In recent years, due to heightened health awareness, many daily meal tracking mobile apps have been released. Some of them use fruit image recognition to estimate not only the fruit name but also the calories of the fruit. However, these applications often require the user to enter information such as fruit category, size, and quantity, which can be cumbersome based on subjective evaluation. To overcome these inconveniences, automatic fruit photo detection is being adopted on mobile devices. However, in most cases, estimated calories are only associated with the estimated fruit category, or relative to the standard size of each fruit category. This is usually specified manually by the user. Currently, no applications exist that can estimate fruit calories automatically. Although CNN based image recognition methods have considerably solved most of the image recognition tasks including fruit recognition. fullyautomatic fruit calorie estimation from a photo still remains an enigma. This paper proposes a new portfolio of pictures include popular fruits. A portfolio named as fruits. As a second object . a deep intimated neural signal is trained to facilitate identification of fruit image this part can find more larger array of picture It is here that the fruits dataset is described as to how it is created and what its contents are, the aim of the project is developing a application for estimating a fruit calorie and improve peoples consumption conducts for health care.
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Component List
- raspberry pi
- Webcam
- Power supply
- wires and jumper
Features
- detects the name of fruits and its calories with image processing
