Delete redball_chase_update.py

redball_chase_update.py

@@ -1,93 +0,0 @@
-#!/usr/bin/env python3
-
-import rospy
-import cv2
-import numpy as np
-from sensor_msgs.msg import Image
-from geometry_msgs.msg import Twist
-from cv_bridge import CvBridge, CvBridgeError
-
-def is_circular(contour, radius):
-    """Check if the contour is circular enough to be considered a ball."""
-    area = cv2.contourArea(contour)
-    if area <= 0:
-        return False
-    circularity = 4 * np.pi * area / (2 * np.pi * radius) ** 2
-    # Circular enough if circularity is close to 1; adjust threshold as needed
-    return 0.7 <= circularity <= 1.3
-
-def find_red_ball(image):
-    # Convert the image to HSV color space
-    hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
-
-    # Red color range in HSV; might need fine-tuning
-    lower_red1 = np.array([0, 120, 70])
-    upper_red1 = np.array([10, 255, 255])
-    lower_red2 = np.array([170, 120, 70])
-    upper_red2 = np.array([180, 255, 255])
-
-    mask1 = cv2.inRange(hsv, lower_red1, upper_red1)
-    mask2 = cv2.inRange(hsv, lower_red2, upper_red2)
-    mask = mask1 + mask2
-
-    # Find contours in the mask
-    contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
-
-    ball_found = False
-    center, radius = None, None
-    for contour in contours:
-        (x, y), radius = cv2.minEnclosingCircle(contour)
-        if radius > 5 and is_circular(contour, radius):  # Checks size and circularity
-            center = (int(x), int(y))
-            cv2.circle(image, center, int(radius), (0, 255, 0), 2)
-            cv2.putText(image, 'Red Ball', (center[0] - 20, center[1] - int(radius) - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 255, 255), 2)
-            ball_found = True
-            break
-
-    return image, (center, radius) if ball_found else (None, None)
-
-def image_callback(msg):
-    try:
-        cv_image = bridge.imgmsg_to_cv2(msg, "bgr8")
-    except CvBridgeError as e:
-        rospy.logerr(e)
-
-    processed_image, ball_info = find_red_ball(cv_image)
-
-    twist_msg = Twist()
-    if ball_info and ball_info[0] is not None:  # Check if ball_info is not None and has valid center
-        center, radius = ball_info
-        x, y = center
-        err = x - cv_image.shape[1] / 2
-        if abs(err) > 100:  # Need to rotate TurtleBot to align with the ball
-            twist_msg.angular.z = -0.005 * err
-        else:  # Move forward towards the ball
-            twist_msg.linear.x = -min(0.05 * radius, 0.1)  # Adjust to control speed
-    else:  # Rotate TurtleBot if the ball is not found
-        twist_msg.angular.z = 0.5
-
-    cmd_vel_pub.publish(twist_msg)
-    cv2.imshow("Red Ball Detection", processed_image)
-    cv2.waitKey(3)
-
-def shutdown():
-    rospy.loginfo("Shutting down")
-    cmd_vel_pub.publish(Twist())  # Stop the robot
-    cv2.destroyAllWindows()
-
-if __name__ == '__main__':
-    rospy.init_node('redball_chase', anonymous=False)
-    bridge = CvBridge()
-    cmd_vel_pub = rospy.Publisher('/cmd_vel', Twist, queue_size=1)
-    rospy.Subscriber("/camera/image", Image, image_callback)
-
-    rospy.on_shutdown(shutdown)
-
-    # Setup window for display (optional, remove if running headless)
-    cv2.namedWindow("Red Ball Detection", cv2.WINDOW_NORMAL)
-
-    try:
-        rospy.spin()
-    except KeyboardInterrupt:
-        rospy.loginfo("Red ball follower node terminated.")
-