Kuk Kuk Kai Object Detection Dataset and Pre-Trained Model by yolov8

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Explore Dataset

Here are a few use cases for this project:

Poultry Quality Control: The "Kuk Kuk Kai" model could be employed in poultry processing plants for automated quality control, inspecting the specific parts of the chicken (like the left and right thigh skin and meat) for consistency, maturity, or any abnormalities.
Food Safety Inspection: Regulatory bodies or food safety organizations can use this model to evaluate the health and safety of poultry products, by identifying specific parts of chicken thighs for potential issues like infection, discoloration, or contamination.
Culinary Education: Culinary schools and cooking courses can utilize this model as an educational tool for students to learn about different parts of chicken, their textures, and how to properly prepare them.
Nutritional Analysis: Nutritionists and dieticians can use this model to accurately identify chicken parts for a precise nutritional breakdown (fat content, protein content etc.), aiding in meal planning and dietary recommendations.
Grocery Store Application: The model could power an app feature in grocery store apps that allows customers to scan and identify different parts of chicken, helping shoppers with limited food knowledge to purchase exactly what recipe demands or according to their dietary preferences.

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

YOLOv8

This project has a YOLOv8 model checkpoint available for inference with Roboflow Deploy. YOLOv8 is a new state-of-the-art real-time object detection model.

Cite This Project

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{
                            kuk-kuk-kai_dataset,
                            title = { Kuk Kuk Kai Dataset },
                            type = { Open Source Dataset },
                            author = { yolov8 },
                            howpublished = { \url{ https://universe.roboflow.com/yolov8-ojalh/kuk-kuk-kai } },
                            url = { https://universe.roboflow.com/yolov8-ojalh/kuk-kuk-kai },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { sep },
                            note = { visited on 2024-05-15 },
                            }