Draw bounding boxes on live feed

[Jerome]

Working on a robot, using a esp32cam live feed, it's supposed to draw bounding boxes for detected objects with the label name "cup", can't get the boxes to display in imshow. Please help.

Main Loop:

Captures a live video feed from the ESP32-CAM, decodes the JPEG image, and performs YOLOv8 object detection. Applies image processing techniques such as Gaussian blur, edge detection (Canny), and contour finding to detect obstacles. Sorts the obstacles by distance and sends steering commands to avoid them. Detects and processes objects labeled as "cup" by YOLOv8, drawing bounding boxes and calculating the average centroid of detected. Sends steering commands based on the average centroid of all detected. Displays the processed frames with bounding boxes, labels, and obstacle detection information.

import cv2
import numpy as np
import requests
from ultralytics import YOLO

# Set up the YOLOv8 model
model = YOLO("yolov8x.pt")
model.conf = 0.5

# Get the IP address and port of the ESP32-CAM
ip_address = ""  
port = 80  

# Function to get the live feed from the ESP32-CAM
def get_frame():
    response = requests.get(f"http://{ip_address}:{port}/cam-lo.jpg")
    return response.content

def calculate_distance(x, y, w, h):
    center_x = x + w / 2
    center_y = y + h / 2
    distance = np.sqrt(center_x**2 + center_y**2)
    return distance

# Function to send the "left" or "right" command based on the centroid of the detected trash
def send_steering_command(avg_centroid):
    if avg_centroid[0] < WIDTH / 2:
        requests.get(f'http://{ip_address}:{port}/control?command=left')
        print("TURN LEFT")
    elif avg_centroid[0] > WIDTH / 2:
        requests.get(f'http://{ip_address}:{port}/control?command=right')
        print("TURN RIGHT")
    else:
        requests.get(f'http://{ip_address}:{port}/control?command=forward')
        print("MOVE FORWARD")

# Main function to process the live feed and detect trash
def main():
    global WIDTH
    WIDTH, HEIGHT = 320, 240  # Set the width and height of the frame

    while True:
        # Get the live feed from the ESP32-CAM
        frame_data = get_frame()

        # Decode the JPEG image from the live feed
        frame = cv2.imdecode(np.frombuffer(frame_data, np.uint8), cv2.IMREAD_COLOR)

        # Perform object detection using YOLOv8
        results = model(frame)

        # Convert the frame to grayscale
        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

        # Apply Gaussian blur to the grayscale image  ****************************************
        blurred = cv2.GaussianBlur(gray, (5, 5), 0)

        # Apply edge detection to the blurred image
        edges = cv2.Canny(blurred, 50, 150)

        # Apply thresholding to the edges image
        _ , thresh = cv2.threshold(edges, 127, 255, cv2.THRESH_BINARY)

        # Find contours in the thresholded image
        contours, _ = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

        # Calculate the distance to the obstacles based on the size and position of the contours
    
        obstacles = []
        for contour in contours:
            x, y, w, h = cv2.boundingRect(contour)
            if w > 50 and h > 50:  # Filter out small contours
                distance = calculate_distance(x, y, w, h)
                obstacles.append((distance, x, y, w, h))

        # Sort the obstacles by distance
        obstacles.sort(key=lambda x: x[0])       

        for obstacle in obstacles:
            if obstacle[0] < 100:  # Adjust this threshold based on your robot's capabilities
                if obstacle[1] < WIDTH / 2:
                    requests.get(f'http://{ip_address}:{port}/control?command=left')  # Turn left
                elif obstacle[1] > WIDTH / 2:
                    requests.get(f'http://{ip_address}:{port}/control?command=right')  # Turn right
                else:
                    requests.get(f'http://{ip_address}:{port}/control?command=forward')

        # Draw bounding boxes and labels for detected objects
            
            center_points_cur_frame = []
         
            for result in results.xyxy[0]:
                x, y, w, h = cv2.boundingRect()  # Extracting box coordinates
                cx = int((x + w) / 2)
                cy = int((y + h) / 2)
                center_points_cur_frame.append((cx, cy))
                label = model.names[int(result[5])]

            if label == "cup":
                cv2.rectangle(frame, (int(x), int(y)), (int(w), int(h)), (0, 255, 0), 2)
                cv2.putText(frame, label, (int(x), int(y) - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)


                # Calculate the average centroid of all detected 
            if center_points_cur_frame:
                   avg_centroid = (sum(x for x, y in center_points_cur_frame) / len(center_points_cur_frame), sum(y for x, y in center_points_cur_frame) / len(center_points_cur_frame))
            else:
                   avg_centroid = (0, 0)  # or some other default value

                # Send the steering command based on the average centroid
                   send_steering_command(avg_centroid)

        # Display the resulting frame
        cv2.imshow("Obstacle Detection", edges)

        # Display the resulting frame
        cv2.imshow("ESP32CAM Cup Detection", frame)

        # Exit the loop if 'q' is pressed
        if cv2.waitKey(1) & 0xFF == ord("q"):
            break

    cv2.destroyAllWindows()

if __name__ == "__main__":
    main()

Error:
Traceback (most recent call last):
  File "c:\Users\floloja\Desktop\robotver2\test.py", line 126, in <module>
    main()
  File "c:\Users\floloja\Desktop\robotver2\test.py", line 92, in main
    for result in results.xyxy[0]:
                  ^^^^^^^^^^^^
AttributeError: 'list' object has no attribute 'xyxy'