Merge pull request #20036 from APrigarina:tracking_api

Tracking API: added DaSiamRPN tracker

* added dasiamrpn tracker

* dasiamrpn: add test, rewrite sample

* change python samples

* fix tests

* fix params

samples/python/tracker.py

@@ -3,8 +3,22 @@
 '''
 Tracker demo
 
+For usage download models by following links
+For GOTURN:
+    goturn.prototxt and goturn.caffemodel: https://github.com/opencv/opencv_extra/tree/c4219d5eb3105ed8e634278fad312a1a8d2c182d/testdata/tracking
+For DaSiamRPN:
+    network:     https://www.dropbox.com/s/rr1lk9355vzolqv/dasiamrpn_model.onnx?dl=0
+    kernel_r1:   https://www.dropbox.com/s/999cqx5zrfi7w4p/dasiamrpn_kernel_r1.onnx?dl=0
+    kernel_cls1: https://www.dropbox.com/s/qvmtszx5h339a0w/dasiamrpn_kernel_cls1.onnx?dl=0
+
 USAGE:
-    tracker.py [<video_source>]
+    tracker.py [-h] [--input INPUT] [--tracker_algo TRACKER_ALGO]
+                    [--goturn GOTURN] [--goturn_model GOTURN_MODEL]
+                    [--dasiamrpn_net DASIAMRPN_NET]
+                    [--dasiamrpn_kernel_r1 DASIAMRPN_KERNEL_R1]
+                    [--dasiamrpn_kernel_cls1 DASIAMRPN_KERNEL_CLS1]
+                    [--dasiamrpn_backend DASIAMRPN_BACKEND]
+                    [--dasiamrpn_target DASIAMRPN_TARGET]
 '''
 
 # Python 2/3 compatibility
@@ -14,18 +28,37 @@ import sys
 
 import numpy as np
 import cv2 as cv
+import argparse
 
 from video import create_capture, presets
 
 class App(object):
 
-    def initializeTracker(self, image):
+    def __init__(self, args):
+        self.args = args
+
+    def initializeTracker(self, image, trackerAlgorithm):
         while True:
+            if trackerAlgorithm == 'mil':
+                tracker = cv.TrackerMIL_create()
+            elif trackerAlgorithm == 'goturn':
+                params = cv.TrackerGOTURN_Params()
+                params.modelTxt = self.args.goturn
+                params.modelBin = self.args.goturn_model
+                tracker = cv.TrackerGOTURN_create(params)
+            elif trackerAlgorithm == 'dasiamrpn':
+                params = cv.TrackerDaSiamRPN_Params()
+                params.model = self.args.dasiamrpn_net
+                params.kernel_cls1 = self.args.dasiamrpn_kernel_cls1
+                params.kernel_r1 = self.args.dasiamrpn_kernel_r1
+                tracker = cv.TrackerDaSiamRPN_create(params)
+            else:
+                sys.exit("Tracker {} is not recognized. Please use one of three available: mil, goturn, dasiamrpn.".format(trackerAlgorithm))
+
             print('==> Select object ROI for tracker ...')
             bbox = cv.selectROI('tracking', image)
             print('ROI: {}'.format(bbox))
 
-            tracker = cv.TrackerMIL_create()
             try:
                 tracker.init(image, bbox)
             except Exception as e:
@@ -37,7 +70,8 @@ class App(object):
             return tracker
 
     def run(self):
-        videoPath = sys.argv[1] if len(sys.argv) >= 2 else 'vtest.avi'
+        videoPath = self.args.input
+        trackerAlgorithm = self.args.tracker_algo
         camera = create_capture(videoPath, presets['cube'])
         if not camera.isOpened():
             sys.exit("Can't open video stream: {}".format(videoPath))
@@ -48,7 +82,7 @@ class App(object):
         assert image is not None
 
         cv.namedWindow('tracking')
-        tracker = self.initializeTracker(image)
+        tracker = self.initializeTracker(image, trackerAlgorithm)
 
         print("==> Tracking is started. Press 'SPACE' to re-initialize tracker or 'ESC' for exit...")
 
@@ -76,5 +110,24 @@ class App(object):
 
 if __name__ == '__main__':
     print(__doc__)
-    App().run()
+    parser = argparse.ArgumentParser(description="Run tracker")
+    parser.add_argument("--input", type=str, default="vtest.avi", help="Path to video source")
+    parser.add_argument("--tracker_algo", type=str, default="mil", help="One of three available tracking algorithms: mil, goturn, dasiamrpn")
+    parser.add_argument("--goturn", type=str, default="goturn.prototxt", help="Path to GOTURN architecture")
+    parser.add_argument("--goturn_model", type=str, default="goturn.caffemodel", help="Path to GOTERN model")
+    parser.add_argument("--dasiamrpn_net", type=str, default="dasiamrpn_model.onnx", help="Path to onnx model of DaSiamRPN net")
+    parser.add_argument("--dasiamrpn_kernel_r1", type=str, default="dasiamrpn_kernel_r1.onnx", help="Path to onnx model of DaSiamRPN kernel_r1")
+    parser.add_argument("--dasiamrpn_kernel_cls1", type=str, default="dasiamrpn_kernel_cls1.onnx", help="Path to onnx model of DaSiamRPN kernel_cls1")
+    parser.add_argument("--dasiamrpn_backend", type=int, default=0, help="Choose one of computation backends:\
+                                                                           0: automatically (by default),\
+                                                                           1: Halide language (http://halide-lang.org/),\
+                                                                           2: Intel's Deep Learning Inference Engine (https://software.intel.com/openvino-toolkit),\
+                                                                           3: OpenCV implementation")
+    parser.add_argument("--dasiamrpn_target", type=int, default=0, help="Choose one of target computation devices:\
+                                                                         0: CPU target (by default),\
+                                                                         1: OpenCL,\
+                                                                         2: OpenCL fp16 (half-float precision),\
+                                                                         3: VPU")
+    args = parser.parse_args()
+    App(args).run()
     cv.destroyAllWindows()