intern_work_5 Computer Vision Project
Updated a year ago
287
13
Metrics
Here are a few use cases for this project:
-
Vehicle Damage Assessment: Companies operating car rental services or insurance sectors can use the "intern_work_5" model to identify the severity of dents or scratches on vehicles before and after they are rented out. This would save manual inspection time and ensure a fair damage tracking system.
-
Home Appliance Quality Inspection: Manufacturers and retailers of household appliances such as dishwasher, refrigerator, or washing machine can use this model to identify any damages before shipping the products, thus improving the quality check process.
-
Second-hand Goods Marketplace: Online platforms trading second-hand goods can use this computer vision model to identify and categorize the condition of the goods, helping buyers better understand the product's condition.
-
Shipping/Delivery Companies: These companies can use "intern_work_5" model to scan packages before and after delivery, keeping a record of any damages incurred during transport, and ensuring accountability.
-
Automobile Repair Services: Workshops and automobile repair services can use the model to efficiently identify and classify the damage severity on cars, enabling faster and more accurate cost estimates for repairs.
Use This Trained Model
Try it in your browser, or deploy via our Hosted Inference API and other deployment methods.
Build Computer Vision Applications Faster with Supervision
Visualize and process your model results with our reusable computer vision tools.
Cite This Project
If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
intern_work_5_dataset,
title = { intern_work_5 Dataset },
type = { Open Source Dataset },
author = { work 2 },
howpublished = { \url{ https://universe.roboflow.com/work-2-epeop/intern_work_5 } },
url = { https://universe.roboflow.com/work-2-epeop/intern_work_5 },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { aug },
note = { visited on 2024-11-21 },
}