GreenMerge (Plant Image Collator)

GreenMerge is a plant image collator for plant phenotyping. It can be used to collect plant images from multiple IoT devices and store them in a database. It also provides a web interface for users to view and download images.

✨ Key Features

• Support for Multiple IoT Devices: Seamlessly compatible with a variety of IoT devices, including Raspberry Pi, Arduino, and more. Learn More
• Extensive Image Format Support: Accommodates a wide range of popular image formats, such as JPG, PNG, ensuring flexible image processing.
• User-Friendly Web Interface: Provides an intuitive web interface for users to easily view and download images.
• Collator Status Monitoring: Enables real-time monitoring of the collator's status, ensuring smooth operation and high efficiency.

🛠️ Hardware Requirements

Server

• Any system capable of running Docker and Docker-compose. This includes computers and single-board computers (SBCs) with the following specifications:
  • Operating System: Must support Docker (Linux, Windows, macOS).
  • Processor: Compatible with ARM64 architecture (for ARM64 OS, requires a CPU greater than ARMv8.2).
  • Memory: Minimum of 1GB RAM.

Collator

• The collator can be either a Single Board Computer (SBC) or a Microcontroller Unit (MCU):

  • SBC Option:

    • Must be Linux-compatible and equipped with a camera.
    • Examples include Raspberry Pi Zero 2 W with a camera module like Raspberry Pi camera (IMX219).
    • Storage: SD card or appropriate storage medium for the SBC.

  • MCU Option:

    • Must support MicroPython and be equipped with a camera.
    • Suitable for MCUs that can handle image capture and basic processing.
    • Camera compatibility is essential for effective image collation.

These hardware setups ensure smooth operation of GreenMerge, allowing for efficient image collection and processing across different environments.

🔧 Installation

Server Setup

The setup process is similar across Windows, Linux, macOS, and Single Board Computers (SBCs). Follow these steps:

1. Install Docker and Docker-Compose:

   • For Windows/Linux/macOS, download and install Docker and Docker-Compose from their official websites.
   • For SBCs, ensure the OS supports Docker and install them accordingly.

2. Clone the Repository:

   • Use the command git clone https://github.com/hibana2077/plant_image_collator.git to clone the GreenMerge repository to your local system.

3. Build and Start the Container:

   • Navigate to the plant_image_collator/server directory.
   • Run docker-compose up -d --build. This command builds and starts the container in detached mode.

4. Access the Web Interface:

   • Once the container is running, open your web browser and go to http://localhost:8501 or http://<your ip address>:8501 to access the web interface.

This installation process sets up the GreenMerge server, allowing you to start managing and collating plant images effectively.

Collator Setup

Raspberry Pi Series + IMX219 Camera Module

Follow these steps to set up a Raspberry Pi as a collator:

1. Prepare the SD Card:

   • Use the Raspberry Pi Imager to flash Raspberry Pi OS Lite (32 bit) onto the SD card.
   • Before flashing, press Ctrl+Shift+X to access advanced options. Set your hostname, configure WiFi credentials, and enable SSH.

2. Initial Raspberry Pi Setup:

   • Insert the flashed SD card into the Raspberry Pi and power it on.
   • Connect to the Raspberry Pi via SSH: ssh pi@<your hostname>.local and log in with your password.

3. Configure Camera Settings:

   • Edit the file /boot/config.txt and add camera_auto_detect=0 and dtoverlay=imx219 at the end.
   • Open the Raspberry Pi configuration tool with sudo raspi-config, navigate to Interfacing Options -> Camera, and enable it.

4. Update and Install Dependencies:

   • Update the OS with: sudo apt update and sudo apt upgrade.
   • Install Git: sudo apt install git.

5. Clone Repository and Setup:

   • Clone the GreenMerge repository: git clone https://github.com/hibana2077/plant_image_collator.git && cd plant_image_collator.
   • Run the setup script: sudo bash ./raspberry_pi_setup.sh.
   • Reboot the Raspberry Pi: sudo reboot.

6. Configure Collator Settings:

   To customization the collator's operations, edit the collator/config.yaml file with the following settings:

   • encoding: Specify the image format. Example: "png".
   • interval: Set the time interval (in seconds) for image capture. Example: "360" (for capturing images every 360 seconds).
   • notify: Enable or disable notifications. Set to True for enabling notifications.
   • verbose: Enable detailed logging. Set to True for more detailed logs.
   • node_name: Define the name of the node. Example: "NODE_NAME".
   • notify_webhook: Provide the webhook URL for notifications. Example: "NOTIFY_WEBHOOK".
   • plant_name: Name the plant being monitored. Example: "PLANT_NAME".
   • URL: Set the URL for the server where images are sent. Example: "http://YOUR_IP:5000/".

7. Start the Collator:

   • Start the collator with: sudo bash ./raspberry_pi_start.sh.

8. Test Camera Module:

   • Test the camera with libcamera-jpeg -o test.jpg.
   • Download the test image to your computer with scp pi@<your hostname>.local:test.jpg ..

ESP32-CAM

(Still under development)

📝 License

This project is licensed under the MIT License. See the LICENSE file for details.