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Drone Programmingprogramming~30 mins

Color-based tracking in Drone Programming - Mini Project: Build & Apply

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Color-based tracking
📖 Scenario: You are programming a drone to follow a red ball in a room. The drone uses a camera to see colors and moves to keep the red ball centered in its view.
🎯 Goal: Build a simple program that detects the red color in the camera feed and decides the drone's movement direction to follow the red ball.
📋 What You'll Learn
Create a dictionary called camera_feed with pixel colors as keys and their counts as values
Create a variable called red_threshold to decide when red is dominant
Use a for loop with variables color and count to iterate over camera_feed.items()
Create a variable called red_count to sum counts of red pixels
Print the drone's movement direction based on red detection
💡 Why This Matters
🌍 Real World
Drones use color tracking to follow objects like balls or markers in sports, delivery, or search and rescue.
💼 Career
Understanding color-based tracking helps in robotics, drone programming, and computer vision jobs.
Progress0 / 4 steps
1
DATA SETUP: Create the camera feed data
Create a dictionary called camera_feed with these exact entries: 'red': 15, 'green': 5, 'blue': 10, 'yellow': 3
Drone Programming
Hint

Use curly braces to create a dictionary with the exact colors and counts.

2
CONFIGURATION: Set the red detection threshold
Create a variable called red_threshold and set it to 10
Drone Programming
Hint

Just assign the number 10 to the variable red_threshold.

3
CORE LOGIC: Count red pixels in the camera feed
Create a variable called red_count and set it to 0. Then use a for loop with variables color and count to iterate over camera_feed.items(). Inside the loop, add count to red_count only if color is equal to 'red'.
Drone Programming
Hint

Use an if statement inside the loop to check if color is 'red' and add count to red_count.

4
OUTPUT: Print the drone's movement direction
Write a print statement that prints "Move forward" if red_count is greater than red_threshold. Otherwise, print "Search for red ball".
Drone Programming
Hint

Use an if-else statement to decide what to print based on red_count and red_threshold.

Practice

(1/5)
1. What is the main purpose of color-based tracking in drone programming?
easy
A. To make the drone follow an object by detecting its color
B. To control the drone's altitude using GPS
C. To improve the drone's battery life
D. To send commands to the drone via remote control

Solution

  1. Step 1: Understand color-based tracking concept

    Color-based tracking means the drone uses color detection to follow an object.
  2. Step 2: Identify the main goal

    The goal is to detect and follow an object by its color, not altitude or battery.
  3. Final Answer:

    To make the drone follow an object by detecting its color -> Option A
  4. Quick Check:

    Color-based tracking = follow object by color [OK]
Hint: Focus on color detection as the tracking method [OK]
Common Mistakes:
  • Confusing color tracking with GPS control
  • Thinking it manages battery or remote commands
  • Mixing color tracking with altitude control
2. Which of the following code snippets correctly initializes a color filter for red in a drone's tracking system?
easy
A. red_filter = {'lower': (0, 255, 255), 'upper': (10, 100, 100)}
B. red_filter = {'lower': [100, 0, 0], 'upper': [255, 10, 10]}
C. red_filter = {'low': (0, 100, 100), 'high': (10, 255, 255)}
D. red_filter = {'lower': (0, 100, 100), 'upper': (10, 255, 255)}

Solution

  1. Step 1: Check correct keys for filter dictionary

    The keys should be 'lower' and 'upper' to define color range.
  2. Step 2: Verify value types and ranges

    Values must be tuples with HSV ranges; red_filter = {'lower': (0, 100, 100), 'upper': (10, 255, 255)} uses correct keys and tuples.
  3. Final Answer:

    red_filter = {'lower': (0, 100, 100), 'upper': (10, 255, 255)} -> Option D
  4. Quick Check:

    Correct keys and tuple values = red_filter = {'lower': (0, 100, 100), 'upper': (10, 255, 255)} [OK]
Hint: Look for 'lower' and 'upper' keys with tuple HSV values [OK]
Common Mistakes:
  • Using wrong dictionary keys like 'low' or 'high'
  • Using lists instead of tuples for HSV values
  • Swapping lower and upper HSV ranges
3. Given the following code snippet for detecting a blue object, what will be printed if the detected object's center is at (150, 200)?
blue_filter = {'lower': (100, 150, 0), 'upper': (140, 255, 255)}
object_center = (150, 200)
if 100 <= object_center[0] <= 140:
    print('Blue object detected at', object_center)
else:
    print('No blue object detected')
medium
A. Blue object detected at (150, 200)
B. SyntaxError
C. No blue object detected
D. RuntimeError

Solution

  1. Step 1: Check the condition on x-coordinate

    Condition checks if 100 <= 150 <= 140, which is false because 150 > 140.
  2. Step 2: Determine which print executes

    Since condition is false, else block runs printing 'No blue object detected'.
  3. Final Answer:

    No blue object detected -> Option C
  4. Quick Check:

    150 not in 100-140 range = No detection [OK]
Hint: Check numeric range conditions carefully [OK]
Common Mistakes:
  • Assuming 150 is within 100 to 140 range
  • Confusing syntax errors with logic errors
  • Ignoring else block output
4. The following code is intended to detect a green object and print its position, but it raises an error. What is the error and how to fix it?
green_filter = {'lower': (40, 50, 50), 'upper': (80, 255, 255)}
object_center = None
if green_filter['lower'][0] <= object_center[0] <= green_filter['upper'][0]:
    print('Green object at', object_center)
else:
    print('No green object detected')
medium
A. SyntaxError due to incorrect dictionary keys; fix keys to 'low' and 'high'
B. TypeError because object_center is None; fix by assigning a tuple to object_center
C. IndexError because green_filter keys are missing; add keys
D. No error; code runs correctly

Solution

  1. Step 1: Identify the error cause

    object_center is None, so accessing object_center[0] causes TypeError.
  2. Step 2: Fix the error

    Assign a tuple like (x, y) to object_center before using it in condition.
  3. Final Answer:

    TypeError because object_center is None; fix by assigning a tuple to object_center -> Option B
  4. Quick Check:

    None used as index causes TypeError [OK]
Hint: Check variable types before indexing [OK]
Common Mistakes:
  • Ignoring NoneType indexing error
  • Changing dictionary keys incorrectly
  • Assuming code runs without error
5. You want the drone to follow a yellow object but only if its detected center's y-coordinate is above 100. Which code snippet correctly implements this condition using color-based tracking?
yellow_filter = {'lower': (20, 100, 100), 'upper': (30, 255, 255)}
object_center = (120, 150)

# Choose the correct condition to check
hard
A. if yellow_filter['lower'][0] <= object_center[0] <= yellow_filter['upper'][0] and object_center[1] > 100: print('Following yellow object')
B. if yellow_filter['lower'][1] <= object_center[1] <= yellow_filter['upper'][1] and object_center[0] > 100: print('Following yellow object')
C. if yellow_filter['lower'][0] <= object_center[1] <= yellow_filter['upper'][0] and object_center[0] > 100: print('Following yellow object')
D. if yellow_filter['lower'][1] <= object_center[0] <= yellow_filter['upper'][1] and object_center[1] > 100: print('Following yellow object')

Solution

  1. Step 1: Understand HSV and coordinate roles

    yellow_filter keys 'lower' and 'upper' define hue range at index 0; object_center[0] is x, object_center[1] is y.
  2. Step 2: Check condition for hue and y-coordinate

    Hue check uses object_center[0] between lower and upper hue; y-coordinate must be > 100.
  3. Final Answer:

    if yellow_filter['lower'][0] <= object_center[0] <= yellow_filter['upper'][0] and object_center[1] > 100: print('Following yellow object') -> Option A
  4. Quick Check:

    Hue range on x and y > 100 condition = if yellow_filter['lower'][0] <= object_center[0] <= yellow_filter['upper'][0] and object_center[1] > 100: print('Following yellow object') [OK]
Hint: Match hue with x, check y > 100 separately [OK]
Common Mistakes:
  • Mixing x and y coordinates in conditions
  • Using wrong indices for hue or saturation
  • Checking y-coordinate against hue range
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