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# The Open-source Machine Vision Project
- [Overview](#overview)
- [ Building the firmware from source](#building-the-firmware-from-source)
- [Tensorflow support](#tensorflow-support)
- [Interface library](#interface-library)
+ [Note on serial port](#note-on-serial-port)
- [ Building the firmware from source](#building-the-firmware-from-source)
## Overview
The OpenMV project aims at making machine vision more accessible to beginners by developing a user-friendly, open-source, low-cost machine vision platform. OpenMV cameras are programmable in Python3 and come with an extensive set of machine learning and image processing functions such as face detection, keypoints descriptors, color tracking, QR and Bar code decoding, AprilTags, GIF and MJPEG recording, and more.
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The first generation of OpenMV cameras is based on STM32 ARM Cortex-M Digital Signal Processors (DSPs) and OmniVision sensors. The boards have built-in RGB and IR LEDs, USB FS support for programming and video streaming, a uSD socket, and I/O headers breaking out PWM, UARTs, SPI, I2C, CAN, and more. Additionally, the OpenMV Cam supports extension modules (shields) using the I/O headers for adding a WiFi adapter, a LCD Display, a Thermal Vision Sensor, a Motor Driver, and more.
The OpenMV project was successfully funded via Kickstarter back in 2015 and has come a long way since then. For more information, please visit [https://openmv.io](https://openmv.io)
## Building the firmware from source
For more information on how to build the OpenMV firmware from source, see [Building the Firmware From Source](https://github.com/openmv/openmv/blob/master/src/README.md)
## Tensorflow support
The OpenMV firmware supports loading quantized Tensorflow Lite models. The firmware supports loading external models that reside on the filesystem to memory (on boards with SDRAM), and internal models (embedded into the firmware) in place. To load an external Tensorflow model from the filesystem from Python use [`tf`](https://docs.openmv.io/library/omv.tf.html) Python module. For information on embedding Tensorflow models into the firmware, and loading them, please see [Tensorflow Support](https://github.com/openmv/openmv/edit/master/src/lib/libtf/README.md).
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if line: print(line)
```
The above code works for Windows, Mac, or Linux. You just need to change the above port name to the same name of the USB VCP port the OpenMV Cam shows up as (it will be under `/dev/` on Mac or Linux). Note that if you are opening the USB VCP port using another serial library and/or language make sure to set the DTR line to false - otherwise the OpenMV Cam will suppress printed output.
## Building the firmware from source
For more information on how to build the OpenMV firmware from source, see [Building the Firmware From Source](https://github.com/openmv/openmv/blob/master/src/README.md)