FC1_R Instance Segmentation Dataset and Pre-Trained Model by GGSIPU

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Explore Dataset

Here are a few use cases for this project:

Grocery Inventory Management: The FC1_R model could be used in a retail environment to automatically identify and count the stock of different food items on grocery store shelves or in refrigerators.
Home Inventory Tracking: In a smart home system, the model might be applied to help homeowners keep track of their food inventory and generate shopping lists automatically, based on what is identified in their fridge or pantry.
Waste Reduction in Food Industry: Restaurants or commercial kitchens could utilize this model to better track food storage and usage, in turn reducing waste by ensuring perishables are used before their expiration date and restocking is accurately predicted.
Visual Assistance for Visually Impaired: This model can also aid visually impaired or elderly individuals by identifying their stored food items, helping them to maintain independence in the kitchen.
Automatic Vending Machine Refill: In the case of automated vending machines or smart fridges in offices or communal spaces, FC1_R could detect when certain items are running low and automatically send a restocking request.

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{
                            fc1_r_dataset,
                            title = { FC1_R Dataset },
                            type = { Open Source Dataset },
                            author = { GGSIPU },
                            howpublished = { \url{ https://universe.roboflow.com/ggsipu-szsk2/fc1_r } },
                            url = { https://universe.roboflow.com/ggsipu-szsk2/fc1_r },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { dec },
                            note = { visited on 2024-04-28 },
                            }