mirror of
https://github.com/OSURoboticsClub/Rover_2017_2018.git
synced 2025-11-08 10:11:14 +00:00
sample code stuff for goal tracking, ball_tracking.py uses a webcam and detects green. Currently testing hardware vs software issues on my surface since distance is a huge issue for testing currently
This commit is contained in:
MatthewTaylor24
12
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104
software/rover/gate_navigation/ball_tracking.py
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104
software/rover/gate_navigation/ball_tracking.py
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||||
# USAGE
|
||||
# python ball_tracking.py --video ball_tracking_example.mp4
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||||
# python ball_tracking.py
|
||||
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||||
# import the necessary packages
|
||||
from collections import deque
|
||||
import numpy as np
|
||||
import argparse
|
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import imutils
|
||||
import cv2
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# construct the argument parse and parse the arguments
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ap = argparse.ArgumentParser()
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ap.add_argument("-v", "--video", help="path to the (optional) video file")
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ap.add_argument("-b", "--buffer", type=int, default=64, help="max buffer size")
|
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args = vars(ap.parse_args())
|
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||||
# define the lower and upper boundaries of the "green"
|
||||
# ball in the HSV color space, then initialize the
|
||||
# list of tracked points
|
||||
greenLower = (50, 112, 50)
|
||||
greenUpper = (144, 255, 145)
|
||||
pts = deque(maxlen=args["buffer"])
|
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||||
# if a video path was not supplied, grab the reference
|
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# to the webcam
|
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if not args.get("video", False):
|
||||
camera = cv2.VideoCapture(1)
|
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|
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# otherwise, grab a reference to the video file
|
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else:
|
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camera = cv2.VideoCapture(args["video"])
|
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|
||||
# keep looping
|
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while True:
|
||||
# grab the current frame
|
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(grabbed, frame) = camera.read()
|
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|
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# if we are viewing a video and we did not grab a frame,
|
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# then we have reached the end of the video
|
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if args.get("video") and not grabbed:
|
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break
|
||||
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# resize the frame, blur it, and convert it to the HSV
|
||||
# color space
|
||||
frame = imutils.resize(frame, width=1000)
|
||||
# blurred = cv2.GaussianBlur(frame, (11, 11), 0)
|
||||
hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)
|
||||
|
||||
# construct a mask for the color "green", then perform
|
||||
# a series of dilations and erosions to remove any small
|
||||
# blobs left in the mask
|
||||
mask = cv2.inRange(hsv, greenLower, greenUpper)
|
||||
mask = cv2.erode(mask, None, iterations=2)
|
||||
mask = cv2.dilate(mask, None, iterations=2)
|
||||
|
||||
# find contours in the mask and initialize the current
|
||||
# (x, y) center of the ball
|
||||
cnts = cv2.findContours(mask.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)[-2]
|
||||
center = None
|
||||
|
||||
# only proceed if at least one contour was found
|
||||
if len(cnts) > 0:
|
||||
# find the largest contour in the mask, then use
|
||||
# it to compute the minimum enclosing circle and
|
||||
# centroid
|
||||
c = max(cnts, key=cv2.contourArea)
|
||||
((x, y), radius) = cv2.minEnclosingCircle(c)
|
||||
M = cv2.moments(c)
|
||||
center = (int(M["m10"] / M["m00"]), int(M["m01"] / M["m00"]))
|
||||
|
||||
# only proceed if the radius meets a minimum size
|
||||
if radius > 1:
|
||||
# draw the circle and centroid on the frame,
|
||||
# then update the list of tracked points
|
||||
cv2.circle(frame, (int(x), int(y)), int(radius), (0, 255, 255), 2)
|
||||
cv2.circle(frame, center, 5, (0, 0, 255), -1)
|
||||
|
||||
# update the points queue
|
||||
pts.appendleft(center)
|
||||
|
||||
# loop over the set of tracked points
|
||||
for i in xrange(1, len(pts)):
|
||||
# if either of the tracked points are None, ignore
|
||||
# them
|
||||
if pts[i - 1] is None or pts[i] is None:
|
||||
continue
|
||||
|
||||
# otherwise, compute the thickness of the line and
|
||||
# draw the connecting lines
|
||||
thickness = int(np.sqrt(args["buffer"] / float(i + 1)) * 2.5)
|
||||
cv2.line(frame, pts[i - 1], pts[i], (0, 0, 255), thickness)
|
||||
|
||||
# show the frame to our screen
|
||||
cv2.imshow("Frame", frame)
|
||||
key = cv2.waitKey(1) & 0xFF
|
||||
|
||||
# if the 'q' key is pressed, stop the loop
|
||||
if key == ord("q"):
|
||||
break
|
||||
|
||||
# cleanup the camera and close any open windows
|
||||
camera.release()
|
||||
cv2.destroyAllWindows()
|
||||
BIN
software/rover/gate_navigation/ball_tracking_example.mp4
Normal file
BIN
software/rover/gate_navigation/ball_tracking_example.mp4
Normal file
Binary file not shown.
42
software/rover/gate_navigation/gate_navi.py
Normal file
42
software/rover/gate_navigation/gate_navi.py
Normal file
@@ -0,0 +1,42 @@
|
||||
import cv2
|
||||
import numpy as np
|
||||
import sys
|
||||
|
||||
def main():
|
||||
# Webcam number 0 is used to capture the frames
|
||||
# camera = cv2.VideoCapture(0)
|
||||
|
||||
# construct the argument parse and parse the arguments
|
||||
# ap = argparse.ArgumentParser()
|
||||
# ap.add_argument("-i", "--image", help="path to the image")
|
||||
# args = vars(ap.parse_args())
|
||||
|
||||
# load the image
|
||||
image = cv2.imread("pokemon_games.png")
|
||||
|
||||
# define the list of boundaries
|
||||
boundaries = [
|
||||
([17, 15, 100], [50, 56, 200]),
|
||||
([86, 31, 4], [220, 88, 50]),
|
||||
([25, 146, 190], [62, 174, 250]),
|
||||
([103, 86, 65], [165, 163, 168])
|
||||
]
|
||||
|
||||
# loop over the boundaries
|
||||
for (lower, upper) in boundaries:
|
||||
# create NumPy arrays from the boundaries
|
||||
lower = np.array(lower, dtype="uint8")
|
||||
upper = np.array(upper, dtype="uint8")
|
||||
|
||||
# find the colors within the specified boundaries and apply
|
||||
# the mask
|
||||
mask = cv2.inRange(image, lower, upper)
|
||||
output = cv2.bitwise_and(image, image, mask=mask)
|
||||
|
||||
# show the images
|
||||
cv2.imshow("images", np.hstack([image, output]))
|
||||
cv2.waitKey(0)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
BIN
software/rover/gate_navigation/pokemon_games.png
Normal file
BIN
software/rover/gate_navigation/pokemon_games.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 601 KiB |
Reference in New Issue
Block a user