So I’m a beginner in robotics and programming. I’m making a project using ESP32 and OpenCv to make a car that follows a certain color. When I was coding the opencv part of the project, I noticed that I would need to use threading to simultaneously process and send commands. So i came up with my own code with a little help from ChatGPT for the locks and Queues which i didnt know about before chatGPT inserted them.

import cv2
import numpy as np
from PIL import Image
import requests, threading
from queue import Queue

#height = 480, width 640

import cv2
import numpy as np
from PIL import Image
import requests, threading
from queue import Queue

#height = 480, width 640
prev_direction = 'None'
lock = threading.Lock()
direction_queue = Queue()

def run_motor():

global prev_direction
while True:
    val = direction_queue.get()

    if val == -1:
        direction = 'right'
    elif val == 1:
        direction = 'left'
    elif val == 0:
        direction = 'stop'
    else:
        continue

    with lock:
        if direction == prev_direction:
            direction_queue.task_done()
            continue

        prev_direction = direction

    url = 'http://192.168.0.110/'
    print (direction)
    '''try:
        print(url+direction)
        response = requests.get(url + direction)
        response.raise_for_status()  # Raises HTTPError if the status code is 4xx or 5xx
        print('Response received successfully')

    except requests.exceptions.HTTPError as errh:
        print(f'HTTP Error: {errh}')
    except requests.exceptions.ConnectionError as errc:
        print(f'Error Connecting: {errc}')
    except requests.exceptions.Timeout as errt:
        print(f'Timeout Error: {errt}')
    except requests.exceptions.RequestException as err:
        print(f'An error occurred: {err}')'''
    
    direction_queue.task_done()

 motor_thread = threading.Thread(target=run_motor, daemon=True)
 motor_thread.start()

 #'http://192.168.0.113:81/stream'
 cap = cv2.VideoCapture('http://192.168.0.113:81/stream')
if not cap.isOpened():
    print("Error: Could not open video stream.")
    exit()
upper_limit = np.array([85,255,255])
lower_limit = np.array([35, 100, 100])

while True:

ret, frame = cap.read()

if not ret:
    print("Error: Could not read frame.")
    break
if frame is None or frame.size == 0:
    print("Error: Empty frame received.")
    continue
#height, width, channel = frame.shape
#print(f"height{height}, width {width}")
hsv_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
mask = cv2.inRange(hsv_frame, lower_limit, upper_limit) 
mask_ = Image.fromarray(mask)
bbox = mask_.getbbox()

if bbox is not None:
    x1, y1, x2, y2 = bbox
    frame = cv2.rectangle (frame, (x1,y1), (x2,y2), (0,255,0), 4)
    cx = (x1+x2)//2
    cy = (y1+y2)//2
    if cx < 140:
        val = -1
    elif cx > 180:
        val = 1
    else:
        val = 0
    if val is not None:
        direction_queue.put(val)
    

cv2.imshow('frame', frame)
if cv2.waitKey(1) == ord('q'):
    break

cap.release()
cv2.destroyAllWindows() '''

after that it was working ok but i was curious on how i can optimize it. So i asked chatGPT (a bad idea…) and it spit out this code

'''direction_queue = Queue()
frame_queue = Queue()
stop_flag = threading.Event()

def run_motor():

prev_direction = 'None'
while not stop_flag.is_set():

    val = direction_queue.get()
    if val == -1:
        direction = 'right'
    elif val == 1:
        direction = 'left'
    elif val == 0:
        direction = 'stop'
    else:
        continue

    
    if direction != prev_direction:
        prev_direction = direction


        url = 'http://192.168.0.110/'
        print (direction)
        try:
            print(url+direction)
            response = requests.get(url + direction)
            response.raise_for_status()  # Raises HTTPError if the status code is 4xx or 5xx
            print('Response received successfully')

        except requests.exceptions.HTTPError as errh:
            print(f'HTTP Error: {errh}')
        except requests.exceptions.ConnectionError as errc:
            print(f'Error Connecting: {errc}')
        except requests.exceptions.Timeout as errt:
            print(f'Timeout Error: {errt}')
        except requests.exceptions.RequestException as err:
            print(f'An error occurred: {err}')
    

def capture_frame():
#'http://192.168.0.113:81/stream'
cap = cv2.VideoCapture('http://192.168.0.113:81/stream')
if not cap.isOpened():
    print("Error: Could not open video stream.")
    return
cap.set(cv2.CAP_PROP_BUFFERSIZE, 1)
while not stop_flag.is_set():

    ret, frame = cap.read()
    
    if not ret:
        print("Error: Could not read frame.")
        break
    if frame is not None and frame.size > 0:
        frame_queue.put(frame)
cap.release()

def process_frame():
x =0
y = 0
upper_limit = np.array([85,255,255])
lower_limit = np.array([35, 100, 100])
while not stop_flag.is_set():
    frame = frame_queue.get()
    if frame is None:
        continue
    hsv_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
    mask = cv2.inRange(hsv_frame, lower_limit, upper_limit) 
    mask_ = Image.fromarray(mask)
    bbox = mask_.getbbox()

    if bbox is not None:
        x1, y1, x2, y2 = bbox
        frame = cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 255, 0), 4)
        cx = (x1 + x2) // 2
        if cx < 300:
            val = -1
        elif cx > 340:
            val = 1
        else:
            val = 0
        direction_queue.put(val)
    cv2.imshow('frame', frame)
    if cv2.waitKey(1) == ord('q'):
        stop_flag.set()
cv2.destroyAllWindows()
    
capture_thread = threading.Thread(target = capture_frame, daemon = True)
process_thread = threading.Thread(target = process_frame, daemon = True)
motor_thread = threading.Thread(target = run_motor, daemon = True)

capture_thread.start()
process_thread.start()
motor_thread.start()

capture_thread.join()
process_thread.join()
motor_thread.join()'''

Turns out this code is so slow and doesnt even close the program properly. I’m just curious on why this code turned out to be slow.