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plane_tracker_wkalman.py
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plane_tracker_wkalman.py
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# Author: Bharath Kumar
# Contact: kumar7bharath@gmail.com
# Reference: opencv.org
import cv2
import numpy as np
from collections import namedtuple
import glob
from kalman_filter import IP_KF
FLANN_INDEX_KDTREE = 1
FLANN_INDEX_LSH = 6
flann_params= dict(algorithm = FLANN_INDEX_LSH,
table_number = 6,
key_size = 12,
multi_probe_level = 1)
MIN_MATCH_COUNT = 10
PlanarTarget = namedtuple('PlaneTarget', 'image, rect, keypoints, descrs, data')
TrackedTarget = namedtuple('TrackedTarget', 'target, p0, p1, H, quad')
class planeTracker:
def __init__(self):
self.detector = cv2.ORB_create(nfeatures=1000)
self.matcher = cv2.FlannBasedMatcher(flann_params, {})
self.targets = []
self.frame_key_points = []
self.kalman_p1 = IP_KF(0, 0)
self.kalman_p2 = IP_KF(0, 0)
self.kalman_p3 = IP_KF(0, 0)
self.kalman_p4 = IP_KF(0, 0)
def track(self, frame):
self. frame_key_points, frame_descriptors = self.detect_features(frame)
if len(self.frame_key_points) < MIN_MATCH_COUNT:
return []
matches = self.matcher.knnMatch(frame_descriptors, k=2)
matches = [m[0] for m in matches if len(m)==2 and m[0].distance < m[1].distance*0.75]
if len(matches) < MIN_MATCH_COUNT:
return []
# For multiple reference images
matches_by_id = [[] for _ in range(len(self.targets))]
for m in matches:
matches_by_id[m.imgIdx].append(m)
tracked = []
for imgIdx, matches in enumerate(matches_by_id):
if len(matches) < MIN_MATCH_COUNT:
continue
target = self.targets[imgIdx]
p0 = [target.keypoints[m.trainIdx].pt for m in matches]
p1 = [self.frame_key_points[m.queryIdx].pt for m in matches]
p0, p1 = np.float32((p0, p1))
H, mask = cv2.findHomography(p0, p1, cv2.RANSAC, 3.0)
mask = mask.ravel() != 0
if mask.sum() < MIN_MATCH_COUNT:
continue
p0, p1 = p0[mask], p1[mask]
x0, y0, x1, y1 = target.rect
quad = np.float32([[x0, y0], [x1, y0], [x1, y1], [x0, y1]])
quad = cv2.perspectiveTransform(quad.reshape(1, -1, 2), H).reshape(-1, 2)
x1, y1 = quad[0][0], quad[0][1]
x2, y2 = quad[1][0], quad[1][1]
x3, y3 = quad[2][0], quad[2][1]
x4, y4 = quad[3][0], quad[3][1]
x1, _, y1, _ = self.kalman_p1.update(x1, y1)
x2, _, y2, _ = self.kalman_p2.update(x2, y2)
x3, _, y3, _ = self.kalman_p3.update(x3, y3)
x4, _, y4, _ = self.kalman_p4.update(x4, y4)
quad = np.array([[x1, y1],
[x2, y2],
[x3, y3],
[x4, y4]])
track = TrackedTarget(target=target, p0=p0, p1=p1, H=H, quad=quad)
tracked.append(track)
tracked.sort(key = lambda t: len(t.p0), reverse=True)
return tracked
def add_target(self, image, rect):
x0, y0, x1, y1 = rect
_key_points, _descriptors = self.detect_features(image)
key_points = []
descriptors = []
for kp, des in zip(_key_points, _descriptors):
x, y = kp.pt
if x0 <= x <= x1 and y0 <= y <= y1:
key_points.append(kp)
descriptors.append(des)
descriptors = np.uint8(descriptors)
self.matcher.add([descriptors])
target = PlanarTarget(image=image, rect=rect, keypoints=key_points, descrs=descriptors, data=None)
self.targets.append(target)
def detect_features(self, frame):
key_points, descriptors = self.detector.detectAndCompute(frame, None)
if descriptors is None:
descriptors = []
return key_points, descriptors
class VideoPlayer:
def __init__(self):
self.cap = cv2.VideoCapture(-1)
self.frame = None
self.tracker = planeTracker()
cv2.namedWindow("PlaneTracker")
train_images = glob.glob("./data/train_images/test/*")
train_images = sorted(train_images)
print(train_images)
with open("./data/train_images/rect.txt") as file:
lines = file.readlines()
lines = [line.split(',') for line in lines]
for index, train_image in enumerate(train_images):
line = [int(point) for point in lines[index]]
print(line)
train_image.split('/')[-1].split('.')[0]
frame = cv2.imread(train_image)
x, y, _ = frame.shape
self.tracker.add_target(frame, (line[0], line[1], line[2], line[3]))
# self.tracker.add_target(frame, (0, 0, y, x))
def play(self):
while True:
ret, frame = self.cap.read()
self.frame = frame.copy()
frame = self.frame.copy()
tracked = self.tracker.track(self.frame)
for tr in tracked:
cv2.polylines(frame, [np.int32(tr.quad)], True, (255, 255, 255), 2)
for (x, y) in np.int32(tr.p1):
cv2.circle(frame, (x, y), 2, (255, 255, 255))
# self.rect.draw(frame)
cv2.imshow("PlaneTracker", frame)
ret = cv2.waitKey(1)
if ret == ord('q'):
break
if __name__ == "__main__":
player = VideoPlayer()
player.play()