which may have been updated since this version, please go here: https://universe.roboflow.com/thermal-imaging-0hwfw/flir-data-set.
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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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- electromagnetic
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- computer-vision
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- bounding-box
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pretty_name: "Flir Camera Objects"
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size_categories:
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- 10K<n<100K
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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: 9306
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- name: validation
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num_examples: 2854
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- name: test
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num_examples: 1452
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---
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# Flir Camera Objects
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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:** Electromagnetic
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- **License:** CC-BY-4.0
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- **Format:** YOLO (LibreYOLO compatible)
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- **Mirrored on:** 2026-01-21
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## Dataset Statistics
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| Split | Images |
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|-------|--------|
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| Train | 9,306 |
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| Validation | 2,854 |
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| Test | 1,452 |
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| **Total** | **13,612** |
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## Classes (4)
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- bicycle
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- car
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- dog
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- person
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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/flir-camera-objects",
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repo_type="dataset",
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local_dir="./flir-camera-objects"
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)
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```
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## Directory Structure
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```
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flir-camera-objects/
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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/flir-camera-objects)
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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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flir camera objects - v1 release-640
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==============================
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This dataset was exported via roboflow.com on April 3, 2023 at 9:43 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 13612 images.
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Flir-camera-objects 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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- bicycle
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- car
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- dog
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- person
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nc: 4
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path: .
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roboflow:
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license: CC BY 4.0
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project: flir-camera-objects
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url: https://universe.roboflow.com/roboflow-100/flir-camera-objects/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/FLIR_00001_jpeg_jpg.rf.31ea941b29c47c1a0fbdacc3c67bdcdc.jpg
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Git LFS Details
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test/images/FLIR_00017_jpeg_jpg.rf.c55a7fcfe63c8025ead49f422a5a4ca0.jpg
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Git LFS Details
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test/images/FLIR_00021_jpeg_jpg.rf.fe6a025b5ca7a3601892117506e7d030.jpg
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Git LFS Details
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test/images/FLIR_00026_jpeg_jpg.rf.3ef2a746eb5397a4b9115f50325a2a08.jpg
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Git LFS Details
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test/images/FLIR_00030_jpeg_jpg.rf.32675254a168c20a4cecd7ec78c62933.jpg
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Git LFS Details
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test/images/FLIR_00037_jpeg_jpg.rf.1e0d6ad44da4ce2360f3e62c839f9073.jpg
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Git LFS Details
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test/images/FLIR_00040_jpeg_jpg.rf.827002b7ae5910b40a5a3f29f9952768.jpg
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Git LFS Details
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test/images/FLIR_00056_jpeg_jpg.rf.0455e3ed41ddd5b4087efc96edb62c60.jpg
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Git LFS Details
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test/images/FLIR_00060_jpeg_jpg.rf.78c5244254e3703cee48aa9f1c4e179d.jpg
ADDED
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Git LFS Details
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test/images/FLIR_00067_jpeg_jpg.rf.c23e01034a7c2907b4d1664b91b4e6ff.jpg
ADDED
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Git LFS Details
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test/images/FLIR_00071_jpeg_jpg.rf.d7dd7c4a79c4c189411b52e06272b550.jpg
ADDED
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Git LFS Details
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test/images/FLIR_00076_jpeg_jpg.rf.dc486eefe6a9cb8b31f5f90dc8318048.jpg
ADDED
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Git LFS Details
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test/images/FLIR_00083_jpeg_jpg.rf.ffb221e88d50cf23b70cfab333383eb5.jpg
ADDED
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Git LFS Details
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test/images/FLIR_00088_jpeg_jpg.rf.44003062c08ad9c73fb7b015d51bc79e.jpg
ADDED
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Git LFS Details
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test/images/FLIR_00095_jpeg_jpg.rf.4ecb7890c54c9892f215848ad8fde31d.jpg
ADDED
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Git LFS Details
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test/images/FLIR_00099_jpeg_jpg.rf.48ac70ec584b4bce1062a58bc26f4c04.jpg
ADDED
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Git LFS Details
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test/images/FLIR_00105_jpeg_jpg.rf.87ed68f967bde1e797f1dd656aeb3568.jpg
ADDED
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Git LFS Details
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test/images/FLIR_00109_jpeg_jpg.rf.5c2e4da34f22c4fa774be17219563c37.jpg
ADDED
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Git LFS Details
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test/images/FLIR_00113_jpeg_jpg.rf.d5d88b2b3a23a5ad801186e64efb33a5.jpg
ADDED
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Git LFS Details
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test/images/FLIR_00122_jpeg_jpg.rf.8c55e8e762728e59e35b214623dac930.jpg
ADDED
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Git LFS Details
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test/images/FLIR_00125_jpeg_jpg.rf.60ae9faaf55b99ef781c373606820d3f.jpg
ADDED
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Git LFS Details
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test/images/FLIR_00129_jpeg_jpg.rf.22b2c8d09bc958415fa7e04986d3053b.jpg
ADDED
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Git LFS Details
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test/images/FLIR_00133_jpeg_jpg.rf.bee98d8314829d22fc377d4a9e28d09a.jpg
ADDED
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Git LFS Details
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test/images/FLIR_00134_jpeg_jpg.rf.7c61e60fe54c561483406d6f3a45cbbb.jpg
ADDED
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Git LFS Details
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test/images/FLIR_00144_jpeg_jpg.rf.8da2e0c1decf3ad658ca76b3c7f47b58.jpg
ADDED
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Git LFS Details
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test/images/FLIR_00152_jpeg_jpg.rf.f8bba71fe14739da82fe5775f826ec92.jpg
ADDED
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Git LFS Details
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test/images/FLIR_00159_jpeg_jpg.rf.13f39dcaa64ee1c1dfd20a2e112a127a.jpg
ADDED
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Git LFS Details
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test/images/FLIR_00163_jpeg_jpg.rf.6180db47c50c8bb93c3e00ae226e647d.jpg
ADDED
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Git LFS Details
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test/images/FLIR_00164_jpeg_jpg.rf.a45f98fbe4aa3ba8e2e35225d901e3ea.jpg
ADDED
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Git LFS Details
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test/images/FLIR_00168_jpeg_jpg.rf.cbc45c9ab5e97e4e582b9d25f6c4e276.jpg
ADDED
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Git LFS Details
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test/images/FLIR_00172_jpeg_jpg.rf.f793bf4cecdf8ffc240260e47bc09ff3.jpg
ADDED
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Git LFS Details
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test/images/FLIR_00175_jpeg_jpg.rf.f77e7b09cf1ceeb44121d756e141a481.jpg
ADDED
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Git LFS Details
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test/images/FLIR_00187_jpeg_jpg.rf.37474424e9e8b9ecd2de7e35171e1db5.jpg
ADDED
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Git LFS Details
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test/images/FLIR_00191_jpeg_jpg.rf.bebc4facf6e745d20ec7f89de9b93f5c.jpg
ADDED
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Git LFS Details
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test/images/FLIR_00200_jpeg_jpg.rf.fb4a68358ee35d15e2cc7d8502249ffd.jpg
ADDED
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Git LFS Details
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test/images/FLIR_00216_jpeg_jpg.rf.58da97727c9f480b6f4ec4b1db472ecc.jpg
ADDED
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Git LFS Details
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test/images/FLIR_00220_jpeg_jpg.rf.29b8ab5420a323390a504e198b8b58e6.jpg
ADDED
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Git LFS Details
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test/images/FLIR_00227_jpeg_jpg.rf.8850072139108a83a382a5eb1470fa96.jpg
ADDED
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Git LFS Details
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test/images/FLIR_00241_jpeg_jpg.rf.16e54f74a9b0a0bbab9598f6de4e4f0e.jpg
ADDED
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Git LFS Details
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test/images/FLIR_00257_jpeg_jpg.rf.4efd0f3056b018113847aa549ec5b23c.jpg
ADDED
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Git LFS Details
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test/images/FLIR_00270_jpeg_jpg.rf.f27c4b0112b0d0f874ff9b5457c17c58.jpg
ADDED
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Git LFS Details
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test/images/FLIR_00277_jpeg_jpg.rf.26a2ff99530e6c73dc5ffc02857dd7c1.jpg
ADDED
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Git LFS Details
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test/images/FLIR_00282_jpeg_jpg.rf.248cfa2dcc60eb41050c1b17e7bfd37e.jpg
ADDED
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Git LFS Details
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test/images/FLIR_00294_jpeg_jpg.rf.15be511074eb724e8dc852585c1f11b1.jpg
ADDED
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Git LFS Details
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test/images/FLIR_00298_jpeg_jpg.rf.c961e560c6fa657a4e1582390dd20d3f.jpg
ADDED
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Git LFS Details
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test/images/FLIR_00304_jpeg_jpg.rf.b05fe6321d61be16ab38be068dcef2bb.jpg
ADDED
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Git LFS Details
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