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CITATION.cff

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+cff-version: 1.2.0
+title: "Controlled Diet (CD) Dataset for Methane Plume Detection"
+message: "If you use this dataset, please cite both the dataset and the accompanying research paper."
+type: dataset
+authors:
+  - family-names: "Embaby"
+    given-names: "Mohamed G."
+    orcid: "https://orcid.org/0000-0002-9695-3433" 
+  - family-names: "Sarker"
+    given-names: "Toqi Tahamid"
+    orcid: "https://orcid.org/0000-0003-2482-8059"  
+  - family-names: "AbuGhazaleh"
+    given-names: "Amer"
+    orcid: "https://orcid.org/0000-0003-1589-2358"  
+  - family-names: "Ahmed"
+    given-names: "Khaled R."
+    orcid: "https://orcid.org/0000-0002-3707-4316"  
+repository-code: "https://github.com/toqitahamid/controlled-diet-methane-dataset" 
+url: "https://huggingface.co/datasets/toqi/controlled-diet-methane" 
+abstract: >-
+  The Controlled Diet (CD) dataset is a large-scale collection of 4,885 methane (CH₄) 
+  plume images captured using optical gas imaging (OGI) technology for semantic 
+  segmentation tasks. This dataset was developed to investigate the detection and 
+  quantification of enteric methane emissions from ruminants under different dietary 
+  conditions using computer vision and deep learning techniques. The dataset contains 
+  methane plumes categorized into three classes based on Gas Chromatography (GC) 
+  measured concentration ranges corresponding to different dietary treatments: 
+  Control (166-171 ppm), Low Forage (300-334 ppm), and High Forage (457-510 ppm).
+keywords:
+  - "optical gas imaging"
+  - "methane detection"
+  - "semantic segmentation"
+  - "livestock emissions"
+  - "computer vision"
+  - "deep learning"
+  - "agriculture"
+  - "climate change"
+  - "FLIR GF77"
+license: "CC-BY-4.0"
+version: "1.0.0"
+date-released: "2025-01-19"
+identifiers:
+  - type: "doi"
+    value: "10.1049/ipr2.13327"
+    description: "Accompanying research paper DOI"
+preferred-citation:
+  type: article
+  title: "Optical gas imaging and deep learning for quantifying enteric methane emissions from rumen fermentation in vitro"
+  authors:
+    - family-names: "Embaby"
+      given-names: "Mohamed G."
+    - family-names: "Sarker"
+      given-names: "Toqi Tahamid"
+    - family-names: "AbuGhazaleh"
+      given-names: "Amer"
+    - family-names: "Ahmed"
+      given-names: "Khaled R."
+  journal: "IET Image Processing"
+  year: 2025
+  publisher:
+    name: "Institution of Engineering and Technology"
+  doi: "10.1049/ipr2.13327"
+  url: "https://doi.org/10.1049/ipr2.13327" 

LICENSE

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+Creative Commons Attribution 4.0 International
+
+Copyright (c) 2025 Mohamed G. Embaby, Toqi Tahamid Sarker, Amer AbuGhazaleh, Khaled R. Ahmed
+
+This work is licensed under the Creative Commons Attribution 4.0 International License.
+
+You are free to:
+- Share — copy and redistribute the material in any medium or format
+- Adapt — remix, transform, and build upon the material for any purpose, even commercially
+
+Under the following terms:
+- Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
+
+No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
+
+To view a copy of this license, visit: https://creativecommons.org/licenses/by/4.0/
+
+This dataset was developed with support from USDA NIFA Grant.

README.md

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----
-license: cc-by-4.0
----
+# Controlled Diet Dataset for Methane Plume Detection
+
+[![Paper](https://img.shields.io/badge/Paper-IET%20Image%20Processing-blue)](https://doi.org/10.1049/ipr2.13327)
+[![License](https://img.shields.io/badge/License-CC%20BY%204.0-green)](https://creativecommons.org/licenses/by/4.0/)
+[![USDA](https://img.shields.io/badge/Funded%20by-USDA%20NIFA-orange)](https://www.nifa.usda.gov/)
+
+## 📊 Dataset Overview
+
+This repository contains the CD dataset for methane plume detection, presented in the paper "Optical gas imaging and deep learning for quantifying enteric methane emissions from rumen fermentation in vitro". This dataset contains **4,885 thermal infrared images** of methane plumes captured using FLIR GF77 optical gas imaging technology for semantic segmentation applications in agricultural emissions monitoring. 
+
+The images document methane emissions from controlled rumen fermentation experiments under three dietary conditions: Control diet (166-171 ppm), Low forage diet (300-334 ppm), and High forage diet (457-510 ppm).
+
+## 📄 Associated Publication
+
+**"Optical gas imaging and deep learning for quantifying enteric methane emissions from rumen fermentation in vitro"**  
+*Mohamed G. Embaby, Toqi Tahamid Sarker, Amer AbuGhazaleh, Khaled R. Ahmed*  
+*IET Image Processing*, January 19, 2025  
+DOI: [10.1049/ipr2.13327](https://doi.org/10.1049/ipr2.13327)
+
+## 📊 Dataset Details
+
+
+### Dataset Statistics
+| Class | GC Range (ppm) | Diet Description | Train | Val | Test | Total |
+|-------|----------------|------------------|-------|-----|------|-------|
+| Control | 166-171 | 50:50 F:C ratio | 1,079 | 138 | 133 | 1,350 |
+| Low Forage | 300-334 | 20:80 F:C ratio | 1,268 | 162 | 157 | 1,587 |
+| High Forage | 457-510 | 80:20 F:C ratio | 1,558 | 196 | 194 | 1,948 |
+
+
+### Class Mapping
+
+- **Class 1**: Control diet methane plumes (166-171 ppm)
+- **Class 2**: Low forage diet methane plumes (300-334 ppm)  
+- **Class 3**: High forage diet methane plumes (457-510 ppm)
+
+**Mask Pixel Values:**
+- Pixel value 0: Background
+- Pixel value 1: Class 1 (Control diet, 166-171 ppm)
+- Pixel value 3: Class 2 (Low forage diet, 300-334 ppm)  
+- Pixel value 2: Class 3 (High forage diet, 457-510 ppm)
+
+
+## 📋 License
+
+This dataset is released under the [Creative Commons Attribution 4.0 International (CC BY 4.0)](https://creativecommons.org/licenses/by/4.0/) license.
+
+## 📚 Additional Resources
+
+For preprocessing methods and code examples, please refer to the [GitHub repository](https://github.com/toqitahamid/controlled-diet-methane-dataset). 
+
+
+## 🙏 Acknowledgments
+
+This work was supported by the USDA National Institute of Food and Agriculture (NIFA) under Grant No. 2022-70001-37404.
+
+## 📜 Citation
+
+This work is published in IET Image Processing (2025, DOI: 10.1049/ipr2.13327).
+
+```bibtex
+@article{embaby2025optical,
+  title={Optical gas imaging and deep learning for quantifying enteric methane emissions from rumen fermentation in vitro},
+  author={Embaby, Mohamed G and Sarker, Toqi Tahamid and AbuGhazaleh, Amer and Ahmed, Khaled R},
+  journal={IET Image Processing},
+  year={2025},
+  doi={10.1049/ipr2.13327}
+}
+```

mappings/class_mapping_summary.txt

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+CONTROLLED DIET DATASET - CLASS MAPPING SUMMARY
+==================================================
+
+OVERALL STATISTICS:
+Total files analyzed: 4885
+
+CLASS DISTRIBUTION BY SPLIT:
+
+TRAIN Split:
+  Class 1 (control_diet): 1079 images
+  Class 2 (low_forage_diet): 1268 images
+  Class 3 (high_forage_diet): 1558 images
+  Split Total: 3905 images
+
+VALIDATION Split:
+  Class 1 (control_diet): 138 images
+  Class 2 (low_forage_diet): 162 images
+  Class 3 (high_forage_diet): 196 images
+  Split Total: 496 images
+
+TEST Split:
+  Class 1 (control_diet): 133 images
+  Class 2 (low_forage_diet): 157 images
+  Class 3 (high_forage_diet): 194 images
+  Split Total: 484 images
+
+FLIR SESSION ANALYSIS:
+
+FLIR0757:
+  Class 3 (high_forage_diet): 534 images
+
+FLIR0759:
+  Class 3 (high_forage_diet): 754 images
+
+FLIR0761:
+  Class 2 (low_forage_diet): 458 images
+
+FLIR0767:
+  Class 1 (control_diet): 458 images
+
+FLIR0769:
+  Class 2 (low_forage_diet): 532 images
+
+FLIR0773:
+  Class 2 (low_forage_diet): 597 images
+
+FLIR0779:
+  Class 3 (high_forage_diet): 660 images
+
+FLIR0783:
+  Class 1 (control_diet): 203 images
+
+FLIR0785:
+  Class 1 (control_diet): 689 images

metadata/class_definitions.json

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+{
+  "class_definitions": {
+    "background": {
+      "class_id": 0,
+      "pixel_value": 0,
+      "name": "background",
+      "description": "Background regions without methane plumes, including ice block and ambient environment",
+      "color_rgb": [0, 0, 0]
+    },
+    "control_diet": {
+      "class_id": 1,
+      "pixel_value": 1,
+      "name": "control_diet",
+      "description": "Methane plumes from control diet (50:50 forage to concentrate ratio)",
+      "gc_range_ppm": "166-171",
+      "diet_composition": {
+        "forage_percentage": 50,
+        "concentrate_percentage": 50,
+        "description": "Standard dairy cow diet with balanced forage to concentrate ratio"
+      },
+      "color_rgb": [255, 0, 0]
+    },
+    "low_forage_diet": {
+      "class_id": 2,
+      "pixel_value": 3,
+      "name": "low_forage_diet", 
+      "description": "Methane plumes from low forage diet (20:80 forage to concentrate ratio)",
+      "gc_range_ppm": "300-334",
+      "diet_composition": {
+        "forage_percentage": 20,
+        "concentrate_percentage": 80,
+        "description": "High-concentrate diet with reduced forage content"
+      },
+      "color_rgb": [0, 255, 0]
+    },
+    "high_forage_diet": {
+      "class_id": 3,
+      "pixel_value": 2,
+      "name": "high_forage_diet",
+      "description": "Methane plumes from high forage diet (80:20 forage to concentrate ratio)", 
+      "gc_range_ppm": "457-510",
+      "diet_composition": {
+        "forage_percentage": 80,
+        "concentrate_percentage": 20,
+        "description": "High-forage diet with minimal concentrate supplementation"
+      },
+      "color_rgb": [0, 0, 255]
+    }
+  },
+  "excluded_classes": {
+    "control_bromoform": {
+      "description": "Control diet with bromoform addition (0.14 mg/L)",
+      "gc_range_ppm": "~1.41",
+      "exclusion_reason": "Methane concentration below OGI camera detection limit due to bromoform inhibition"
+    }
+  },
+  "class_mapping": {
+    "0": "background",
+    "1": "control_diet", 
+    "2": "low_forage_diet",
+    "3": "high_forage_diet"
+  },
+  "pixel_to_class_mapping": {
+    "0": 0,
+    "1": 1,
+    "2": 3,
+    "3": 2
+  },
+  "total_classes": 4,
+  "annotation_format": "Binary masks with pixel values 0-3 corresponding to class IDs",
+  "validation_method": "Gas Chromatography (GC) concentration measurements",
+  "notes": {
+    "concentration_correlation": "Class assignments based on measured GC concentration ranges from corresponding dietary treatments",
+    "mask_generation": "Automated pipeline with background subtraction, thresholding, and watershed segmentation",
+    "quality_assurance": "Manual verification of automated mask generation results",
+    "pixel_value_discrepancy": "Class IDs follow paper numbering (Class 2=Low Forage, Class 3=High Forage), but pixel values in masks are swapped (Low Forage=3, High Forage=2). Dataset loader handles this conversion automatically."
+  }
+} 

metadata/dataset_statistics.json

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+{
+  "dataset_statistics": {
+    "overview": {
+      "name": "Controlled Diet (CD) Dataset",
+      "version": "1.0.0",
+      "total_images": 4885,
+      "total_masks": 4885,
+      "total_files": 9770,
+      "image_format": "PNG",
+      "mask_format": "PNG",
+      "image_resolution": "640x480"
+    },
+    "split_distribution": {
+      "train": {
+        "images": 3905,
+        "percentage": 79.94,
+        "class_breakdown": {
+          "class_1_control": 1079,
+          "class_2_low_forage": 1268,
+          "class_3_high_forage": 1558
+        }
+      },
+      "validation": {
+        "images": 496,
+        "percentage": 10.15,
+        "class_breakdown": {
+          "class_1_control": 138,
+          "class_2_low_forage": 162,
+          "class_3_high_forage": 196
+        }
+      },
+      "test": {
+        "images": 484,
+        "percentage": 9.91,
+        "class_breakdown": {
+          "class_1_control": 133,
+          "class_2_low_forage": 157,
+          "class_3_high_forage": 194
+        }
+      }
+    },
+    "class_statistics": {
+      "class_1_control": {
+        "gc_range_ppm": "166-171",
+        "diet_type": "Control (50:50 F:C)",
+        "total_images": 1350,
+        "percentage_of_dataset": 27.63,
+        "train_images": 1079,
+        "validation_images": 138,
+        "test_images": 133
+      },
+      "class_2_low_forage": {
+        "gc_range_ppm": "300-334", 
+        "diet_type": "Low Forage (20:80 F:C)",
+        "total_images": 1587,
+        "percentage_of_dataset": 32.49,
+        "train_images": 1268,
+        "validation_images": 162,
+        "test_images": 157
+      },
+      "class_3_high_forage": {
+        "gc_range_ppm": "457-510",
+        "diet_type": "High Forage (80:20 F:C)",
+        "total_images": 1948,
+        "percentage_of_dataset": 39.88,
+        "train_images": 1558,
+        "validation_images": 196,
+        "test_images": 194
+      }
+    },
+    "model_performance_baseline": {
+      "best_model": "Gasformer",
+      "best_miou_percent": 85.1,
+      "best_fscore_percent": 91.72,
+      "fastest_fps": 64.56,
+      "most_efficient_gflops": 9.92,
+      "smallest_params_m": 3.65
+    },
+    "collection_metadata": {
+      "collection_date": "2024",
+      "location": "Southern Illinois University Carbondale",
+      "team_members": [
+        "Mohamed G. Embaby",
+        "Toqi Tahamid Sarker", 
+        "Amer AbuGhazaleh",
+        "Khaled R. Ahmed"
+      ]
+    }
+  },
+  "generation_timestamp": "2025-01-19T12:00:00Z",
+  "statistics_version": "1.0.0"
+} 

metadata/metadata.json

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+{
+  "name": "Controlled Diet (CD) Dataset for Methane Plume Detection",
+  "version": "1.0.0",
+  "description": "A large-scale collection of 4,885 methane (CH₄) plume images captured using optical gas imaging (OGI) technology for semantic segmentation tasks",
+  "authors": [
+    {
+      "name": "Mohamed G. Embaby",
+      "affiliation": "Southern Illinois University Carbondale",
+      "email": "embaby@siu.edu"
+    },
+    {
+      "name": "Toqi Tahamid Sarker", 
+      "affiliation": "Southern Illinois University Carbondale",
+      "email": "toqitahamid.sarker@siu.edu"
+    },
+    {
+      "name": "Amer AbuGhazaleh",
+      "affiliation": "Southern Illinois University Carbondale",
+      "email": "aamer@siu.edu"
+    },
+    {
+      "name": "Khaled R. Ahmed",
+      "affiliation": "Southern Illinois University Carbondale", 
+      "email": "kahmed@siu.edu"
+    }
+  ],
+  "license": "CC0-1.0",
+  "publication": {
+    "title": "Optical gas imaging and deep learning for quantifying enteric methane emissions from rumen fermentation in vitro",
+    "journal": "IET Image Processing",
+    "year": 2025,
+    "doi": "10.1049/ipr2.13327",
+    "url": "https://doi.org/10.1049/ipr2.13327"
+  },
+  "funding": {
+    "agency": "National Institute of Food and Agriculture, United States Department of Agriculture",
+    "award_number": "2022-70001-37404"
+  },
+  "dataset_info": {
+    "total_images": 4885,
+    "image_resolution": "640x480",
+    "file_format": "PNG",
+    "camera": "FLIR GF77 OGI camera",
+    "spectral_range": "7-8.5 μm",
+    "annotation_type": "semantic segmentation masks",
+    "classes": 4,
+    "background_method": "ice block thermal contrast"
+  },
+  "splits": {
+    "train": {
+      "images": 3905,
+      "percentage": 80
+    },
+    "validation": {
+      "images": 496,
+      "percentage": 10
+    },
+    "test": {
+      "images": 484,
+      "percentage": 10
+    }
+  },
+  "class_distribution": {
+    "class_1": {
+      "gc_range_ppm": "166-171",
+      "diet": "Control (50:50 F:C ratio)",
+      "train": 1079,
+      "validation": 138,
+      "test": 133,
+      "total": 1350
+    },
+    "class_2": {
+      "gc_range_ppm": "300-334", 
+      "diet": "Low Forage (20:80 F:C ratio)",
+      "train": 1268,
+      "validation": 162,
+      "test": 157,
+      "total": 1587
+    },
+    "class_3": {
+      "gc_range_ppm": "457-510",
+      "diet": "High Forage (80:20 F:C ratio)", 
+      "train": 1558,
+      "validation": 196,
+      "test": 194,
+      "total": 1948
+    }
+  },
+  "experimental_setup": {
+    "source": "In vitro continuous culture fermentation system",
+    "simulation": "Cow rumen environment",
+    "collection_method": "24-hour ANKOM batch culture",
+    "validation_methods": ["Gas Chromatography (GC)", "Laser Methane Detector (LMD)"],
+    "temperature": "22°C controlled room temperature"
+  },
+  "mask_generation": {
+    "method": "Automated pipeline",
+    "steps": [
+      "Background subtraction using pre-recorded reference frames",
+      "Contrast enhancement for improved plume visibility",
+      "Adaptive thresholding for binary separation",
+      "Watershed algorithm with Sobel filter elevation maps",
+      "Region analysis with size-based filtering",
+      "Binary mask generation for pixel-wise annotations"
+    ]
+  },
+  "applications": [
+    "Semantic segmentation model training",
+    "Agricultural monitoring and assessment",
+    "Environmental research on livestock emissions", 
+    "Computer vision system development",
+    "Climate change mitigation strategy evaluation"
+  ],
+  "keywords": [
+    "optical gas imaging",
+    "methane detection", 
+    "semantic segmentation",
+    "livestock emissions",
+    "computer vision",
+    "deep learning",
+    "agriculture",
+    "climate change",
+    "FLIR GF77",
+    "rumen fermentation"
+  ],
+  "created": "2025-01-19",
+  "updated": "2025-01-19",
+  "format_version": "1.0",
+  "schema": "https://schema.org/Dataset"
+}