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multi_tracking_self_select.py

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+import argparse
+import cv2
+import numpy as np
+import cv2.legacy
+
+ap = argparse.ArgumentParser()
+ap.add_argument("-v", "--video", type=str,
+	help="path to input video file")
+ap.add_argument("-t", "--tracker", type=str, default="kcf",
+	help="OpenCV object tracker type")
+args = vars(ap.parse_args())
+
+OPENCV_OBJECT_TRACKERS = {
+	"csrt": cv2.legacy.TrackerCSRT_create,
+	"kcf": cv2.TrackerKCF_create,
+	"boosting": cv2.legacy.TrackerBoosting_create,
+	"mil": cv2.TrackerMIL_create,
+	"tld": cv2.legacy.TrackerTLD_create,
+	"medianflow": cv2.legacy.TrackerMedianFlow_create,
+	"mosse": cv2.legacy.TrackerMOSSE_create
+}
+
+# 实例化OpenCV's multi-object tracker
+trackers = cv2.legacy.MultiTracker_create()
+vs = cv2.VideoCapture(args["video"])
+
+while True:
+	frame = vs.read()
+	frame = frame[1]
+	if frame is None:
+		break
+
+	# resize每一帧
+	(h, w) = frame.shape[:2]
+	width=600
+	r = width / float(w)
+	dim = (width, int(h * r))
+	frame = cv2.resize(frame, dim, interpolation=cv2.INTER_AREA)
+
+	# 追踪结果
+	(success, boxes) = trackers.update(frame)
+
+	# 绘制区域
+	for box in boxes:
+		(x, y, w, h) = [int(v) for v in box]
+		cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
+
+	# 显示
+	cv2.imshow("Frame", frame)
+	key = cv2.waitKey(100) & 0xFF
+
+	if key == ord("s"):
+		# 选择一个区域，按s
+		box = cv2.selectROI("Frame", frame, fromCenter=False,
+			showCrosshair=True)
+
+		# 创建一个新的追踪器
+		tracker = OPENCV_OBJECT_TRACKERS[args["tracker"]]()
+		trackers.add(tracker, frame, box)
+
+	# 退出
+	elif key == 27:
+		break
+vs.release()
+cv2.destroyAllWindows()