changed sensor data to db in other function

Resolve "Als gebruiker wil ik dat mijn data word opgeslagen in een database om data terug te zien"

Closes #35

See merge request technische-informatica-sm3/ti-projectten/rooziinuubii79!4

README.md

@@ -1,8 +1,39 @@
-# TI-project - Kobuki
+# TI-project - exploration robot Kobuki
 
 ## Description
-This project is a kobuki that drives around in dangerous areas and detects objects in its path. It uses a camera to detect objects. The kobuki is able to drive around in a room and detect objects.
+This project is a kobuki that drives around in dangerous areas and detects objects in its path. It uses a camera to detect objects. The purpose of this project is to explore dangerous areas without risking human lives. You are able to control the robot using controller on the website. 
 
 ## Photos
 ![Kobuki](/docs/assets/KobukiPhoto.jpg)
 
+## Installation
+
+### Requirements
+
+- Kobuki robot
+- Raspberry Pi (minimum 3B)
+- Camera
+- power supply for Raspberry Pi
+- laptop or computer
+
+### Steps
+
+1. **Install Python and Pip**
+   - Ensure you have Python installed on your system. You can download it from [python.org](https://www.python.org/).
+   - Pip is the package installer for Python. It usually comes with Python, but you can install it separately if needed.
+
+2. **Clone Our Repository**
+    - Clone our repository to your local machine doing the following :
+        - Open your terminal
+        - Change the current working directory to the location where you want the cloned directory.
+        - Type `git clone https://gitlab.fdmci.hva.nl/technische-informatica-sm3/ti-projectten/rooziinuubii79.git
+  
+3. **Install the required packages**
+    - Open the terminal and navigate to the project - scr - Python - flask.
+    - Run the following command to install the required packages:
+        - `pip install -r requirements.txt`
+        -  This will install all the python packages required to run the project.
+        -  for C++, you will need to install the following packages:
+           - OpenCV
+           - mqtt-client
+4.   

src/Python/flask/requirements.txt

@@ -3,3 +3,4 @@ paho-mqtt==1.6.1
 ultralytics==8.3.58 
 opencv-python-headless==4.6.0.66
 numpy==1.23.4
+mysql-connector-python==9.1.0

src/Python/flask/web/app.py

@@ -1,4 +1,4 @@
-from flask import Flask, Response, request, render_template, jsonify
+from flask import Flask, Response, request, render_template, jsonify, g
 import paho.mqtt.client as mqtt
 from ultralytics import YOLO
 import cv2
@@ -49,18 +49,6 @@ def on_message(client, userdata, message):
                     cv2.rectangle(processed_image, (x1, y1), (x2, y2), (0, 255, 0), 2)
                     cv2.putText(processed_image, f"{class_name} {box.conf.item():.2f}", (x1, y1 - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.9, (0, 255, 0), 2)
 
-
-# Globale MQTT setup
-def on_message(client,userdata, message):
-    global kobuki_message, latest_image
-    if message.topic == "kobuki/data":
-        kobuki_message = str(message.payload.decode("utf-8"))
-        with app.app_context():
-            sensor_data(kobuki_message)  # Sla de data op in de database
-    elif message.topic == "kobuki/cam":
-        latest_image = message.payload
-
-
 # Create an MQTT client instance
 mqtt_client = mqtt.Client()
 mqtt_client.username_pw_set("server", "serverwachtwoordofzo")
@@ -132,7 +120,9 @@ def database():
     cursor.close()
     return str(rows)
     
-def sensor_data(kobuki_message):
+
+@app.route('/data', methods=['GET'])
+def data():
     try:
         # Parse de JSON-string naar een Python-dictionary
         data = json.loads(kobuki_message)
@@ -165,12 +155,10 @@ def sensor_data(kobuki_message):
         print(f"JSON decode error: {e}")
     except mysql.connector.Error as err:
         print(f"Database error: {err}")
-
-@app.route('/data', methods=['GET'])
-def data():
     return kobuki_message
     
 
+
 @app.route('/image')
 def image():
     global processed_image

src/Python/flask/web/static/script.js

@@ -35,6 +35,7 @@ document.addEventListener("DOMContentLoaded", function() {
   }
 
   // Parse the data and show it on the website
+  async function parseData() {
     const data = await fetchData();
     const sensorDataContainer = document.getElementById("sensor-data");
     sensorDataContainer.innerHTML = ""; // Clear previous data
@@ -58,4 +59,3 @@ document.addEventListener("DOMContentLoaded", function() {
   // Update the image every 200 milliseconds
   setInterval(updateImage, 100);
 });
-