it4_chana_app1 Computer Vision Project

Here are a few use cases for this project:

1. Grain Quality Inspection and Analytics: This computer vision model could be used in agricultural and related industries to automate the process of identifying and sorting different types of chana (chickpeas). The identification of broken samples as well as organic/inorganic classes would enable the maintenance of quality standards and guarantee of product purity.

2. Learning and Education: This model could be used as a teaching tool for agricultural students studying grain types and properties. It can help students learn to differentiate between Desi, Hybrid, Mexico, Dabra and other classes of chana.

3. Agricultural Trading Industries: The model could be valuable for food trading companies for fast and accurate inspection of acquired stock. By identifying the type and quality of products, fair pricing systems can be implemented, ensuring transparency in trading.

4. Grocery Stores/Supermarkets: Retailers could use this computer vision model to conduct an in-depth inventory analysis, allowing them to understand what classes of grains they have in stock and identify if they have received any broken or non-organic grain, ensuring the products they sell meet their quality standards.

5. Consumer Shopping Applications: An app for consumers could use this model to educate shoppers about the types and quality of the grains they buy. Users could take a photo of chana they're considering purchasing, and the app could tell them what type the grain is and whether it’s organic, hybrid, or inorganic.