Build a color-based object sorting system using the TCS34725 sensor and a Raspberry Pi

 Let’s build a color-based object sorting system using the TCS34725 sensor and a Raspberry Pi. This project can classify objects (e.g., Skittles, LEGO bricks) by color and trigger actions (e.g., servo motors, LEDs, or even a robotic arm). Here’s how to do it:

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Project Overview

1. Hardware Setup

   • Raspberry Pi + TCS34725 sensor

   • Servo motor (to push objects into bins)

   • LED feedback (optional)

   • Conveyor belt (optional, for automation)

2. Software Logic

   • Calibrate sensor for target colors (e.g., red, green, blue).

   • Classify objects based on RGB values.

   • Trigger servo/LED when a color is detected.

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Step 1: Wiring (Add a Servo Motor)

Component	Raspberry Pi Pin
TCS34725 (VCC)	3.3V (Pin 1)
TCS34725 (GND)	GND (Pin 6)
TCS34725 (SDA)	GPIO2 (Pin 3)
TCS34725 (SCL)	GPIO3 (Pin 5)
Servo PWM	GPIO17 (Pin 11)

(Use a separate 5V power supply for the servo if needed.)

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Step 2: Install Servo Control Library

bash

sudo pip3 install gpiozero

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Step 3: Python Code (Color Sorting Logic)

python

import time
import Adafruit_TCS34725
from gpiozero import Servo, LED

# Initialize hardware
tcs = Adafruit_TCS34725.TCS34725()
servo = Servo(17)  # GPIO17
led_red = LED(22)   # GPIO22 (optional)

# Color thresholds (calibrate these for your objects!)
COLOR_THRESHOLDS = {
    "red":   ((150, 50, 50), (255, 100, 100)),  # Min/Max (R, G, B)
    "green": ((50, 150, 50), (100, 255, 100)),
    "blue":  ((50, 50, 150), (100, 100, 255)),
}

def classify_color(r, g, b):
    for color, ((r_min, g_min, b_min), (r_max, g_max, b_max)) in COLOR_THRESHOLDS.items():
        if (r_min <= r <= r_max) and (g_min <= g <= g_max) and (b_min <= b <= b_max):
            return color
    return "unknown"

try:
    while True:
        r, g, b, _ = tcs.get_raw_data()
        r_norm = int((r / (r + g + b)) * 255)  # Normalize
        g_norm = int((g / (r + g + b)) * 255)
        b_norm = int((b / (r + g + b)) * 255)

        color = classify_color(r_norm, g_norm, b_norm)
        print(f"Detected: {color} (R: {r_norm}, G: {g_norm}, B: {b_norm})")

        # Trigger actions
        if color == "red":
            servo.max()  # Move servo to 90°
            led_red.on()
        elif color == "green":
            servo.mid()  # Move servo to 45°
            led_red.off()
        elif color == "blue":
            servo.min()  # Move servo to 0°
            led_red.off()

        time.sleep(1)

except KeyboardInterrupt:
    servo.close()
    led_red.off()

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Step 4: Calibration

1. Place a red object under the sensor and note the (R, G, B) values.

2. Repeat for green/blue objects.

3. Adjust COLOR_THRESHOLDS in the code to match your readings.

(Tip: Use print(r_norm, g_norm, b_norm) to debug values.)

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Step 5: Mechanical Sorting

• Attach a cardboard arm to the servo to push objects into bins.

• Use a sloped track to guide objects after sorting.

• For a conveyor belt, add a motor controlled via GPIO.

https://i.imgur.com/JQ8WzVl.png
(Example: Servo arm pushes objects left/right based on color.)

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Troubleshooting

Issue	Solution
Servo jitters	Use a capacitor or external power.
Wrong colors detected	Re-calibrate thresholds.
Sensor noise	Add a diffuser (e.g., white paper).

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Extensions

1. Add a Database
   Log sorted colors to a CSV/SQLite file:

   python

   import csv
   with open('colors.csv', 'a') as f:
       csv.writer(f).writerow([time.time(), color])

2. Web Interface
   Use Flask to display sorting stats in real-time:

   python

   from flask import Flask
   app = Flask(__name__)
   @app.route("/")
   def stats():
       return f"Last sorted: {color}"

3. Machine Learning
   Train a K-NN classifier for more colors (e.g., purple, yellow).

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Demo Video Idea

• Show Skittles being sorted into cups by color.

• Use LEDs to light up the bin where the object lands.