Create README.md

README.md

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+---
+task_categories:
+- object-detection
+language:
+- id
+- en
+tags:
+- poultry
+- chicken
+- animal-health
+- computer-vision
+- yolov11s
+- early-disease-detection
+- Indonesia
+---
+
+# `chbd-yolov11s-chicken-detector`
+
+This model is a YOLOv11s-based object detector specifically trained to identify individual chickens in farm environments. It is a core component of the "Chicken Health & Behavior Detection" multimodal project, aiming to provide visual insights for early disease detection and behavioral analysis in poultry farming.
+
+## Model Description
+
+The `chbd-yolov11s-chicken-detector` is an object detection model trained using the Ultralytics YOLOv11s architecture. It is designed to accurately locate and classify chickens within images and video frames, serving as a foundational step for downstream tasks such as chicken counting, density estimation, tracking, and the analysis of anomalous visual behaviors related to health.
+
+## Training Data
+
+This model was trained on the `vision-object-detection` datasets from [chicken-health-behavior-multimodal](https://huggingface.co/datasets/IceKhoffi/chicken-health-behavior-multimodal).
+
+The visual data within this dataset was curated from publicly available videos, specifically from the **Kipster Farm YouTube channel**. While Kipster Farm is located in the US, this data provides high-quality depictions of chicken behavior and general farm environments suitable for developing robust foundational detection models.
+
+* **Dataset Size :** Total images used for training and validation: 24 (21 training, 3 validation)
+* **Annotations :** Bounding boxes in YOLO format (`class_id x_center y_center width height`).
+* **Classes :** Currently trained for a single class: `0`.
+
+## Training Procedure
+
+The model was trained using the Ultralytics YOLO framework (version 8.3.162)
+
+* **Model :** `yolov11s.pt`
+* **Epochs :** 100
+* **Image Size :** 640x640 pixels
+* **Hardware :** Training was performed on a Tesla T4 GPU with 15095MiB memory
+* **Optimizer :** AdamW
+* **Python/Pytorch :** Python 3.11.13, PyTorch 2.6.0+cu124
+
+## How to Use
+
+You can load and use this model for inference with the Ultralytics YOLO library:
+
+```python
+from ultralytics import YOLO
+```
+import YOLO