├── .gitignore ├── LICENSE ├── README.md ├── controllers ├── __init__.py ├── base_controller.py ├── detect.py ├── ping.py └── track.py ├── docs └── surf.pdf ├── message ├── __init__.py ├── request.proto └── response.proto ├── models ├── Point.py └── __init__.py ├── requirements.txt ├── server.py ├── tests ├── __init__.py ├── test_image_filter.py ├── test_morphology.py ├── test_moving_target_outline.py └── test_sac.py └── utils ├── __init__.py ├── camera.py ├── image_utils.py ├── moving_target_outline.py ├── moving_target_track.py └── response.py /.gitignore: -------------------------------------------------------------------------------- 1 | /.idea 2 | __pycache__ 3 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | GNU GENERAL PUBLIC LICENSE 2 | Version 3, 29 June 2007 3 | 4 | Copyright (C) 2007 Free Software Foundation, Inc. 5 | Everyone is permitted to copy and distribute verbatim copies 6 | of this license document, but changing it is not allowed. 7 | 8 | Preamble 9 | 10 | The GNU General Public License is a free, copyleft license for 11 | software and other kinds of works. 12 | 13 | The licenses for most software and other practical works are designed 14 | to take away your freedom to share and change the works. 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Interpretation of Sections 15 and 16. 613 | 614 | If the disclaimer of warranty and limitation of liability provided 615 | above cannot be given local legal effect according to their terms, 616 | reviewing courts shall apply local law that most closely approximates 617 | an absolute waiver of all civil liability in connection with the 618 | Program, unless a warranty or assumption of liability accompanies a 619 | copy of the Program in return for a fee. 620 | 621 | END OF TERMS AND CONDITIONS 622 | 623 | How to Apply These Terms to Your New Programs 624 | 625 | If you develop a new program, and you want it to be of the greatest 626 | possible use to the public, the best way to achieve this is to make it 627 | free software which everyone can redistribute and change under these terms. 628 | 629 | To do so, attach the following notices to the program. It is safest 630 | to attach them to the start of each source file to most effectively 631 | state the exclusion of warranty; and each file should have at least 632 | the "copyright" line and a pointer to where the full notice is found. 633 | 634 | {one line to give the program's name and a brief idea of what it does.} 635 | Copyright (C) {year} {name of author} 636 | 637 | This program is free software: you can redistribute it and/or modify 638 | it under the terms of the GNU General Public License as published by 639 | the Free Software Foundation, either version 3 of the License, or 640 | (at your option) any later version. 641 | 642 | This program is distributed in the hope that it will be useful, 643 | but WITHOUT ANY WARRANTY; without even the implied warranty of 644 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 645 | GNU General Public License for more details. 646 | 647 | You should have received a copy of the GNU General Public License 648 | along with this program. If not, see . 649 | 650 | Also add information on how to contact you by electronic and paper mail. 651 | 652 | If the program does terminal interaction, make it output a short 653 | notice like this when it starts in an interactive mode: 654 | 655 | {project} Copyright (C) {year} {fullname} 656 | This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. 657 | This is free software, and you are welcome to redistribute it 658 | under certain conditions; type `show c' for details. 659 | 660 | The hypothetical commands `show w' and `show c' should show the appropriate 661 | parts of the General Public License. Of course, your program's commands 662 | might be different; for a GUI interface, you would use an "about box". 663 | 664 | You should also get your employer (if you work as a programmer) or school, 665 | if any, to sign a "copyright disclaimer" for the program, if necessary. 666 | For more information on this, and how to apply and follow the GNU GPL, see 667 | . 668 | 669 | The GNU General Public License does not permit incorporating your program 670 | into proprietary programs. If your program is a subroutine library, you 671 | may consider it more useful to permit linking proprietary applications with 672 | the library. If this is what you want to do, use the GNU Lesser General 673 | Public License instead of this License. But first, please read 674 | . -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | ## RealTimeTrackingCamera: 基于[OpenCV](https://github.com/opencv/opencv)的物体追踪摄像头 2 | 3 | ### 特性 4 | 5 | 1. 先让跟踪的目标运动一下，获取跟踪轮廓。 6 | 2. 通过轮廓匹配在实时的视频流中找到目标的运动轨迹。 7 | 3. 发送控制命令给舵机控制摄像头旋转。 8 | 9 | ### 关键点 10 | 11 | #### 获取跟踪轮廓 12 | 13 | 1. 通过一系列差分帧，两两差分直接进行与运算，找出与运算结果最大的一帧。 14 | 2. 闭运算连接孤立点。 15 | 3. 通过用户选择精细化边缘。 16 | 17 | #### 实时图像传输 18 | 19 | 1. 循环捕捉相机的帧。 20 | 2. 抓取到的帧使用jpeg编码成二进制字节流，使用protobuf协议，通过WebSocket传输到前端。 21 | 3. 前端使用标签显示图像，渲染可以通过src="data:img/jpeg;base64,xxx"方式渲染。 22 | 23 | #### 用户轮廓选择 24 | 25 | 1. 使用Canvas渲染图像 26 | 2. 通过MouseDown、MouseUp、MouseMove事件获取用户手势，使用beginPath()&closePath()以及clip()获取闭合路径。 27 | 3. 使用clearRect()清除图像显示背景图像。 28 | 29 | #### 目标追踪 30 | 31 | 1. 通过差分法获取运动边缘。 32 | 2. 使用腐蚀扩大白点范围。 33 | 3. 运动边缘作为mask搜索特征点，与用户选择图像进行匹配。 34 | 4. 使用PROSAC匹配点降低误差。 35 | 5. 计算特征点的重心。 36 | 37 | ### 依赖库 38 | 39 | 请阅读[requirements.txt](requirements.txt)。 40 | 41 | FE：[https://github.com/picone/RealTimeTrackingCamera_FE](https://github.com/picone/RealTimeTrackingCamera_FE) 42 | 43 | ### DOCs 44 | 45 | [SURF译文](docs/surf.pdf) 46 | 47 | ### Contributing 48 | 49 | 欢迎各种大佬提交宝贵代码OTZ__ 50 | 51 | ### TODO 52 | 53 | - 目标跟踪应该使用相关滤波和神经卷积网络 54 | 55 | ### LICENSE 56 | 57 | 你可以在[GPL 3.0](LICENSE)许可下自由使用本项目。 58 | -------------------------------------------------------------------------------- /controllers/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/picone/RealTimeTrackingCamera/c85a5e38d3df4f696ad51b943d00519214fc2dba/controllers/__init__.py -------------------------------------------------------------------------------- /controllers/base_controller.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | 3 | 4 | class BaseController: 5 | 6 | def execute(self, websocket): 7 | pass 8 | -------------------------------------------------------------------------------- /controllers/detect.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | import asyncio 3 | import cv2 4 | 5 | from controllers.base_controller import BaseController 6 | from message import request_pb2 7 | from message import response_pb2 8 | from utils.camera import Camera 9 | from utils.image_utils import ImageUtils 10 | from utils.moving_target_outline import MovingTargetOutline 11 | from websockets import ConnectionClosed 12 | 13 | 14 | class Detect(BaseController): 15 | 16 | def __init__(self): 17 | self.__outline = MovingTargetOutline() 18 | self.__is_capturing = False 19 | 20 | async def execute(self, websocket): 21 | self.__is_capturing = True 22 | await asyncio.wait([ 23 | asyncio.ensure_future(self._capture(websocket)), 24 | asyncio.ensure_future(self._wait_stop(websocket)), 25 | ]) 26 | # 直到收到停止命令 27 | background, max_difference_frame = self.__outline.get_max_difference_frame() 28 | if max_difference_frame is not None: 29 | response_frame = response_pb2.FrameResponse() 30 | response_frame.code = 1 31 | response_frame.type = response_pb2.FrameResponse.OUTLINE 32 | # 进行开运算连接孤立点 33 | max_difference_frame = ImageUtils.morphology(max_difference_frame, cv2.MORPH_OPEN, 3) 34 | response_frame.frame = ImageUtils.img2bytes(max_difference_frame) 35 | await websocket.send(response_frame.SerializeToString()) 36 | response_frame.type = response_pb2.FrameResponse.BACKGROUND 37 | response_frame.frame = ImageUtils.img2bytes(background) 38 | await websocket.send(response_frame.SerializeToString()) 39 | 40 | async def _capture(self, websocket): 41 | response_frame = response_pb2.FrameResponse() 42 | response_frame.code = 1 43 | response_frame.type = response_pb2.FrameResponse.VIDEO 44 | while self.__is_capturing: 45 | ret, img = Camera.get_frame() 46 | if ret: 47 | response_frame.frame = ImageUtils.img2bytes(img) 48 | try: 49 | await websocket.send(response_frame.SerializeToString()) 50 | except ConnectionClosed: 51 | self.__is_capturing = False 52 | self.__outline.add_frame(img) 53 | await asyncio.sleep(1 / 10) 54 | 55 | async def _wait_stop(self, websocket): 56 | try: 57 | response = await websocket.recv() 58 | command = request_pb2.CommandRequest() 59 | command.ParseFromString(response) 60 | if command.code == 1: 61 | self.__is_capturing = False 62 | except ConnectionClosed: 63 | self.__is_capturing = False 64 | -------------------------------------------------------------------------------- /controllers/ping.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | from controllers.base_controller import BaseController 3 | 4 | 5 | class Ping(BaseController): 6 | 7 | async def execute(self, websocket): 8 | await websocket.send("pong") 9 | -------------------------------------------------------------------------------- /controllers/track.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | import asyncio 3 | import copy 4 | 5 | from controllers.base_controller import BaseController 6 | from message import request_pb2 7 | from message import response_pb2 8 | from utils.camera import Camera 9 | from utils.image_utils import ImageUtils 10 | from utils.moving_target_track import MovingTargetTrack 11 | from websockets import ConnectionClosed 12 | 13 | 14 | class Track(BaseController): 15 | def __init__(self): 16 | self.__capture = False 17 | self.__target = None 18 | self.__tracker = None 19 | self.__mask = None 20 | 21 | async def execute(self, websocket): 22 | response = await websocket.recv() 23 | command = request_pb2.CommandRequest() 24 | command.ParseFromString(response) 25 | self.__target = ImageUtils.bytes2img(command.frame) 26 | self.__mask = ImageUtils.bytes2img(command.mask) 27 | self.__tracker = MovingTargetTrack(self.__target, self.__mask) 28 | if command.code == 2: 29 | self.__capture = True 30 | await asyncio.wait([ 31 | asyncio.ensure_future(self._send_frame(websocket)), 32 | asyncio.ensure_future(self._wait_stop(websocket)), 33 | ]) 34 | 35 | async def _send_frame(self, websocket): 36 | response = response_pb2.FrameResponse() 37 | response.code = 1 38 | response.type = response_pb2.FrameResponse.VIDEO 39 | while self.__capture: 40 | ret, img = Camera.get_frame() 41 | if ret: 42 | old_position, new_position, points = self.__tracker.track(img) 43 | response.position_x = new_position.x 44 | response.position_y = new_position.y 45 | response.points_count = len(points) 46 | img = copy.deepcopy(img) # 深复制,不然影响track内部 47 | # 把轮廓绘制到帧上 48 | if response.points_count > 0: 49 | ImageUtils.draw_points(img, points, 6, (0, 0, 255)) 50 | # 把质心绘制到帧上 51 | ImageUtils.draw_points(img, [(int(new_position.x), int(new_position.y))], 6, (0, 255, 0)) 52 | response.frame = ImageUtils.img2bytes(img) 53 | try: 54 | await websocket.send(response.SerializeToString()) 55 | except ConnectionClosed: 56 | self.__capture = False 57 | await asyncio.sleep(1 / 100) # 要加个sleep，不然无法让其他协程运行 58 | 59 | async def _wait_stop(self, websocket): 60 | try: 61 | response = await websocket.recv() 62 | command = request_pb2.CommandRequest() 63 | command.ParseFromString(response) 64 | if command.code == 1: 65 | self.__capture = False 66 | except ConnectionClosed: 67 | print("Connection has closed") 68 | -------------------------------------------------------------------------------- /docs/surf.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/picone/RealTimeTrackingCamera/c85a5e38d3df4f696ad51b943d00519214fc2dba/docs/surf.pdf -------------------------------------------------------------------------------- /message/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/picone/RealTimeTrackingCamera/c85a5e38d3df4f696ad51b943d00519214fc2dba/message/__init__.py -------------------------------------------------------------------------------- /message/request.proto: -------------------------------------------------------------------------------- 1 | syntax = "proto3"; 2 | 3 | message CommandRequest { 4 | int32 code = 1; 5 | bytes frame = 16; 6 | bytes mask = 17; 7 | } 8 | -------------------------------------------------------------------------------- /message/response.proto: -------------------------------------------------------------------------------- 1 | syntax = "proto3"; 2 | 3 | message FrameResponse { 4 | int32 code = 1; 5 | enum Type { 6 | VIDEO = 0;//视频帧 7 | OUTLINE = 1;//轮廓帧 8 | BACKGROUND = 2;//背景帧 9 | } 10 | Type type = 2; 11 | bytes frame = 3; 12 | float position_x = 16;//物体横坐标 13 | float position_y = 17;//物体纵坐标 14 | int32 points_count = 18;//匹配特征点数 15 | } 16 | -------------------------------------------------------------------------------- /models/Point.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | 3 | 4 | class Point(object): 5 | def __init__(self, x=-1, y=-1): 6 | """ 7 | 构造函数 8 | """ 9 | self.__x = x 10 | self.__y = y 11 | 12 | @property 13 | def x(self): 14 | """ 15 | 设置横坐标 16 | :rtype: float|int 17 | :return: 18 | """ 19 | return self.__x 20 | 21 | @property 22 | def y(self): 23 | """ 24 | 设置纵坐标 25 | :rtype: float|int 26 | :return: 27 | """ 28 | return self.__y 29 | 30 | def set(self, x, y): 31 | """ 32 | 设置点坐标 33 | :param float|int x: 34 | :param float|int y: 35 | """ 36 | self.__x = x 37 | self.__y = y 38 | 39 | def is_point(self): 40 | """ 41 | 判断是否合法坐标 42 | :rtype: bool 43 | :return: 44 | """ 45 | return self.__x < 0 or self.__y < 0 46 | 47 | def __str__(self): 48 | return "x:%f,y:%s" % (self.__x, self.__y) 49 | 50 | __repr__ = __str__ 51 | -------------------------------------------------------------------------------- /models/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/picone/RealTimeTrackingCamera/c85a5e38d3df4f696ad51b943d00519214fc2dba/models/__init__.py -------------------------------------------------------------------------------- /requirements.txt: -------------------------------------------------------------------------------- 1 | numpy==1.14.0 2 | opencv-contrib-python==3.4.0.12 3 | opencv-python==3.4.0.12 4 | protobuf==3.5.1 5 | six==1.11.0 6 | websockets==4.0.1 7 | -------------------------------------------------------------------------------- /server.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | import asyncio 3 | import websockets 4 | 5 | 6 | async def websocket_handler(websocket, path): 7 | """ 8 | 实现websocket命令路由 9 | """ 10 | path = str(path[1:]).split("/") 11 | if len(path) == 1: 12 | path.append("execute") 13 | try: 14 | controller = __import__("controllers." + path[0], fromlist=True) 15 | class_name = str(path[0]).capitalize() 16 | if hasattr(controller, class_name): 17 | class_name = getattr(controller, class_name) 18 | if not hasattr(class_name, path[1]): 19 | raise ModuleNotFoundError() 20 | else: 21 | raise ModuleNotFoundError() 22 | obj = class_name() 23 | func = getattr(obj, path[1]) 24 | await func(websocket) 25 | except ModuleNotFoundError: 26 | print("RouterNotFound") 27 | 28 | start_server = websockets.serve(websocket_handler, "localhost", 8080) 29 | 30 | asyncio.get_event_loop().run_until_complete(start_server) 31 | asyncio.get_event_loop().run_forever() 32 | -------------------------------------------------------------------------------- /tests/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/picone/RealTimeTrackingCamera/c85a5e38d3df4f696ad51b943d00519214fc2dba/tests/__init__.py -------------------------------------------------------------------------------- /tests/test_image_filter.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | import cv2 3 | import unittest 4 | 5 | from utils.image_utils import ImageUtils 6 | 7 | 8 | class TestImageFilter(unittest.TestCase): 9 | 10 | def setUp(self): 11 | self.__image = cv2.imread("outputs/1_0.jpg") 12 | if self.__image is None: 13 | self.fail("读取样本失败") 14 | _, img = ImageUtils.binary(self.__image, threshold_type=cv2.THRESH_OTSU) 15 | cv2.imwrite("result/origin.jpg", img) 16 | 17 | def test_median_blur(self): 18 | """ 19 | 中值滤波 20 | """ 21 | ret = cv2.medianBlur(self.__image, 1) 22 | cv2.imwrite("result/median_0.jpg", ret) 23 | _, ret = ImageUtils.binary(ret, threshold_type=cv2.THRESH_OTSU) 24 | cv2.imwrite("result/median_1.jpg", ret) 25 | 26 | def test_gaussian_blur(self): 27 | """ 28 | 高斯滤波 29 | """ 30 | ret = cv2.GaussianBlur(self.__image, (3, 3), 0.8) 31 | cv2.imwrite("result/gaussian_0.jpg", ret) 32 | _, ret = ImageUtils.binary(ret, threshold_type=cv2.THRESH_OTSU) 33 | cv2.imwrite("result/gaussian_1.jpg", ret) 34 | 35 | def test_mean_blur(self): 36 | """ 37 | 均值滤波 38 | """ 39 | ret = cv2.pyrMeanShiftFiltering(self.__image, 3, 3) 40 | cv2.imwrite("result/mean_0.jpg", ret) 41 | _, ret = ImageUtils.binary(ret, threshold_type=cv2.THRESH_OTSU) 42 | cv2.imwrite("result/mean_1.jpg", ret) 43 | -------------------------------------------------------------------------------- /tests/test_morphology.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | import cv2 3 | import unittest 4 | 5 | from utils.image_utils import ImageUtils 6 | 7 | 8 | class TestImageFilter(unittest.TestCase): 9 | 10 | def setUp(self): 11 | self.__image = cv2.imread("result/gaussian_1.jpg") 12 | if self.__image is None: 13 | self.fail("读取样本失败") 14 | 15 | def test_dilate(self): 16 | """ 17 | 膨胀 18 | """ 19 | ret = ImageUtils.morphology(self.__image, cv2.MORPH_DILATE, 2) 20 | _, ret = ImageUtils.binary(ret, threshold_type=cv2.THRESH_OTSU) 21 | cv2.imwrite("result/dilate.jpg", ret) 22 | 23 | def test_erode(self): 24 | """ 25 | 腐蚀 26 | """ 27 | ret = ImageUtils.morphology(self.__image, cv2.MORPH_ERODE, 2) 28 | _, ret = ImageUtils.binary(ret, threshold_type=cv2.THRESH_OTSU) 29 | cv2.imwrite("result/erode.jpg", ret) 30 | 31 | def test_close(self): 32 | """ 33 | 闭运算 34 | """ 35 | ret = ImageUtils.morphology(self.__image, cv2.MORPH_CLOSE, 8) 36 | _, ret = ImageUtils.binary(ret, threshold_type=cv2.THRESH_OTSU) 37 | cv2.imwrite("result/close.jpg", ret) 38 | -------------------------------------------------------------------------------- /tests/test_moving_target_outline.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | import cv2 3 | import unittest 4 | from utils.moving_target_outline import MovingTargetOutline 5 | 6 | 7 | class TestMovingTargetOutline(unittest.TestCase): 8 | 9 | def setUp(self): 10 | cap = cv2.VideoCapture(0) 11 | if cap is None or not cap.isOpened(): 12 | self.fail("启动摄像头失败") 13 | self.__cap = cap 14 | 15 | def test_get_max_difference_frame(self): 16 | outline = MovingTargetOutline() 17 | for i in range(1, 5): 18 | ret, img = self.__cap.read() 19 | if not ret: 20 | break 21 | outline.add_frame(img) 22 | max_difference_frame = outline.get_max_difference_frame() 23 | self.assertIsNotNone(max_difference_frame) 24 | -------------------------------------------------------------------------------- /tests/test_sac.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | import cv2 3 | import unittest 4 | 5 | import time 6 | 7 | from utils.camera import Camera 8 | from utils.image_utils import ImageUtils 9 | 10 | 11 | class TestImageFilter(unittest.TestCase): 12 | 13 | def setUp(self): 14 | target = cv2.imread("result/track_target.jpg") 15 | mask = cv2.imread("result/mask.jpg") 16 | self.__target = cv2.cvtColor(target, cv2.COLOR_BGR2GRAY) 17 | _, self.__mask = ImageUtils.binary(mask, threshold_type=cv2.THRESH_OTSU) 18 | self.__target_key_points, self.__target_descriptors = ImageUtils.get_key_points(self.__target, self.__mask) 19 | 20 | def test_ransac(self): 21 | """ 22 | 随机抽样一致 23 | """ 24 | Camera.reset() 25 | self.__last_frame = None 26 | print("RANSAC") 27 | for i in range(1, 30): 28 | start = time.clock() 29 | _, frame = Camera.get_frame() 30 | if self.__last_frame is None: 31 | self.__last_frame = frame 32 | continue 33 | img = cv2.absdiff(frame, self.__last_frame) 34 | self.__last_frame = frame 35 | img = cv2.GaussianBlur(img, (5, 5), 2.5) 36 | img = ImageUtils.morphology(img, cv2.MORPH_DILATE, 16) 37 | _, img = ImageUtils.binary(img, threshold_type=cv2.THRESH_OTSU) 38 | # 计算特征点 39 | key_points, descriptors = ImageUtils.get_key_points(frame, img) 40 | matches = ImageUtils.knn_match(self.__target_descriptors, descriptors) 41 | if len(matches) > 0: 42 | # 匹配到合适的特征点 43 | points = ImageUtils.get_matches_points(key_points, matches) 44 | src_key_points = ImageUtils.get_matches_points(self.__target_key_points, matches, 1) 45 | # RANSAC去除错误点 46 | _, mask = cv2.findHomography(src_key_points, points, cv2.RANSAC) 47 | if mask is not None: 48 | points_after = points[mask.ravel() == 1] 49 | end = time.clock() 50 | print("%d\t%d\t%d\t%f" % (i, len(points), len(points_after), end-start)) 51 | 52 | def test_prosac(self): 53 | """ 54 | 改进抽样一致 55 | """ 56 | Camera.reset() 57 | self.__last_frame = None 58 | print("PROSAC") 59 | for i in range(1, 30): 60 | start = time.clock() 61 | _, frame = Camera.get_frame() 62 | if self.__last_frame is None: 63 | self.__last_frame = frame 64 | continue 65 | img = cv2.absdiff(frame, self.__last_frame) 66 | self.__last_frame = frame 67 | img = cv2.GaussianBlur(img, (5, 5), 2.5) 68 | img = ImageUtils.morphology(img, cv2.MORPH_DILATE, 16) 69 | _, img = ImageUtils.binary(img, threshold_type=cv2.THRESH_OTSU) 70 | # 计算特征点 71 | key_points, descriptors = ImageUtils.get_key_points(frame, img) 72 | matches = ImageUtils.knn_match(self.__target_descriptors, descriptors) 73 | if len(matches) > 0: 74 | # 匹配到合适的特征点 75 | points = ImageUtils.get_matches_points(key_points, matches) 76 | src_key_points = ImageUtils.get_matches_points(self.__target_key_points, matches, 1) 77 | # PROSAC去除错误点 78 | _, mask = cv2.findHomography(src_key_points, points, cv2.RHO) 79 | if mask is not None: 80 | points_after = points[mask.ravel() == 1] 81 | end = time.clock() 82 | print("%d\t%d\t%d\t%f" % (i, len(points), len(points_after), end - start)) 83 | -------------------------------------------------------------------------------- /utils/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/picone/RealTimeTrackingCamera/c85a5e38d3df4f696ad51b943d00519214fc2dba/utils/__init__.py -------------------------------------------------------------------------------- /utils/camera.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | import cv2 3 | 4 | 5 | class Camera: 6 | 7 | #_cap = cv2.VideoCapture(0) 8 | _cap = cv2.VideoCapture("TUD-Stadtmitte.mp4") 9 | 10 | @classmethod 11 | def get_frame(cls): 12 | return cls._cap.read() 13 | 14 | @classmethod 15 | def reset(cls): 16 | cls._cap.retrieve() 17 | -------------------------------------------------------------------------------- /utils/image_utils.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | import cv2 3 | import numpy 4 | 5 | from models.Point import Point 6 | 7 | 8 | class ImageUtils: 9 | @staticmethod 10 | def binary(src, threshold=0, maxval=255, threshold_type=cv2.THRESH_OTSU): 11 | """ 二值化图像 12 | :type src: numpy.ndarray 13 | :param src: 待处理图像 14 | :type threshold: int 15 | :param threshold: 阈值 16 | :type maxval: int 17 | :param maxval: 最大值，与THRESH_BINARY和THRESH_BINARY_INV一起使用 18 | :type threshold_type: int 19 | :param threshold_type: 自动选择阈值的算法，可选值: 20 | THRESH_BINARY 21 | THRESH_BINARY_INV 22 | THRESH_TRUNC 23 | THRESH_TOZERO 24 | THRESH_TOZERO_INV 25 | THRESH_MASK 26 | THRESH_OTSU 大律法 27 | THRESH_TRIANGLE 三角法 28 | 参考https://docs.opencv.org/master/d7/d1b/group__imgproc__misc.html#gaa9e58d2860d4afa658ef70a9b1115576 29 | :rtype: (int, numpy.ndarray) 30 | :returns: (阈值，类型与src相同) 31 | """ 32 | # 三通道的先灰度处理 33 | if src.dtype and len(src.shape) == 3 and src.shape[2] == 3: 34 | src = cv2.cvtColor(src, cv2.COLOR_BGR2GRAY) 35 | return cv2.threshold(src, threshold, maxval, threshold_type) 36 | 37 | @staticmethod 38 | def img2bytes(img): 39 | """ 40 | :type img: numpy.ndarray 41 | :param img: img图像 42 | :rtype: bytearray | None 43 | :return: 字节流 44 | """ 45 | ret, img = cv2.imencode(".jpg", img) 46 | if ret: 47 | return numpy.array(img).tobytes() 48 | else: 49 | return None 50 | 51 | @staticmethod 52 | def bytes2img(img): 53 | buffer = numpy.asarray(bytearray(img), dtype="uint8") 54 | return cv2.imdecode(buffer, cv2.IMREAD_COLOR) 55 | 56 | @staticmethod 57 | def get_centroid(points): 58 | """ 59 | 计算质心 60 | :param points: 61 | :return Point: 62 | """ 63 | points = numpy.array(points) 64 | return Point(points[:, 0].mean(), points[:, 1].mean()) 65 | 66 | @staticmethod 67 | def compare_hu_moments(hu_moments_a, hu_moments_b): 68 | """ 69 | 计算两个hu矩的相似度，相当于cv2.CONTOURS_MATCH_I1 70 | :param list hu_moments_a: 71 | :param list hu_moments_b: 72 | :return float|bool: 73 | """ 74 | hu_moments_a = numpy.array(hu_moments_a) 75 | hu_moments_b = numpy.array(hu_moments_b) 76 | if numpy.count_nonzero(hu_moments_a, 1).sum() != 7 or numpy.count_nonzero(hu_moments_b, 1).sum() != 7: 77 | return False 78 | return numpy.sum(numpy.abs(1 / numpy.sign(hu_moments_a) * numpy.log(numpy.abs(hu_moments_a)) 79 | - 1 / numpy.sign(hu_moments_b) * numpy.log(numpy.abs(hu_moments_b)))) 80 | 81 | @staticmethod 82 | def morphology(img, operation, iteration=1, kernel_size=(5, 5)): 83 | """ 84 | 进行开运算 85 | :param numpy.ndarray img: 86 | :param int operation: 使用的操作 87 | :param int iteration: 迭代次数 88 | :param list kernel_size: 卷积核大小 89 | :return numpy.ndarray: 90 | """ 91 | kernel = cv2.getStructuringElement(cv2.MORPH_RECT, kernel_size) 92 | return cv2.morphologyEx(img, operation, kernel, iterations=iteration) 93 | 94 | @staticmethod 95 | def get_key_points(img, mask=None, hessian_threshold=100): 96 | """ 97 | 计算特征点 98 | :param numpy.ndarray img: 99 | :param numpy.ndarray mask: 100 | :param int hessian_threshold: 101 | :return list, list: 102 | """ 103 | surf = cv2.xfeatures2d.SURF_create(hessian_threshold) 104 | return surf.detectAndCompute(img, mask) 105 | 106 | @staticmethod 107 | def knn_match(descriptors_a, descriptors_b, good_distance=0.7): 108 | """ 109 | 匹配descriptors 110 | :param list descriptors_a: 111 | :param list descriptors_b: 112 | :param int k: 至少匹配特征值 113 | :param float good_distance: 距离阈值 114 | :return list: 115 | """ 116 | FLANN_INDEX_KDTREE = 1 # bug: flann enums are missing 117 | index_params = dict(algorithm=FLANN_INDEX_KDTREE, trees=3) 118 | search_params = dict(checks=100) 119 | flann = cv2.FlannBasedMatcher(index_params, search_params) 120 | try: 121 | matches = flann.knnMatch(descriptors_a, descriptors_b, 2) 122 | except Exception: 123 | return () 124 | if good_distance > 0: 125 | ret = [] 126 | for m, n in matches: 127 | if m.distance < good_distance * n.distance: 128 | ret.append(m) 129 | return ret 130 | else: 131 | return matches 132 | 133 | @staticmethod 134 | def get_matches_points(points, matches, idx=0): 135 | """ 136 | 获取匹配的点坐标 137 | :param list points: 138 | :param list(DMatch) matches: 139 | :param int idx: 140 | :return numpy.ndarray: 141 | """ 142 | if idx == 0: 143 | return numpy.float32([points[m.trainIdx].pt for m in matches]) 144 | else: 145 | return numpy.float32([points[m.queryIdx].pt for m in matches]) 146 | 147 | @staticmethod 148 | def draw_points(img, points, radius, color): 149 | """ 150 | 绘制一系列点在图片上 151 | :param numpy.ndarray img: 152 | :param list points: 153 | :param int radius: 154 | :param tuple color: 155 | :return: 156 | """ 157 | for point in points: 158 | cv2.circle(img, point, radius, color, cv2.FILLED) 159 | 160 | @staticmethod 161 | def scale_image(img, max_width=0, max_height=0, keep_ratio=True, ratio=1): 162 | """ 163 | 缩放图像 164 | :param numpy.ndarray img: 165 | :param int max_width: 166 | :param int max_height: 167 | :param bool keep_ratio: 168 | :param int ratio: 169 | :return int: 170 | """ 171 | if ratio != 1: 172 | height, width, _ = img.shape 173 | return ratio, cv2.resize(img, (int(width / ratio), int(height / ratio))) 174 | elif keep_ratio and max_width > 0 and max_height > 0: 175 | height, width, _ = img.shape 176 | width_ratio = width / max_width 177 | height_ratio = height / max_height 178 | ratio = max(width_ratio, height_ratio) 179 | return ratio, cv2.resize(img, (int(width / ratio), int(height / ratio))) 180 | else: 181 | return 0, cv2.resize(img, (max_width, max_height)) 182 | 183 | @staticmethod 184 | def scale_points(points, ratio): 185 | return numpy.array(points) * ratio 186 | 187 | @staticmethod 188 | def duplicate_points(points): 189 | visited = dict() 190 | ret = list() 191 | for point in points: 192 | x, y = int(point[0]), int(point[1]) 193 | if x not in visited: 194 | visited[x] = {} 195 | if y not in visited[x]: 196 | visited[x][y] = 1 197 | ret.append((x, y)) 198 | return ret 199 | 200 | @staticmethod 201 | def affinity_point(point, matrix): 202 | if type(point) == Point: 203 | x = (matrix[0][0] * point.x + matrix[0][1] * point.y + matrix[0][2]) \ 204 | / (matrix[2][0] * point.x + matrix[2][1] * point.y + matrix[2][2]) 205 | y = (matrix[1][0] * point.x + matrix[1][1] * point.y + matrix[1][2]) \ 206 | / (matrix[2][0] * point.x + matrix[2][1] * point.y + matrix[2][2]) 207 | return Point(x, y) 208 | else: 209 | x = (matrix[0][0] * point[0] + matrix[0][1] * point[1] + matrix[0][2]) \ 210 | / (matrix[2][0] * point[0] + matrix[2][1] * point[1] + matrix[2][2]) 211 | y = (matrix[1][0] * point[0] + matrix[1][1] * point[1] + matrix[1][2]) \ 212 | / (matrix[2][0] * point[0] + matrix[2][1] * point[1] + matrix[2][2]) 213 | return numpy.array([[int(x), int(y)]]) 214 | 215 | @staticmethod 216 | def create_img(shape): 217 | return numpy.zeros(shape, dtype=numpy.uint8) 218 | -------------------------------------------------------------------------------- /utils/moving_target_outline.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | import cv2 3 | import multiprocessing 4 | 5 | from utils.image_utils import ImageUtils 6 | 7 | 8 | class MovingTargetOutline: 9 | """ 10 | 对连续帧运动目标提取轮廓 11 | """ 12 | 13 | def __init__(self): 14 | self.__video_frames = [] 15 | 16 | def add_frame(self, frame): 17 | """ 18 | 添加一帧 19 | :param frame: 一帧 20 | """ 21 | self.__video_frames.append(frame) 22 | 23 | def set_frames(self, frames): 24 | """ 25 | 设置帧序列（会重置帧） 26 | :type frames: tuple 27 | :param frames: 帧序列 28 | """ 29 | self.__video_frames = frames 30 | 31 | def reset(self): 32 | """ 33 | 重置所有帧 34 | """ 35 | self.__video_frames = [] 36 | 37 | def get_max_difference_frame(self): 38 | """ 39 | 使用三帧差分法 40 | :rtype: numpy.ndarray, numpy.ndarray 41 | :return: 差分帧像素最多的一帧 42 | """ 43 | frame_len = len(self.__video_frames) 44 | # 帧数大于1才能差分 45 | if frame_len <= 1: 46 | return None, None 47 | # 每帧之间求差分,结果要求按顺序 48 | # 多进程使用cvtColor会崩溃？？？ 49 | result_difference_frame = [] 50 | for i in range(0, (frame_len - 2) if frame_len % 2 == 0 else (frame_len - 1)): 51 | difference_frame = self._get_difference_frame(self.__video_frames[i], self.__video_frames[i + 1]) 52 | result_difference_frame.append(difference_frame) 53 | with multiprocessing.Pool() as pool: 54 | # 对差分帧每帧之间与运算 55 | max_none_zero = 0 56 | max_difference_frame = None 57 | max_difference_frame_index = None 58 | for none_zero, frame_index, and_frame in pool.imap_unordered( 59 | self._get_and_frame, 60 | map( 61 | lambda x: (x, result_difference_frame[x], x + 1, result_difference_frame[x + 1]), 62 | range(0, len(result_difference_frame) - 1) 63 | ) 64 | ): 65 | if none_zero > max_none_zero: 66 | max_none_zero = none_zero 67 | max_difference_frame = and_frame 68 | max_difference_frame_index = frame_index + 1 69 | if max_difference_frame_index: 70 | return self.__video_frames[max_difference_frame_index], max_difference_frame 71 | return None, None 72 | 73 | @staticmethod 74 | def _get_difference_frame(pre_frame, next_frame): 75 | """ 76 | 帧进行差分并二值化，二值化使用OTSU算法 77 | :param numpy.ndarray pre_frame: 前一帧 78 | :param numpy.ndarray next_frame: 后一帧 79 | :rtype: numpy.ndarray 80 | :returns: 差分帧 81 | """ 82 | img = cv2.absdiff(pre_frame, next_frame) 83 | # 灰度处理后再高斯滤波，降低计算量 84 | img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) 85 | img = cv2.GaussianBlur(img, (5, 5), 2.5) 86 | _, img = ImageUtils.binary(img, threshold_type=cv2.THRESH_BINARY_INV | cv2.THRESH_OTSU) 87 | return img 88 | 89 | @staticmethod 90 | def _get_and_frame(args): 91 | """ 92 | 帧进行与运算 93 | :param tuple args: args[0]前一帧下标, args[1]前一帧, args[2]后一帧下标, args[3]后一帧 94 | :rtype: (int, numpy.ndarray) 95 | :return: (非0像素个数，帧与运算结果) 96 | """ 97 | img = cv2.bitwise_and(args[1], args[3]) 98 | return cv2.countNonZero(img), args[0], img 99 | -------------------------------------------------------------------------------- /utils/moving_target_track.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | import cv2 3 | import numpy 4 | 5 | from models.Point import Point 6 | from utils.camera import Camera 7 | from utils.image_utils import ImageUtils 8 | 9 | 10 | class MovingTargetTrack: 11 | """ 12 | 模板跟踪 13 | """ 14 | __match_points_ratio = 100 15 | 16 | def __init__(self, target, mask): 17 | """ 18 | 构造函数 19 | :param numpy.ndArray target: 要跟踪的目标 20 | """ 21 | self.__last_frame = None 22 | # self.__target_ratio, self.__target = ImageUtils.scale_image(target, 1080, 720) 23 | self.__target = cv2.cvtColor(target, cv2.COLOR_BGR2GRAY) 24 | _, mask_binary = ImageUtils.binary(mask, threshold_type=cv2.THRESH_OTSU) 25 | self.__target_key_points, self.__target_descriptors = ImageUtils.get_key_points(self.__target, mask_binary) 26 | self.__target_key_points_len = len(self.__target_key_points) 27 | # 查找mask重心 28 | _, contours, _ = cv2.findContours(mask_binary, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) 29 | self.__mask_contour = contours[0] 30 | moments = cv2.moments(self.__mask_contour) 31 | self.__position = Point(moments['m10'] / moments['m00'], moments['m01'] / moments['m00']) 32 | # 计算颜色直方图 33 | # target_mask = cv2.bitwise_and(target, mask) 34 | # target_hsv = cv2.cvtColor(target_mask, cv2.COLOR_BGR2HSV) 35 | # target_hist = cv2.calcHist(target_hsv, [0, 1], None, [50, 60], [0, 256, 0, 180]) 36 | # self.__target_hist = None 37 | # cv2.normalize(target_hist, self.__target_hist) 38 | print("特征点数:%d" % self.__target_key_points_len) 39 | 40 | def track(self, frame): 41 | """ 42 | 更新目标的新坐标，并返回新旧质心坐标 43 | 通过差分获取轮廓，Hu矩匹配 44 | :param numpy.ndArray frame: 45 | :return (Point, Point, list|None): 新旧坐标 46 | """ 47 | # _, frame = ImageUtils.scale_image(frame, ratio=self.__target_ratio) 48 | if self.__last_frame is None: 49 | self.__last_frame = frame 50 | return self.__position, self.__position, () 51 | 52 | img = cv2.absdiff(frame, self.__last_frame) 53 | self.__last_frame = frame 54 | img = cv2.GaussianBlur(img, (5, 5), 2.5) 55 | img = ImageUtils.morphology(img, cv2.MORPH_DILATE, 16) 56 | _, img = ImageUtils.binary(img, threshold_type=cv2.THRESH_OTSU) 57 | # 计算特征点 58 | key_points, descriptors = ImageUtils.get_key_points(frame, img) 59 | if len(key_points) * self.__match_points_ratio > self.get_key_points_count(): 60 | matches = ImageUtils.knn_match(self.__target_descriptors, descriptors) 61 | if len(matches) > 0: 62 | # 匹配到合适的特征点 63 | points = ImageUtils.get_matches_points(key_points, matches) 64 | src_key_points = ImageUtils.get_matches_points(self.__target_key_points, matches, 1) 65 | # PROSAC去除错误点 66 | h, mask = cv2.findHomography(src_key_points, points, cv2.RHO) 67 | if mask is not None: 68 | points = points[mask.ravel() == 1] 69 | if len(points) > 0: 70 | # points = ImageUtils.scale_points(points, self.__target_ratio) 71 | points = ImageUtils.duplicate_points(points) 72 | old_position = self.__position 73 | self.__position = ImageUtils.affinity_point(old_position, h) 74 | return old_position, self.__position, points 75 | 76 | # 匹配到的特征点较少 77 | return self.__position, self.__position, () 78 | 79 | def get_key_points_count(self): 80 | """ 81 | 获取关键点数 82 | :return int: 83 | """ 84 | return self.__target_key_points_len 85 | -------------------------------------------------------------------------------- /utils/response.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | import json 3 | 4 | 5 | class Response: 6 | 7 | _response_msg = { 8 | 1: "OK", 9 | 10: "JSON解析失败", 10 | 11: "未知错误", 11 | 12: "路径不存在", 12 | } 13 | 14 | @classmethod 15 | def get(cls, code, data=None, msg=None): 16 | """ 17 | 获取消息响应json 18 | :type code: int 19 | :param code: 消息代码 20 | :type data: Dict | None 21 | :param data: 附加数据 22 | :type msg: string 23 | :param msg: 附加消息 24 | :rtype: string 25 | :return: 返回的json 26 | """ 27 | response = {"code": code, "data": data} 28 | if msg is None and cls._response_msg[code]: 29 | response["msg"] = cls._response_msg[code] 30 | return json.dumps(response) 31 | --------------------------------------------------------------------------------