copy and paste this google map to your website or blog!
Press copy button and paste into your blog or website.
(Please switch to 'HTML' mode when posting into your blog. Examples: WordPress Example, Blogger Example)
Vegetable Identifier – Instantly Recognize Vegetables with AI Upload a photo of any vegetable and let advanced AI instantly identify the type, variety, season, and nutritional info Fast, free, and accurate vegetable recognition tool for gardeners, cooks, and shoppers
Identification fruit and vegetables The following photos will allow you to identify fruit and vegetables Many of the vegetables listed here are available year-round The information on their season refers to their harvest times, i e their main season In this part of the site you can get tips for growing and using of some vegetables
Vegetable Classification Detection - GitHub Vegetable Classification Detection, a web-based tool, leverages Streamlit, TensorFlow, and OpenCV It employs CNN and YOLO models to classify and detect vegetables from images and live feeds, benefiting agriculture and food processing with accurate identification detection tasks
Free AI Plant Identifier (No Login Required) | Galaxy. ai Instantly identify plants with our advanced AI Plant Identifier Get detailed analysis of species, care requirements, and growing conditions Perfect for gardeners, botanists, and plant lovers
Plant. id - Plant identification app Plant id is a free plant identification service based on machine learning Take a photo, upload it, and instantly get a name and information about your plant
Fruits and Vegetables Image Dataset for AI and ML Projects A diverse Fruits and Vegetables Image Dataset designed for machine learning and image recognition tasks Featuring 36 food categories, this dataset includes organized training, testing, and validation sets to support AI projects like food identification and recipe suggestion applications Ideal for educational and non-commercial use
Vegetable Identification Vegetable Image Recognition Dataset <p>The dataset contains images of six types of vegetables: eggplant, beans, okra, squash, potatoes, and onions, with 800 images of each type, for a total of 4,800 images It aims to enhance the capabilities of machine learning and computer vision in vegetable detection, classification, and recognition < p>