Flower Identification and Quality Assessment using ML and CNN

The floricultural assiduity of India is huge and diversified. Other diligence similar to herbal assiduity, drugs, scents, spices, cosmetics, skincare, and medicinal diligence is dependent on the floricultural diligence directly or laterally. That is why it's important to check the quality of the flowers before they're applied to other diligence to maintain thickness in the quality of the flowers and to meet client satisfaction. still, delicate floricultural products are veritably perishable and vulnerable to the external terrain. therefore, exposing them to the external terrain for a long time for quality checking can reduce their overall life. Statistics show that the postharvest processing loss for fresh-cut flowers can be as high as 31.88, of which the grading loss makes up 21.74. So, it's important to make a system for quality checking and health classification of flowers through image scanning grounded on their appearance. So that, only healthy, fresh, non-infected flowers can be named, and dead, infected flowers can be barred from the process. Because of this force will be reduced for homemade checking and effectiveness will be bettered.