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siamdw_360_default.py
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#################################################################################################
# Visual object tracking in panoramic video
# Master thesis at Brno University of Technology - Faculty of Information Technology
# Author: Vít Ambrož ([email protected])
# Supervisor: Doc. Ing. Martin Čadík, Ph.D.
# Module: siamdw_360_default.py
# Description: Default tracking using SiamDW tracker
#################################################################################################
# ------------------------------------------------------------------------------
# Copyright (c) Microsoft
# Licensed under the MIT License.
# Email: [email protected]
# https://github.com/researchmm/TracKit
# ------------------------------------------------------------------------------
import _init_paths
import os
import sys
import cv2
import torch
import numpy as np
# try:
# from torch2trt import TRTModule
# except:
# print('Warning: TensorRT is not successfully imported')
import models.models as models
from os.path import exists, join, dirname, realpath
from tracker.siamfc import SiamFC
from easydict import EasyDict as edict
from utils.utils import load_pretrain, cxy_wh_2_rect
# custom modules to improve equirectangular tracking
from boundingbox import BoundingBox
from parser import Parser
class SiamDW360Default:
"""Default tracking using SiamDW tracker"""
def __init__(self, resume: str, video_path: str, groundtruth_path: str = None, save_result_path: str = None):
# SiamDW architecture attributes
self.resume = resume
self.arch = "SiamDW"
# other attributes
self.video_path = video_path
self.groundtruth_path = groundtruth_path
if save_result_path:
self.save_result_path = save_result_path
else:
self.save_result_path = "tmp-result-SiamDW.txt"
self.video = None
self.video_width = None
self.video_height = None
self.frame = None
self.bbox = None
self.gt_bounding_boxes = []
self.result_bounding_boxes = []
# enable parsing/creating methods
self.parser = Parser()
# constants for sizes and positions of opencv circles, rectangles and texts
self.RECTANGLE_BORDER_PX = 3
self.FONT_SCALE = 0.75
self.FONT_WEIGHT = 1
self.TEXT_ROW1_POS = (30,30)
self.TEXT_ROW2_POS = (30,60)
self.TEXT_ROW3_POS = (30,90)
self.TEXT_ROW4_POS = (30,120)
self.WINDOW_NAME = "Tracker-SiamDW"
def _drawBoundingBox(self, videoWidth, point1, point2, boundingBox, color, thickness):
"""Method for drawing rectangle according to points"""
if (boundingBox.is_on_border()):
# draw two rectangles around the region of interest
rightBorderPoint = (videoWidth - 1, point2[1])
cv2.rectangle(self.frame, point1, rightBorderPoint, color, thickness)
leftBorderPoint = (0, point1[1])
cv2.rectangle(self.frame, leftBorderPoint, point2, color, thickness)
else:
# draw a rectangle around the region of interest
cv2.rectangle(self.frame, point1, point2, color, thickness)
def _checkBoundsOfPoint(self, point):
"""Checks if given point is in interval [0,self.width] and [0,self.height] with x overflow"""
# horizontal could overflow in equirectangular
x = point[0]
y = point[1]
if x < 0:
x = self.video_width + x - 1
elif x > self.video_width - 1:
x = x - self.video_width - 1
# vertical
if y < 0:
y = 0
elif y > self.video_height - 1:
y = self.video_height - 1
point = (x,y)
return point
def _saveResults(self):
"""Method for saving result bounding boxes to .txt file"""
# creating string result data
resultData = self.parser.createAnnotations(self.result_bounding_boxes)
# saving file on drive
self.parser.saveDataToFile(self.save_result_path, resultData)
print("File '" + self.save_result_path + "' has been successfully created with total " + str(len(self.result_bounding_boxes)) + " computed frames.")
def run_siamdw_default(self):
"""Method for start SiamDW tracking without any modifications"""
# prepare tracker
info = edict()
info.arch = self.arch
info.dataset = self.video
info.epoch_test = True
info.cls_type = 'thinner'
net = models.__dict__[self.arch]()
tracker = SiamFC(info)
print('[*] ======= Track video with {} ======='.format(self.arch))
print(self.resume)
net = load_pretrain(net, self.resume)
net.eval()
net = net.cuda()
self._track_video(tracker, net)
def _track_video(self, siam_tracker, siam_net):
########## 1) Video Checking ##########
# Read video
self.video = cv2.VideoCapture(self.video_path)
# Exit if video not opened.
if not self.video.isOpened():
print("Could not open video")
print(help)
sys.exit(-1)
# Read first frame.
ok, self.frame = self.video.read()
if not ok:
print("Error - Could not read a video file")
sys.exit(-1)
# save video width/height to global variables
self.video_width = int(self.video.get(cv2.CAP_PROP_FRAME_WIDTH))
self.video_height = int(self.video.get(cv2.CAP_PROP_FRAME_HEIGHT))
########## 2) Setup opencv2 window ##########
# resize window (lets define max width is 1600px)
if self.video_width < 1600:
cv2.namedWindow(self.WINDOW_NAME)
else:
cv2.namedWindow(self.WINDOW_NAME, cv2.WINDOW_NORMAL | cv2.WINDOW_KEEPRATIO)
whRatio = self.video_width / self.video_height
if whRatio == 2:
# pure equirectangular 2:1
cv2.resizeWindow(self.WINDOW_NAME, 1600, 800)
else:
# default 16:9
cv2.resizeWindow(self.WINDOW_NAME, 1600, 900)
scaleFactor = self.video_width / 1600
self.RECTANGLE_BORDER_PX = int(self.RECTANGLE_BORDER_PX * scaleFactor)
self.FONT_SCALE = self.FONT_SCALE * scaleFactor
self.FONT_WEIGHT = int(self.FONT_WEIGHT * scaleFactor) + 1
self.TEXT_ROW1_POS = (int(self.TEXT_ROW1_POS[0] * scaleFactor), int(self.TEXT_ROW1_POS[1] * scaleFactor))
self.TEXT_ROW2_POS = (int(self.TEXT_ROW2_POS[0] * scaleFactor), int(self.TEXT_ROW2_POS[1] * scaleFactor))
self.TEXT_ROW3_POS = (int(self.TEXT_ROW3_POS[0] * scaleFactor), int(self.TEXT_ROW3_POS[1] * scaleFactor))
self.TEXT_ROW4_POS = (int(self.TEXT_ROW4_POS[0] * scaleFactor), int(self.TEXT_ROW4_POS[1] * scaleFactor))
# use copy of frame to be shown in window
frame_disp = self.frame.copy()
########## 3) Initialation of bounding box ##########
# Set up initial bounding box
self.bbox = None
self.result_bounding_boxes = []
self.gt_bounding_boxes = []
if self.groundtruth_path:
# use first bounding box from given groundtruth
self.gt_bounding_boxes = self.parser.parseGivenDataFile(self.groundtruth_path, self.video_width)
if len(self.gt_bounding_boxes) > 0:
bb1 = self.gt_bounding_boxes[0]
if bb1.is_annotated:
self.bbox = (bb1.get_point1_x(), bb1.get_point1_y(), bb1.get_width(), bb1.get_height())
self.result_bounding_boxes.append(bb1)
else:
print("Error - Invalid first frame annotation from file: '" + self.groundtruth_path + "'")
sys.exit(-1)
else:
# using opencv2 select ROI
cv2.putText(frame_disp, 'Select target ROI and press ENTER', self.TEXT_ROW1_POS, cv2.FONT_HERSHEY_SIMPLEX, self.FONT_SCALE, (0, 200, 250), self.FONT_WEIGHT)
x, y, w, h = cv2.selectROI(self.WINDOW_NAME, frame_disp, False)
self.bbox = [x, y, w, h]
# save it to result list
p1 = (int(self.bbox[0]), int(self.bbox[1]))
p2 = (int(self.bbox[0] + self.bbox[2]), int(self.bbox[1] + self.bbox[3]))
# new instance of bounding box
bb1 = BoundingBox(p1, p2, self.video_width)
bb1.is_annotated = True
self.result_bounding_boxes.append(bb1)
if not(self.bbox) or self.bbox == (0,0,0,0):
print("Error - Invalid first frame annotation")
sys.exit(-1)
########## 4) Tracking process ##########
# prints just basic guide and info
print("--------------------------------------------------------------------")
print("SiamDW default tracking process has started...")
print("Tracker : SiamDW")
print("Frame #1 : " + str(self.bbox))
print("Press 'Esc' or 'Q' key to exit")
print("--------------------------------------------------------------------")
# initialize tracker with first frame and bounding box
lx, ly, w, h = self.bbox[0], self.bbox[1], self.bbox[2], self.bbox[3]
target_pos = np.array([lx + w/2, ly + h/2])
target_sz = np.array([w, h])
state = siam_tracker.init(self.frame, target_pos, target_sz, siam_net)
# display first frame
cv2.imshow(self.WINDOW_NAME, frame_disp)
# if you want to have the FPS according to the video then uncomment this code
# fps = cap.get(cv2.CAP_PROP_FPS)
videoFPS = 30
# calculate the interval between frame
interval = int(1000/videoFPS)
while True:
# Read a new frame
ok, self.frame = self.video.read()
if not ok:
break
# Start timer
timer = cv2.getTickCount()
# update tracker
state = siam_tracker.track(state, self.frame)
location = cxy_wh_2_rect(state['target_pos'], state['target_sz'])
self.bbox = [int(location[0]), int(location[1]), int(location[2]), int(location[3])]
# Calculate Frames per second (FPS)
fps = cv2.getTickFrequency() / (cv2.getTickCount() - timer)
# draw bounding box
if self.bbox[0] and self.bbox[1] and self.bbox[2] and self.bbox[3]:
# Tracking success
p1 = (self.bbox[0], self.bbox[1])
p2 = (self.bbox[0] + self.bbox[2], self.bbox[1] + self.bbox[3])
p1 = self._checkBoundsOfPoint(p1)
p2 = self._checkBoundsOfPoint(p2)
# new instance of bounding box
bb = BoundingBox(p1, p2, self.video_width)
bb.is_annotated = True
self.result_bounding_boxes.append(bb)
# draw bounding box to original frame
self._drawBoundingBox(self.video_width, p1, p2, bb, (0, 255, 0), self.RECTANGLE_BORDER_PX)
else:
# tracking failure
cv2.putText(self.frame, "Tracking failure detected", self.TEXT_ROW4_POS, cv2.FONT_HERSHEY_SIMPLEX, self.FONT_SCALE, (0, 0, 255), self.FONT_WEIGHT)
# new instance of bounding box
bb = BoundingBox(None, None, self.video_width)
bb.is_annotated = False
self.result_bounding_boxes.append(bb)
# Display tracker type on frame
cv2.putText(self.frame, "SiamDW Tracker", self.TEXT_ROW1_POS, cv2.FONT_HERSHEY_SIMPLEX, self.FONT_SCALE, (0, 200, 250), self.FONT_WEIGHT)
# Display FPS on frame
cv2.putText(self.frame, "Video FPS : " + str(videoFPS), self.TEXT_ROW2_POS, cv2.FONT_HERSHEY_SIMPLEX, self.FONT_SCALE, (0, 250, 0), self.FONT_WEIGHT)
cv2.putText(self.frame, "Tracker FPS : " + str(int(fps)), self.TEXT_ROW3_POS, cv2.FONT_HERSHEY_SIMPLEX, self.FONT_SCALE, (0, 250, 0), self.FONT_WEIGHT)
# Display result
cv2.imshow(self.WINDOW_NAME, self.frame)
# waitKey time computing
# time in ms
time = int(1000 * (cv2.getTickCount() - timer) / cv2.getTickFrequency())
waitMiliseconds = 1
if (time >= interval):
waitMiliseconds = 1
else:
waitMiliseconds = interval - time
k = cv2.waitKey(waitMiliseconds) & 0xff
# Exit if 'Esc' or 'q' key is pressed
if k == 27 or k == ord("q"):
break
# always save tracker result
self._saveResults()
self.video.release()
cv2.destroyAllWindows()