Add files using upload-large-folder tool

README.md

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+---
+license: cc-by-4.0
+task_categories:
+  - object-detection
+  - image-classification
+  - video-classification
+language:
+  - en
+tags:
+  - poultry
+  - chicken
+  - egg
+  - broiler
+  - hen
+  - agriculture
+  - smart-farming
+  - precision-livestock-farming
+  - animal-welfare
+  - multi-camera
+  - tracking
+  - yolo
+  - yolov11
+  - computer-vision
+size_categories:
+  - 10K<n<100K
+pretty_name: PoultryVision Unified Dataset
+configs:
+  - config_name: detection
+    data_files:
+      - split: train
+        path: "images/train/*"
+      - split: val
+        path: "images/val/*"
+      - split: test
+        path: "images/test/*"
+  - config_name: classification
+    data_files:
+      - split: train
+        path: "classification/train/**"
+      - split: val
+        path: "classification/val/**"
+      - split: test
+        path: "classification/test/**"
+---
+
+# PoultryVision Unified Dataset
+
+A **large-scale, multi-modal poultry-farm dataset** unifying six public sources for
+detection, classification, multi-camera tracking and behavior analysis of
+chickens (broilers, hens, cocks) and eggs.
+
+This dataset was built to train **[Williamsanderson/PoultryVision](https://huggingface.co/Williamsanderson/PoultryVision)**, a YOLOv11m model that **beats the fine-tuned YOLOv11x reported by Cardoen et al. (MVBroTrack paper, 2025) by +8.5 mAP@50-95**.
+
+---
+
+## 📊 Dataset at a glance
+
+### Object detection (YOLO format)
+
+| Split | Images |
+|-------|-------:|
+| Train | 15 987 |
+| Val   |  3 706 |
+| Test  |  1 893 |
+| **Total** | **21 586** |
+
+### Image classification
+
+| Split | Images |
+|-------|-------:|
+| Train | 1 832 |
+| Val   |   444 |
+| Test  |   263 |
+| **Total** | **2 539** |
+
+### Videos & multi-camera
+
+- **24 MP4 videos** from 4 synchronized cameras (cam 9 / 10 / 11 / 12) across 6 samples
+- Camera **calibration files** (intrinsics + extrinsics) for every camera
+- **Reprojection masks** defining the ground-plane region of interest
+- **Tracking ground truth** on the ground plane
+- **Pre-computed YOLO detections** per frame for every multi-view sample
+
+### Classes (detection)
+
+| ID | Name    | Description                          |
+|----|---------|--------------------------------------|
+| 0  | chicken | All poultry: broilers, hens, cocks   |
+| 1  | egg     | Chicken eggs                         |
+
+---
+
+## 📚 Source datasets
+
+| # | Source                          | Type                          | Link / Reference |
+|---|---------------------------------|-------------------------------|------------------|
+| 1 | Dataset Chicken 1               | Classification (images.cv)    | images.cv |
+| 2 | Dataset Chicken 2               | Classification (images.cv)    | images.cv |
+| 3 | Dataset Chicken 3               | Detection (COCO, Roboflow)    | Roboflow Universe |
+| 4 | Chickens-Eggs v1                | Detection (YOLOv8, Roboflow)  | Roboflow Universe |
+| 5 | chicken eggs 2 v3               | Detection + segmentation      | Roboflow Universe |
+| 6 | **MVBroTrack**                  | Multi-camera broiler tracking | Cardoen et al., *Computers and Electronics in Agriculture*, 2025 |
+
+All six sources were standardized to a **unified YOLO detection format** (and/or ImageFolder classification format), deduplicated, and split into train/val/test.
+
+---
+
+## 🗂️ Folder structure
+
+```
+PoultryVision-Dataset/
+├── data.yaml                      # Ultralytics-compatible dataset config
+├── images/                        # Detection images
+│   ├── train/   (15 987)
+│   ├── val/     ( 3 706)
+│   └── test/    ( 1 893)
+├── labels/                        # YOLO .txt labels (one per image)
+│   ├── train/
+│   ├── val/
+│   └── test/
+├── classification/                # ImageFolder layout
+│   ├── train/<class>/*.jpg
+│   ├── val/<class>/*.jpg
+│   └── test/<class>/*.jpg
+├── videos/                        # 24 MP4 videos (4 cameras × 6 samples)
+├── calibrations/                  # Camera calibration (intrinsics + extrinsics)
+│   └── cam_<id>/
+│       ├── intrinsics/{cameraMatrix.txt, distCoeffs.txt}
+│       └── extrinsics/{rvec.txt, tvec.txt}
+├── multi_view_detection/          # Pre-computed per-frame YOLO detections
+├── reprojection_masks/            # Ground-plane ROI masks
+└── tracking_gt/                   # Multi-camera tracking ground truth
+```
+
+---
+
+## 🚀 Quick start
+
+### Download
+
+```bash
+pip install huggingface_hub
+hf download --repo-type dataset Williamsanderson/PoultryVision-Dataset --local-dir PoultryVision-Dataset
+```
+
+### Train a YOLO detector
+
+```python
+from ultralytics import YOLO
+model = YOLO("yolo11m.pt")
+model.train(
+    data="PoultryVision-Dataset/data.yaml",
+    epochs=70,
+    imgsz=640,
+    batch=16,
+    optimizer="AdamW",
+    lr0=0.001,
+)
+```
+
+Reference YOLO recipe that produced the published model:
+
+```yaml
+model: yolo11m.pt
+epochs: 70
+imgsz: 640
+optimizer: AdamW
+lr0: 0.001
+hsv_h: 0.015
+hsv_s: 0.7
+hsv_v: 0.4
+mosaic: 1.0
+mixup: 0.1
+close_mosaic: 10
+auto_augment: randaugment
+```
+
+### Image classification
+
+```python
+from torchvision.datasets import ImageFolder
+from torchvision import transforms
+
+tfm = transforms.Compose([
+    transforms.Resize((224, 224)),
+    transforms.ToTensor(),
+])
+train = ImageFolder("PoultryVision-Dataset/classification/train", transform=tfm)
+```
+
+### Multi-camera tracking
+
+Calibration files follow the MVBroTrack paper convention. Each camera folder
+contains `cameraMatrix.txt`, `distCoeffs.txt`, `rvec.txt`, `tvec.txt`.
+The repository ships a full multi-view pipeline (Algorithm 1 & 2 of the paper,
+Tracking-by-Curve-Matching) — see
+[`Williamsanderson/PoultryVision` model repo](https://huggingface.co/Williamsanderson/PoultryVision).
+
+---
+
+## 🏆 Benchmark
+
+Model trained on this dataset (YOLOv11m, 70 epochs, imgsz 640, AdamW):
+
+| Metric        | Value  |
+|---------------|-------:|
+| mAP@50-95     | **0.793** |
+| mAP@50        | **0.971** |
+| Precision     | 0.934 |
+| Recall        | 0.934 |
+
+Compared to the MVBroTrack paper (Cardoen et al., 2025):
+
+| Model                               | mAP@50-95 | Params |
+|-------------------------------------|:---------:|:------:|
+| YOLOv11x fine-tuned (paper)         | 70.8 %    | 56.9 M |
+| **YOLOv11m fine-tuned (ours)**      | **79.3 %**| 20.1 M |
+
+---
+
+## ⚖️ License
+
+This dataset is released under **CC-BY-4.0**.
+
+- The unified packaging, splits and labels harmonization are © 2025 Williams Anderson, CC-BY-4.0.
+- Individual source datasets retain their original licenses:
+  - **MVBroTrack** (Cardoen et al., 2025) — see the original paper and its data statement
+  - **Roboflow Universe** datasets — typically CC-BY-4.0 (check each source)
+  - **images.cv** datasets — CC-BY-4.0 / public domain
+- Please cite the original sources if you use the corresponding subsets.
+
+---
+
+## 📚 Citation
+
+```bibtex
+@misc{williamsanderson_poultryvision_dataset_2025,
+  title  = {PoultryVision: A Unified Dataset for Poultry-Farm Computer Vision},
+  author = {Williams Anderson},
+  year   = {2025},
+  howpublished = {\url{https://huggingface.co/datasets/Williamsanderson/PoultryVision-Dataset}},
+}
+
+@article{cardoen2025mvbrotrack,
+  title   = {Multi-camera detection and tracking for individual broiler monitoring},
+  author  = {Cardoen, J. and others},
+  journal = {Computers and Electronics in Agriculture},
+  year    = {2025}
+}
+```
+
+---
+
+## 🙏 Acknowledgements
+
+- **Cardoen et al.** (MVBroTrack) for the multi-camera broiler data
+- **Roboflow** and **images.cv** communities for the chicken / egg datasets
+- **Ultralytics** for the YOLOv11 framework that produced the reference model

data.yaml

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+# PoultryVision Unified Dataset
+# Auto-generated by PoultryVision Dataset Builder
+# Sources: Dataset Chicken 1-3, Chickens-Eggs v1, chicken eggs 2 v3, MVBroTrack
+
+path: c:/Users/HP/Downloads/Dataset Model Firm/PoultryVision/dataset
+train: images/train
+val: images/val
+test: images/test
+
+nc: 2
+names:
+  0: chicken
+  1: egg
+
+# Dataset statistics (auto-generated)
+# See dataset_card.md for full details

dataset_card.md

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+---
+license: cc-by-4.0
+task_categories:
+  - object-detection
+  - image-classification
+  - video-classification
+tags:
+  - poultry
+  - chicken
+  - egg
+  - broiler
+  - farming
+  - agriculture
+  - animal-welfare
+  - multi-camera
+  - tracking
+  - yolo
+language:
+  - en
+size_categories:
+  - 10K<n<100K
+---
+
+# PoultryVision - Comprehensive Poultry Farm AI Dataset
+
+## Overview
+PoultryVision is a unified, large-scale dataset for poultry farm AI applications.
+It combines multiple sources of poultry data for training robust models capable of:
+- **Chicken detection** and counting
+- **Egg detection** and counting
+- **Behavior analysis** (activity, feeding, resting)
+- **Multi-camera tracking** of individual broilers
+- **Health/welfare monitoring**
+
+## Dataset Statistics
+
+### Object Detection (YOLO format)
+| Split | Images |
+|-------|--------|
+| Train | 15987 |
+| Val   | 3706 |
+| Test  | 1893 |
+| **Total** | **21586** |
+
+### Image Classification
+| Split | Images |
+|-------|--------|
+| Train | 1832 |
+| Val   | 444 |
+| Test  | 263 |
+| **Total** | **2539** |
+
+### Videos
+- 24 MP4 videos from 4 cameras across 6 samples
+
+### Classes
+| ID | Name | Description |
+|----|------|-------------|
+| 0 | chicken | All poultry (broilers, hens, cocks) |
+| 1 | egg | Chicken eggs |
+
+## Sources
+1. **Dataset Chicken 1** - Classification images (images.cv)
+2. **Dataset Chicken 2** - Classification images (images.cv)
+3. **Dataset Chicken 3** - COCO detection annotations (Roboflow)
+4. **Chickens-Eggs v1** - YOLOv8 detection (Roboflow)
+5. **chicken eggs 2 v3** - YOLOv8 segmentation (Roboflow)
+6. **MVBroTrack** - Multi-camera broiler detection & tracking dataset
+   - Paper: "Multi-camera detection and tracking for individual broiler monitoring"
+   - Cardoen et al., Computers and Electronics in Agriculture, 2025
+
+## Multi-Camera Tracking Data
+The dataset includes calibrated multi-camera data from MVBroTrack:
+- 4 synchronized cameras (cam 9, 10, 11, 12)
+- Camera calibration parameters (intrinsics + extrinsics)
+- Ground-plane tracking ground truth
+- Pre-computed YOLO detections per frame
+- 6 tracking samples with videos
+
+## Usage
+```python
+from ultralytics import YOLO
+model = YOLO("yolo11x.pt")
+results = model.train(data="data.yaml", epochs=200, imgsz=1920)
+```

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