├── .gitignore ├── LICENSE ├── README.rst ├── calibration ├── board.png ├── calibration.json ├── charuco_calibration.ipynb ├── openpose │ ├── calibration_boards │ │ └── intrinsics │ │ │ ├── 18284509 │ │ │ ├── capture_0.jpg │ │ │ ├── capture_1.jpg │ │ │ ├── capture_10.jpg │ │ │ ├── capture_11.jpg │ │ │ ├── capture_12.jpg │ │ │ ├── capture_13.jpg │ │ │ ├── capture_14.jpg │ │ │ ├── capture_2.jpg │ │ │ ├── capture_24.jpg │ │ │ ├── capture_25.jpg │ │ │ ├── capture_26.jpg │ │ │ ├── capture_27.jpg │ │ │ ├── capture_28.jpg │ │ │ ├── capture_29.jpg │ │ │ ├── capture_3.jpg │ │ │ ├── capture_30.jpg │ │ │ ├── capture_31.jpg │ │ │ ├── capture_32.jpg │ │ │ ├── capture_4.jpg │ │ │ ├── capture_5.jpg │ │ │ ├── capture_6.jpg │ │ │ ├── capture_7.jpg │ │ │ └── capture_9.jpg │ │ │ ├── 18284511 │ │ │ ├── capture_0.jpg │ │ │ ├── capture_1.jpg │ │ │ ├── capture_10.jpg │ │ │ ├── capture_11.jpg │ │ │ ├── capture_12.jpg │ │ │ ├── capture_13.jpg │ │ │ ├── capture_14.jpg │ │ │ ├── capture_15.jpg │ │ │ ├── capture_16.jpg │ │ │ ├── capture_17.jpg │ │ │ ├── capture_18.jpg │ │ │ ├── capture_19.jpg │ │ │ ├── capture_2.jpg │ │ │ ├── capture_20.jpg │ │ │ ├── capture_21.jpg │ │ │ ├── capture_22.jpg │ │ │ ├── capture_3.jpg │ │ │ ├── capture_4.jpg │ │ │ ├── capture_5.jpg │ │ │ ├── capture_6.jpg │ │ │ ├── capture_7.jpg │ │ │ ├── capture_8.jpg │ │ │ └── capture_9.jpg │ │ │ └── 18284512 │ │ │ ├── capture_11.jpg │ │ │ ├── capture_12.jpg │ │ │ ├── capture_14.jpg │ │ │ ├── capture_15.jpg │ │ │ ├── capture_16.jpg │ │ │ ├── capture_17.jpg │ │ │ ├── capture_18.jpg │ │ │ ├── capture_20.jpg │ │ │ ├── capture_21.jpg │ │ │ ├── capture_22.jpg │ │ │ ├── capture_23.jpg │ │ │ ├── capture_24.jpg │ │ │ ├── capture_25.jpg │ │ │ ├── capture_5.jpg │ │ │ ├── capture_6.jpg │ │ │ └── tmp │ │ │ ├── capture_0.jpg │ │ │ ├── capture_1.jpg │ │ │ ├── capture_10.jpg │ │ │ ├── capture_13.jpg │ │ │ ├── capture_19.jpg │ │ │ ├── capture_2.jpg │ │ │ ├── capture_3.jpg │ │ │ ├── capture_4.jpg │ │ │ ├── capture_7.jpg │ │ │ ├── capture_8.jpg │ │ │ └── capture_9.jpg │ ├── captured-data │ │ ├── frame_00.jpg │ │ ├── frame_00.json │ │ ├── frame_00_annotated.jpg │ │ ├── frame_01.jpg │ │ ├── frame_01.json │ │ ├── frame_01_annotated.jpg │ │ ├── frame_02.jpg │ │ ├── frame_02.json │ │ ├── frame_02_annotated.jpg │ │ ├── frame_03.jpg │ │ ├── frame_03.json │ │ └── frame_03_annotated.jpg │ ├── charuco_origin.ipynb │ ├── charuco_pose_estimation.ipynb │ ├── chessboard_alternative_calibration.ipynb │ ├── compare_calibration.ipynb │ ├── flir_aruco.py │ ├── models │ │ ├── 18284509.xml │ │ ├── 18284511.xml │ │ └── 18284512.xml │ └── sample-data │ │ ├── 18284509 │ │ ├── capture_0.jpg │ │ ├── capture_1.jpg │ │ ├── capture_2.jpg │ │ └── capture_3.jpg │ │ ├── 18284511 │ │ ├── capture_0.jpg │ │ ├── capture_1.jpg │ │ ├── capture_2.jpg │ │ └── capture_3.jpg │ │ └── 18284512 │ │ ├── capture_0.jpg │ │ ├── capture_1.jpg │ │ └── capture_2.jpg ├── points_imageframe_1.jpg.json ├── points_imageframe_10.jpg.json ├── points_imageframe_11.jpg.json ├── points_imageframe_2.jpg.json ├── points_imageframe_3.jpg.json ├── points_imageframe_4.jpg.json ├── points_imageframe_5.jpg.json ├── points_imageframe_6.jpg.json ├── points_imageframe_7.jpg.json ├── points_imageframe_8.jpg.json ├── points_imageframe_9.jpg.json └── sample-data │ ├── calibration.json │ ├── frame_1.jpg │ ├── frame_10.jpg │ ├── frame_11.jpg │ ├── frame_2.jpg │ ├── frame_3.jpg │ ├── frame_4.jpg │ ├── frame_5.jpg │ ├── frame_6.jpg │ ├── frame_7.jpg │ ├── frame_8.jpg │ ├── frame_9.jpg │ ├── test_frame_1.jpg │ ├── test_frame_2.jpg │ ├── test_frame_3.jpg │ ├── test_frame_4.jpg │ └── test_frame_5.jpg ├── data ├── ChAruCo 11x8, 300dpi, 50mm spacing, 30mm markers.pdf └── board.pdf ├── flir ├── README.rst ├── common.py ├── flir_capture.py ├── flir_capture_all_continuous.py ├── flir_capture_multiple.py ├── flir_capture_multiple_video.py ├── flir_capture_single.py ├── flir_capture_single_continuous.py ├── flir_detect_aruco.py └── fps_counter.py ├── img └── kinect_detection.jpg ├── kinect-v2 ├── README.rst ├── body.py ├── cap │ ├── frame_0.jpg │ ├── frame_0.json │ └── frame_0_annotated.jpg ├── capture_board.py ├── color.py ├── color_3d.py ├── depth.py ├── detect_aruco.py ├── detect_charuco.py ├── frame_0.jpg ├── frame_0.json ├── infrared.py └── sample-data │ ├── frame_0.jpg │ ├── frame_0.json │ ├── frame_1.jpg │ ├── frame_1.json │ ├── frame_2.jpg │ ├── frame_2.json │ ├── frame_3.jpg │ └── frame_3.json └── webcam ├── capture_webcam.py ├── detect_aruco.py ├── estimate_pose.py ├── sample-data └── calibration.json └── shared.py /.gitignore: -------------------------------------------------------------------------------- 1 | .DS_Store 2 | *.swp 3 | 4 | # Byte-compiled / optimized / DLL files 5 | __pycache__/ 6 | *.py[cod] 7 | *$py.class 8 | 9 | # C extensions 10 | *.so 11 | 12 | # Distribution / packaging 13 | .Python 14 | build/ 15 | develop-eggs/ 16 | dist/ 17 | downloads/ 18 | eggs/ 19 | .eggs/ 20 | lib/ 21 | lib64/ 22 | parts/ 23 | sdist/ 24 | var/ 25 | wheels/ 26 | *.egg-info/ 27 | .installed.cfg 28 | *.egg 29 | MANIFEST 30 | 31 | # PyInstaller 32 | # Usually these files are written by a python script from a template 33 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 34 | *.manifest 35 | *.spec 36 | 37 | # Installer logs 38 | pip-log.txt 39 | pip-delete-this-directory.txt 40 | 41 | # Unit test / coverage reports 42 | htmlcov/ 43 | .tox/ 44 | .coverage 45 | .coverage.* 46 | .cache 47 | nosetests.xml 48 | coverage.xml 49 | *.cover 50 | .hypothesis/ 51 | .pytest_cache/ 52 | 53 | # Translations 54 | *.mo 55 | *.pot 56 | 57 | # Django stuff: 58 | *.log 59 | local_settings.py 60 | db.sqlite3 61 | 62 | # Flask stuff: 63 | instance/ 64 | .webassets-cache 65 | 66 | # Scrapy stuff: 67 | .scrapy 68 | 69 | # Sphinx documentation 70 | docs/_build/ 71 | 72 | # PyBuilder 73 | target/ 74 | 75 | # Jupyter Notebook 76 | .ipynb_checkpoints 77 | 78 | # pyenv 79 | .python-version 80 | 81 | # celery beat schedule file 82 | celerybeat-schedule 83 | 84 | # SageMath parsed files 85 | *.sage.py 86 | 87 | # Environments 88 | .env 89 | .venv 90 | env/ 91 | venv/ 92 | ENV/ 93 | env.bak/ 94 | venv.bak/ 95 | 96 | # Spyder project settings 97 | .spyderproject 98 | .spyproject 99 | 100 | # Rope project settings 101 | .ropeproject 102 | 103 | # mkdocs documentation 104 | /site 105 | 106 | # mypy 107 | .mypy_cache/ 108 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | BSD 3-Clause License 2 | 3 | Copyright (c) 2018, Daniel Saakes 4 | All rights reserved. 5 | 6 | Redistribution and use in source and binary forms, with or without 7 | modification, are permitted provided that the following conditions are met: 8 | 9 | * Redistributions of source code must retain the above copyright notice, this 10 | list of conditions and the following disclaimer. 11 | 12 | * Redistributions in binary form must reproduce the above copyright notice, 13 | this list of conditions and the following disclaimer in the documentation 14 | and/or other materials provided with the distribution. 15 | 16 | * Neither the name of the copyright holder nor the names of its 17 | contributors may be used to endorse or promote products derived from 18 | this software without specific prior written permission. 19 | 20 | THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" 21 | AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE 22 | IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE 23 | DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE 24 | FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL 25 | DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR 26 | SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER 27 | CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, 28 | OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE 29 | OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. 30 | -------------------------------------------------------------------------------- /README.rst: -------------------------------------------------------------------------------- 1 | ------------------------------ 2 | calibrating-with-python-opencv 3 | ------------------------------ 4 | intrinsics, extrinsics, pose estimation examples with KinectV2, Flir and others. All python. 5 | 6 | 7 | .. image:: img/kinect_detection.jpg 8 | :width: 400 9 | :alt: detecting markers with the Kinect -------------------------------------------------------------------------------- /calibration/board.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/daan/calibrating-with-python-opencv/c143ddb341847e540d773f4c7bff8f523842a45f/calibration/board.png -------------------------------------------------------------------------------- /calibration/calibration.json: -------------------------------------------------------------------------------- 1 | { 2 | "calibrationDate": "2018-10-10 10:41:26.877267", 3 | "cameraResolution": { 4 | "type_id": "opencv-matrix", 5 | "rows": 2, 6 | "cols": 1, 7 | "dt": "d", 8 | "data": [ 720.0, 1280.0 ] 9 | }, 10 | "cameraMatrix": { 11 | "type_id": "opencv-matrix", 12 | "rows": 3, 13 | "cols": 3, 14 | "dt": "d", 15 | "data": [ 1.0036890509044972e+03, 0.0, 6.3670897816398144e+02, 16 | 0.0, 1.0036890509044972e+03, 4.1429682375533667e+02, 0.0, 17 | 0.0, 1.0 ] 18 | }, 19 | "dist_coeffs": { 20 | "type_id": "opencv-matrix", 21 | "rows": 14, 22 | "cols": 1, 23 | "dt": "d", 24 | "data": [ -8.5188812484719122e-03, -4.4933351860255627e-01, 25 | 5.7140445300074899e-03, -1.2610711736297426e-03, 26 | 2.6073694779700285e-01, -1.3493827802828759e-01, 27 | 1.0285916634349823e-01, -3.4395347152192784e-01, 0.0, 0.0, 28 | 0.0, 0.0, 0.0, 0.0 ] 29 | } 30 | } 31 | -------------------------------------------------------------------------------- /calibration/openpose/calibration_boards/intrinsics/18284509/capture_0.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/daan/calibrating-with-python-opencv/c143ddb341847e540d773f4c7bff8f523842a45f/calibration/openpose/calibration_boards/intrinsics/18284509/capture_0.jpg -------------------------------------------------------------------------------- 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-0.5417339003942344], [0.15110318416348492, 0.5545789095730688, -0.8182970492384791]]}} -------------------------------------------------------------------------------- /calibration/openpose/captured-data/frame_00_annotated.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/daan/calibrating-with-python-opencv/c143ddb341847e540d773f4c7bff8f523842a45f/calibration/openpose/captured-data/frame_00_annotated.jpg -------------------------------------------------------------------------------- /calibration/openpose/captured-data/frame_01.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/daan/calibrating-with-python-opencv/c143ddb341847e540d773f4c7bff8f523842a45f/calibration/openpose/captured-data/frame_01.jpg -------------------------------------------------------------------------------- /calibration/openpose/captured-data/frame_01.json: -------------------------------------------------------------------------------- 1 | {"pose": {"t": {"x": -0.17509263733713282, "y": 0.18506135463113796, "z": 3.5213673163459887}, "rot3x3": [[0.9586101378459623, -0.051292589791719904, 0.2800636960610992], [0.1141706474557033, -0.8318463116997036, -0.5431360575133501], [0.2608288076085364, 0.5526307844701179, -0.7915601993389075]]}} -------------------------------------------------------------------------------- /calibration/openpose/captured-data/frame_01_annotated.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/daan/calibrating-with-python-opencv/c143ddb341847e540d773f4c7bff8f523842a45f/calibration/openpose/captured-data/frame_01_annotated.jpg -------------------------------------------------------------------------------- /calibration/openpose/captured-data/frame_02.jpg: -------------------------------------------------------------------------------- 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[0.4719265595323651, 0.44286192639697153, -0.7623376132370148]]}} -------------------------------------------------------------------------------- /calibration/openpose/captured-data/frame_03_annotated.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/daan/calibrating-with-python-opencv/c143ddb341847e540d773f4c7bff8f523842a45f/calibration/openpose/captured-data/frame_03_annotated.jpg -------------------------------------------------------------------------------- /calibration/openpose/flir_aruco.py: -------------------------------------------------------------------------------- 1 | import sys 2 | import time 3 | import PySpin 4 | import os 5 | import json 6 | 7 | import numpy as np 8 | import cv2 9 | 10 | import argparse 11 | 12 | 13 | charuco_square_length = 138.0 / 1000 # chessboard square side length (normally in meters) 14 | charuco_marker_length = 87.0 / 1000 # marker side length (same unit than squareLength) 15 | squaresX = 5 16 | squaresY = 7 17 | dictionary = cv2.aruco.getPredefinedDictionary(cv2.aruco.DICT_4X4_250) 18 | board = cv2.aruco.CharucoBoard_create(squaresX,squaresY,charuco_square_length,charuco_marker_length,dictionary) 19 | 20 | 21 | 22 | 23 | # construct the argument parse and parse the arguments 24 | ap = argparse.ArgumentParser() 25 | ap.add_argument("folder", help="folder to save images") 26 | ap.add_argument("-c", "--camera", type=str, default="0", help="use camera by id") 27 | ap.add_argument("-f", "--force", action="store_true", help="force overwrite in folder") 28 | ap.add_argument("--fps", type=int, default=20, help="set framerate") 29 | 30 | args = vars(ap.parse_args()) 31 | 32 | # make folder 33 | target_folder = args['folder'] 34 | if os.path.isdir(target_folder): 35 | if args['force'] == False: 36 | print("{}: error: folder {} exists. Use --force to overwrite files.".format(os.path.basename(sys.argv[0]), target_folder)) 37 | sys.exit() 38 | else: 39 | os.makedirs(target_folder) 40 | 41 | 42 | def set_trigger_mode_software(cam): 43 | cam.TriggerMode.SetValue(PySpin.TriggerMode_Off) 44 | cam.TriggerSource.SetValue(PySpin.TriggerSource_Software) 45 | cam.TriggerMode.SetValue(PySpin.TriggerMode_On) 46 | print("set trigger mode software") 47 | 48 | 49 | def reset_trigger_mode_software(cam): 50 | cam.TriggerMode.SetValue(PySpin.TriggerMode_Off) 51 | print("reset trigger mode") 52 | 53 | 54 | def find_aruco_corners(img, dictionary): 55 | corner_criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 100, 0.00001) 56 | gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) 57 | 58 | corners, ids, rejectedImgPoints = cv2.aruco.detectMarkers(gray, dictionary) 59 | if len(corners)>0: 60 | for corner in corners: 61 | cv2.cornerSubPix(gray, corner, winSize=(3,3), zeroZone=(-1,-1), criteria=corner_criteria) 62 | return corners, ids, rejectedImgPoints 63 | 64 | 65 | def find_charuco_board(img, board, dictionary): 66 | corner_criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 100, 0.00001) 67 | gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) 68 | 69 | corners, ids, rejectedImgPoints = cv2.aruco.detectMarkers(gray, dictionary) 70 | if len(corners)>0: 71 | for corner in corners: 72 | cv2.cornerSubPix(gray, corner, winSize=(3,3), zeroZone=(-1,-1), criteria=corner_criteria) 73 | ret, detectedCorners, detectedIds = cv2.aruco.interpolateCornersCharuco(corners,ids,gray,board) 74 | if detectedCorners is not None and detectedIds is not None and len(detectedCorners)>3: 75 | return detectedCorners, detectedIds 76 | return [], [] 77 | 78 | 79 | 80 | 81 | 82 | 83 | # 84 | # setup 85 | # 86 | 87 | system = PySpin.System.GetInstance() 88 | cam_list = system.GetCameras() 89 | 90 | if cam_list.GetSize() == 0: 91 | print("no cameras found, aborting") 92 | system.ReleaseInstance() 93 | del system 94 | sys.exit() 95 | 96 | cameras = [] 97 | for i in range(cam_list.GetSize()): 98 | cam = cam_list.GetByIndex(i) 99 | print("camera {} serial: {}".format(i, cam.GetUniqueID())) 100 | 101 | 102 | camera_serial = args["camera"] 103 | if camera_serial == "0": 104 | camera_serial = cam_list.GetByIndex(0).GetUniqueID() 105 | print("no camera specified (use -c), using the first one in the list {}".format(camera_serial)) 106 | 107 | 108 | filename = "models/{}.xml".format(camera_serial) 109 | 110 | fs = cv2.FileStorage(filename, cv2.FILE_STORAGE_READ) 111 | 112 | if fs.isOpened() == False: 113 | print("couldn't open camera calibration {} aborting".format(filename)) 114 | sys.exit() 115 | 116 | intrinsics = fs.getNode("Intrinsics").mat() 117 | dist_coeffs = fs.getNode("Distortion").mat() 118 | 119 | fs.release() 120 | 121 | 122 | 123 | 124 | 125 | cam = cam_list.GetBySerial(camera_serial) 126 | 127 | try: 128 | cam.Init() 129 | cam.AcquisitionMode.SetValue(PySpin.AcquisitionMode_Continuous) 130 | set_trigger_mode_software(cam) 131 | cam.BeginAcquisition() 132 | 133 | except: 134 | print("error initializing camera {}".format(camera_serial)) 135 | sys.exit() 136 | 137 | 138 | #os.mkdir(camera_serial) 139 | 140 | def makeRT(rvec, tvec): 141 | rot3x3, _ = cv2.Rodrigues(rvec) 142 | return{"t": { "x":tvec[0][0], "y":tvec[1][0], "z":tvec[2][0] }, "rot3x3" : rot3x3.tolist()} 143 | 144 | def makeMarkersJson(rvecs, tvecs, ids): 145 | ret = [] 146 | for i in range(len(rvecs)): 147 | rot3x3, _ = cv2.Rodrigues(rvecs[i]) 148 | ret.append( {"id": int(ids[i][0]), "t": { "x":tvecs[i][0][0], "y":tvecs[i][0][1], "z":tvecs[i][0][2] }, "rot3x3" : rot3x3.tolist()} ) 149 | return ret 150 | # 151 | # loop 152 | # 153 | 154 | count = 0 155 | 156 | while 1: 157 | key = cv2.waitKey(1) 158 | 159 | 160 | 161 | if key == 27: # ESC 162 | cv2.destroyAllWindows() 163 | break 164 | 165 | cam.TriggerSoftware() 166 | i = cam.GetNextImage() 167 | #print(i.GetWidth(), i.GetHeight(), i.GetBitsPerPixel()) 168 | frame = None 169 | 170 | font = cv2.FONT_HERSHEY_SIMPLEX 171 | 172 | if i.IsIncomplete(): 173 | pass 174 | else: 175 | # see documentation: enum ColorProcessingAlgorithm 176 | image_converted = i.Convert(PySpin.PixelFormat_BGR8, PySpin.DIRECTIONAL_FILTER) 177 | image_data = image_converted.GetData() 178 | frame = np.frombuffer(image_data, dtype=np.uint8) 179 | frame = frame.reshape((i.GetHeight(),i.GetWidth(),3)) 180 | frame_annotated = frame.copy() 181 | 182 | corners, ids = find_charuco_board(frame, board, dictionary) 183 | 184 | valid = False 185 | if len(corners) > 0 and len(ids) > 0: 186 | valid, rvec, tvec = cv2.aruco.estimatePoseCharucoBoard(corners, ids, board, intrinsics, dist_coeffs) 187 | cv2.aruco.drawDetectedCornersCharuco(frame_annotated, corners, ids) 188 | 189 | corners2, ids2, _ = find_aruco_corners(frame, dictionary) 190 | cv2.aruco.drawDetectedMarkers(frame_annotated, corners2, ids2) 191 | rvecs, tvecs, _ = cv2.aruco.estimatePoseSingleMarkers(corners2, charuco_marker_length, intrinsics, dist_coeffs) 192 | for n in range(len(tvecs)): 193 | cv2.aruco.drawAxis(frame_annotated, intrinsics, dist_coeffs, rvecs[n], tvecs[n], 0.1) 194 | 195 | if valid == True: 196 | cv2.aruco.drawAxis(frame_annotated, intrinsics, dist_coeffs, rvec, tvec, 0.2) 197 | 198 | p3d = [tvec[0][0], tvec[1][0], tvec[2][0]] 199 | 200 | # draw the coordinates 201 | cv2.putText(frame_annotated,"{:.3f}".format(p3d[0]), (100,200), font, 4,(0,0,255), 6, cv2.LINE_AA) 202 | cv2.putText(frame_annotated,"{:.3f}".format(p3d[1]), (100,400), font, 4,(0,255,0), 6, cv2.LINE_AA) 203 | cv2.putText(frame_annotated,"{:.3f}".format(p3d[2]), (100,600), font, 4,(255,0,0), 6, cv2.LINE_AA) 204 | 205 | if key == 32: 206 | print("save frame to disc") 207 | cv2.imwrite("{}/frame_{:02}.jpg".format(target_folder, count), frame) 208 | cv2.imwrite("{}/frame_{:02}_annotated.jpg".format(target_folder, count), frame_annotated) 209 | # save the json data 210 | markers = makeMarkersJson(rvecs, tvecs, ids2) 211 | # board 212 | pose = makeRT(rvec, tvec) 213 | filename = "{}/frame_{:02}.json".format(target_folder, count) 214 | with open(filename, "w") as write_file: 215 | json.dump( { "pose": pose, "markers" : markers }, write_file) 216 | count += 1 217 | cv2.imshow("cam1",frame_annotated) 218 | i.Release() 219 | del i 220 | 221 | # 222 | # cleanup 223 | # 224 | 225 | cam.EndAcquisition() 226 | reset_trigger_mode_software(cam) 227 | cam.DeInit() 228 | del cam 229 | del cam_list 230 | 231 | system.ReleaseInstance() 232 | del system -------------------------------------------------------------------------------- /calibration/openpose/models/18284509.xml: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 3 5 | 4 6 |
d
7 | 8 | 1. 0. 0. 0. 0. 1. 0. 0. 0. 0. 1. 0. 9 | 10 | 3 11 | 3 12 |
d
13 | 14 | 1.6062015380859375e+03 0. 6.3332989501953125e+02 0. 15 | 1.6014158935546875e+03 5.1715637207031250e+02 0. 0. 1. 16 | 17 | 4 18 | 1 19 |
d
20 | 21 | -3.8691338896751404e-01 1.8264715373516083e-01 22 | 5.0779170123860240e-04 7.0454436354339123e-04 23 | 24 | -------------------------------------------------------------------------------- /calibration/openpose/models/18284511.xml: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 3 5 | 4 6 |
d
7 | 8 | 8.6182423177752765e-01 9.2365614963480780e-02 9 | -4.9872596352455129e-01 1.4962586538184854e+00 10 | -1.3722739884753807e-01 9.8906887675602162e-01 11 | -5.3957372416754107e-02 -2.1298977473255817e-01 12 | 4.8829052266720557e-01 1.1494063774400942e-01 8.6507861796971230e-01 13 | 1.8544227437140977e+00 14 | 15 | 3 16 | 3 17 |
d
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0.916336334648947}}} -------------------------------------------------------------------------------- /calibration/sample-data/calibration.json: -------------------------------------------------------------------------------- 1 | { 2 | "calibrationDate": "2018-10-08 15:32:40.781436", 3 | "cameraResolution": { 4 | "type_id": "opencv-matrix", 5 | "rows": 2, 6 | "cols": 1, 7 | "dt": "d", 8 | "data": [ 720.0, 1280.0 ] 9 | }, 10 | "cameraMatrix": { 11 | "type_id": "opencv-matrix", 12 | "rows": 3, 13 | "cols": 3, 14 | "dt": "d", 15 | "data": [ 1.0036890509044972e+03, 0.0, 6.3670897816398144e+02, 16 | 0.0, 1.0036890509044972e+03, 4.1429682375533667e+02, 0.0, 17 | 0.0, 1.0 ] 18 | }, 19 | "dist_coeffs": { 20 | "type_id": "opencv-matrix", 21 | "rows": 14, 22 | "cols": 1, 23 | "dt": "d", 24 | "data": [ -8.5188812484719122e-03, -4.4933351860255627e-01, 25 | 5.7140445300074899e-03, -1.2610711736297426e-03, 26 | 2.6073694779700285e-01, -1.3493827802828759e-01, 27 | 1.0285916634349823e-01, 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-------------------------------------------------------------------------------- /data/ChAruCo 11x8, 300dpi, 50mm spacing, 30mm markers.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/daan/calibrating-with-python-opencv/c143ddb341847e540d773f4c7bff8f523842a45f/data/ChAruCo 11x8, 300dpi, 50mm spacing, 30mm markers.pdf -------------------------------------------------------------------------------- /data/board.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/daan/calibrating-with-python-opencv/c143ddb341847e540d773f4c7bff8f523842a45f/data/board.pdf -------------------------------------------------------------------------------- /flir/README.rst: -------------------------------------------------------------------------------- 1 | Find Chessboards with Flir cameras 2 | ================================== 3 | 4 | Installation 5 | ------------ 6 | Install python opencv and contrib and pyspinnaker from Flir/PTGrey. 7 | 8 | 9 | 10 | 11 | -------------------------------------------------------------------------------- /flir/common.py: -------------------------------------------------------------------------------- 1 | import sys 2 | import time 3 | import PySpin 4 | import os 5 | 6 | import numpy as np 7 | import cv2 8 | 9 | 10 | import argparse 11 | 12 | # construct the argument parse and parse the arguments 13 | ap = argparse.ArgumentParser() 14 | ap.add_argument("-c", "--camera", type=str, default="0", help="camera by id") 15 | 16 | args = vars(ap.parse_args()) 17 | 18 | def set_trigger_mode_software(cam): 19 | cam.TriggerMode.SetValue(PySpin.TriggerMode_Off) 20 | cam.TriggerSource.SetValue(PySpin.TriggerSource_Software) 21 | cam.TriggerMode.SetValue(PySpin.TriggerMode_On) 22 | print("set trigger mode software") 23 | 24 | 25 | def reset_trigger_mode_software(cam): 26 | cam.TriggerMode.SetValue(PySpin.TriggerMode_Off) 27 | print("reset trigger mode") 28 | 29 | 30 | # 31 | # setup 32 | # 33 | 34 | system = PySpin.System.GetInstance() 35 | cam_list = system.GetCameras() 36 | 37 | if cam_list.GetSize() == 0: 38 | print("no cameras found, aborting") 39 | system.ReleaseInstance() 40 | del system 41 | sys.exit() 42 | 43 | cameras = [] 44 | for i in range(cam_list.GetSize()): 45 | cam = cam_list.GetByIndex(i) 46 | print("camera {} serial: {}".format(i, cam.GetUniqueID())) 47 | 48 | 49 | camera_serial = args["camera"] 50 | if camera_serial == "0": 51 | camera_serial = cam_list.GetByIndex(0).GetUniqueID() 52 | print("no camera specified (use -c), using the first one in the list {}".format(camera_serial)) 53 | 54 | 55 | cam = cam_list.GetBySerial(camera_serial) 56 | 57 | try: 58 | cam.Init() 59 | cam.AcquisitionMode.SetValue(PySpin.AcquisitionMode_Continuous) 60 | set_trigger_mode_software(cam) 61 | cam.BeginAcquisition() 62 | 63 | except: 64 | print("error initializing camera {}".format(camera_serial)) 65 | sys.exit() 66 | 67 | 68 | os.mkdir(camera_serial) 69 | 70 | 71 | 72 | # 73 | # loop 74 | # 75 | 76 | count = 0 77 | 78 | while 1: 79 | key = cv2.waitKey(1) 80 | 81 | 82 | 83 | if key == 27: # ESC 84 | cv2.destroyAllWindows() 85 | break 86 | 87 | cam.TriggerSoftware() 88 | i = cam.GetNextImage() 89 | #print(i.GetWidth(), i.GetHeight(), i.GetBitsPerPixel()) 90 | cvi = None 91 | 92 | if i.IsIncomplete(): 93 | pass 94 | else: 95 | # see documentation: enum ColorProcessingAlgorithm 96 | image_converted = i.Convert(PySpin.PixelFormat_BGR8, PySpin.DIRECTIONAL_FILTER) 97 | image_data = image_converted.GetData() 98 | cvi = np.frombuffer(image_data, dtype=np.uint8) 99 | cvi = cvi.reshape((i.GetHeight(),i.GetWidth(),3)) 100 | cv2.imshow("cam1",cvi) 101 | i.Release() 102 | del i 103 | 104 | if key == 32: 105 | cv2.imwrite("{}/capture_{}.jpg".format(camera_serial,count), cvi) 106 | count+= 1 107 | print("saved image {}".format(count)) 108 | # 109 | # cleanup 110 | # 111 | 112 | cam.EndAcquisition() 113 | reset_trigger_mode_software(cam) 114 | cam.DeInit() 115 | del cam 116 | del cam_list 117 | 118 | system.ReleaseInstance() 119 | del system -------------------------------------------------------------------------------- /flir/flir_capture.py: -------------------------------------------------------------------------------- 1 | import sys 2 | import time 3 | import PySpin 4 | 5 | import numpy as np 6 | import cv2 7 | 8 | 9 | 10 | def set_trigger_mode_software(cam): 11 | cam.TriggerMode.SetValue(PySpin.TriggerMode_Off) 12 | cam.TriggerSource.SetValue(PySpin.TriggerSource_Software) 13 | cam.TriggerMode.SetValue(PySpin.TriggerMode_On) 14 | print("set trigger mode software") 15 | 16 | 17 | def reset_trigger_mode_software(cam): 18 | cam.TriggerMode.SetValue(PySpin.TriggerMode_Off) 19 | print("reset trigger mode") 20 | 21 | 22 | # 23 | # setup 24 | # 25 | 26 | system = PySpin.System.GetInstance() 27 | cam_list = system.GetCameras() 28 | 29 | print("number of cameras {}".format(cam_list.GetSize())) 30 | 31 | if cam_list.GetSize() == 0: 32 | print("no cameras found, aborting") 33 | system.ReleaseInstance() 34 | del system 35 | sys.exit() 36 | 37 | cameras = [] 38 | for i in range(cam_list.GetSize()): 39 | cam = cam_list.GetByIndex(i) 40 | print("camera {} serial: {}".format(i, cam.GetUniqueID())) 41 | cam.Init() 42 | cam.AcquisitionMode.SetValue(PySpin.AcquisitionMode_Continuous) 43 | set_trigger_mode_software(cam) 44 | cam.BeginAcquisition() 45 | cameras.append(cam) 46 | 47 | 48 | # 49 | # loop 50 | # 51 | 52 | count = 0 53 | 54 | while 1: 55 | 56 | if cv2.waitKey(1) == 27: # ESC 57 | cv2.destroyAllWindows() 58 | break 59 | 60 | for cam in cameras: 61 | cam.TriggerSoftware() 62 | i = cam.GetNextImage() 63 | #print(i.GetWidth(), i.GetHeight(), i.GetBitsPerPixel()) 64 | 65 | if i.IsIncomplete(): 66 | pass 67 | else: 68 | # see documentation: enum ColorProcessingAlgorithm 69 | image_converted = i.Convert(PySpin.PixelFormat_BGR8, PySpin.DIRECTIONAL_FILTER) 70 | image_data = image_converted.GetData() 71 | cvi = np.frombuffer(image_data, dtype=np.uint8) 72 | cvi = cvi.reshape((i.GetHeight(),i.GetWidth(),3)) 73 | print(cvi.shape) 74 | cv2.imshow("cam1",cvi) 75 | i.Release() 76 | del i 77 | 78 | # 79 | # cleanup 80 | # 81 | 82 | for cam in cameras: 83 | cam.EndAcquisition() 84 | reset_trigger_mode_software(cam) 85 | cam.DeInit() 86 | del cam 87 | del cameras 88 | del cam_list 89 | 90 | system.ReleaseInstance() 91 | del system -------------------------------------------------------------------------------- /flir/flir_capture_all_continuous.py: -------------------------------------------------------------------------------- 1 | import sys 2 | import time 3 | import PySpin 4 | import os 5 | 6 | import numpy as np 7 | import cv2 8 | 9 | from queue import Queue 10 | import threading 11 | 12 | import argparse 13 | 14 | # construct the argument parse and parse the arguments 15 | ap = argparse.ArgumentParser() 16 | ap.add_argument("folder", help="folder to save images") 17 | ap.add_argument("-m", "--master", type=str, default="18284509", help="master camera by id") 18 | ap.add_argument("-f", "--force", action="store_true", help="force overwrite in folder") 19 | ap.add_argument("--fps", type=int, default=20, help="set framerate") 20 | 21 | ap.add_argument("--openpose", action="store_true", help="name images for openpose (e.g. 000000000000_rendered, ..._1, ..._2, ...)") 22 | 23 | args = vars(ap.parse_args()) 24 | 25 | save_for_openpose = args['openpose'] 26 | 27 | fps = args["fps"] 28 | 29 | # make folder 30 | target_folder = args['folder'] 31 | if os.path.isdir(target_folder): 32 | if not args['force']: 33 | print("{}: error: folder {} exists. Use --force to overwrite files.".format(os.path.basename(sys.argv[0]), target_folder)) 34 | sys.exit() 35 | else: 36 | os.makedirs(target_folder) 37 | 38 | 39 | 40 | def set_fps(cam, fps): 41 | print("current acquisitionFrameRate", cam.AcquisitionFrameRate.GetValue() ) 42 | cam.AcquisitionFrameRateEnable.SetValue(True) 43 | print("acquisitionFrameRate Enable", cam.AcquisitionFrameRateEnable.GetValue() ) 44 | cam.AcquisitionFrameRate.SetValue(fps) 45 | print("acquisitionFrameRate set to", cam.AcquisitionFrameRate.GetValue() ) 46 | 47 | def set_trigger_mode(cam, triggerSource): 48 | cam.TriggerMode.SetValue(PySpin.TriggerMode_Off) 49 | cam.TriggerSource.SetValue(triggerSource) 50 | cam.TriggerMode.SetValue(PySpin.TriggerMode_On) 51 | 52 | def reset_trigger_mode_software(cam): 53 | cam.TriggerMode.SetValue(PySpin.TriggerMode_Off) 54 | print("reset trigger mode") 55 | 56 | 57 | def reset_trigger_mode_software(cam): 58 | cam.TriggerMode.SetValue(PySpin.TriggerMode_Off) 59 | print("reset trigger mode") 60 | 61 | 62 | # 63 | # setup 64 | # 65 | master_id = args["master"] 66 | master = None 67 | 68 | 69 | system = PySpin.System.GetInstance() 70 | cam_list = system.GetCameras() 71 | 72 | if cam_list.GetSize() == 0: 73 | print("no cameras found, aborting") 74 | system.ReleaseInstance() 75 | del system 76 | sys.exit() 77 | 78 | for i in range(cam_list.GetSize()): 79 | cam = cam_list.GetByIndex(i) 80 | print("camera {} serial: {}".format(i, cam.GetUniqueID())) 81 | 82 | 83 | 84 | cameras = [] 85 | for i in range(cam_list.GetSize()): 86 | try: 87 | cam = cam_list.GetByIndex(i) 88 | cam_id = cam.GetUniqueID() 89 | cam.Init() 90 | 91 | if cam_id == master_id: 92 | print("master: {}".format(cam_id)) 93 | master = cam 94 | #set_trigger_mode(cam, PySpin.TriggerSource_Software) 95 | set_fps(cam, fps) 96 | else: 97 | print("follower: {}".format(cam_id)) 98 | set_trigger_mode(cam, PySpin.TriggerSource_Line3) 99 | 100 | cam.AcquisitionMode.SetValue(PySpin.AcquisitionMode_Continuous) 101 | cam.BeginAcquisition() 102 | cameras.append(cam) 103 | except PySpin.SpinnakerException as ex: 104 | print("Error: {}".format(ex)) 105 | sys.exit() 106 | 107 | 108 | class ImageWorker(threading.Thread): 109 | def __init__(self): 110 | super(ImageWorker, self).__init__() 111 | self.images = Queue() 112 | self._stop_event = threading.Event() 113 | 114 | def addImage(self, img): 115 | self.images.put(img) 116 | def stop(self): 117 | self._stop_event.set() 118 | def stopped(self): 119 | return self._stop_event.is_set() 120 | def run(self): 121 | print("run") 122 | while(1): 123 | if self.images.empty(): 124 | if self.stopped(): 125 | break 126 | else: 127 | time.sleep(0.10) 128 | else: 129 | item = self.images.get() 130 | 131 | if item != None: 132 | filename, i = item 133 | 134 | #i.save(filename) 135 | 136 | image_converted = i.Convert(PySpin.PixelFormat_BGR8, PySpin.DIRECTIONAL_FILTER) 137 | 138 | #writing with spinaker 139 | 140 | image_converted.Save(filename) 141 | 142 | #writing with opencv 143 | 144 | #image_data = image_converted.GetData() 145 | #cvi = np.frombuffer(image_data, dtype=np.uint8) 146 | #cvi = cvi.reshape((i.GetHeight(),i.GetWidth(),3)) 147 | #cv2.imwrite(filename, cvi) 148 | 149 | 150 | 151 | 152 | # 153 | # loop 154 | # 155 | 156 | count = 0 157 | 158 | 159 | 160 | worker = ImageWorker() 161 | worker.start() 162 | 163 | 164 | images = [None, None, None] 165 | 166 | fps_report_frequency = fps*2 167 | start_time = time.time() 168 | 169 | try: 170 | while 1: 171 | if cv2.waitKey(1) != -1: 172 | break 173 | 174 | if count % fps_report_frequency == 0: 175 | fps = fps_report_frequency / (time.time() - start_time) # / fps_report_frequency 176 | print("fps {:.3f} image count {}, in buffer {}".format(fps, count,worker.images.qsize() )) 177 | start_time = time.time() 178 | 179 | 180 | 181 | for n in range(len(cameras)): 182 | cam = cameras[n] 183 | try: 184 | # milliseconds. 185 | try: 186 | if n == 0: 187 | i = cam.GetNextImage() 188 | else: 189 | i = cam.GetNextImage(20) 190 | #print(i.GetWidth(), i.GetHeight(), i.GetBitsPerPixel()) 191 | except PySpin.SpinnakerException as ex: 192 | print("none") 193 | continue 194 | 195 | if i.IsIncomplete(): 196 | print("incomplete") 197 | pass 198 | else: 199 | if n == 0: 200 | print("new frame") 201 | count += 1 202 | images = [None, None, None] 203 | 204 | print(n, time.time() ) 205 | 206 | cam_id = cam.GetUniqueID() 207 | 208 | if save_for_openpose: 209 | if n == 0: 210 | filename = "{}/{:012}_rendered.jpg".format(target_folder, count) 211 | else: 212 | filename = "{}/{:012}_rendered_{}.jpg".format(target_folder, count, n) 213 | else: 214 | filename = "{}/cam_{}__{:06}.jpg".format(target_folder, cam_id, count) 215 | #print(filename, count[n], cam_id) 216 | 217 | images[n] = (filename, i) 218 | #worker.addImage( (filename, i) ) 219 | 220 | 221 | i.Release() 222 | del i 223 | except PySpin.SpinnakerException as ex: 224 | print("Error: {}".format(ex)) 225 | # after a capture round of all cameras. 226 | if (images[0] is not None) and (images[1] is not None) and (images[2] is not None): 227 | print("got three images") 228 | worker.addImage( images[0]) 229 | worker.addImage( images[1]) 230 | worker.addImage( images[2]) 231 | 232 | 233 | 234 | except KeyboardInterrupt: 235 | pass 236 | # 237 | # cleanup 238 | # 239 | 240 | worker.stop() 241 | 242 | while(1): 243 | 244 | print("{} images to be processed. waiting for thread to finish".format(worker.images.qsize())) 245 | time.sleep(0.5) 246 | 247 | done = True 248 | if worker.images.empty(): 249 | break 250 | 251 | 252 | master = None 253 | 254 | for cam in cameras: 255 | cam.EndAcquisition() 256 | reset_trigger_mode_software(cam) 257 | cam.DeInit() 258 | del cam 259 | 260 | del cameras 261 | del cam_list 262 | 263 | system.ReleaseInstance() 264 | del system 265 | -------------------------------------------------------------------------------- /flir/flir_capture_multiple.py: -------------------------------------------------------------------------------- 1 | import sys 2 | import time 3 | import PySpin 4 | 5 | import numpy as np 6 | import cv2 7 | 8 | def set_trigger_mode(cam, triggerSource): 9 | cam.TriggerMode.SetValue(PySpin.TriggerMode_Off) 10 | cam.TriggerSource.SetValue(triggerSource) 11 | cam.TriggerMode.SetValue(PySpin.TriggerMode_On) 12 | 13 | def reset_trigger_mode_software(cam): 14 | cam.TriggerMode.SetValue(PySpin.TriggerMode_Off) 15 | print("reset trigger mode") 16 | 17 | 18 | # 19 | # setup 20 | # 21 | 22 | system = PySpin.System.GetInstance() 23 | cam_list = system.GetCameras() 24 | 25 | master_id = "18284509" 26 | master = None 27 | 28 | print("number of cameras {}".format(cam_list.GetSize())) 29 | 30 | 31 | if cam_list.GetSize() == 0: 32 | print("no cameras found, aborting") 33 | system.ReleaseInstance() 34 | del system 35 | sys.exit() 36 | 37 | cameras = [] 38 | for i in range(cam_list.GetSize()): 39 | try: 40 | cam = cam_list.GetByIndex(i) 41 | cam_id = cam.GetUniqueID() 42 | cam.Init() 43 | 44 | 45 | if cam_id == master_id: 46 | print("master: {}".format(cam_id)) 47 | master = cam 48 | set_trigger_mode(cam, PySpin.TriggerSource_Software) 49 | else: 50 | print("follower: {}".format(cam_id)) 51 | set_trigger_mode(cam, PySpin.TriggerSource_Line3) 52 | cam.AcquisitionMode.SetValue(PySpin.AcquisitionMode_Continuous) 53 | cam.BeginAcquisition() 54 | cameras.append(cam) 55 | except PySpin.SpinnakerException as ex: 56 | print("Error: {}".format(ex)) 57 | 58 | 59 | # 60 | # loop 61 | # 62 | 63 | 64 | count = 0 65 | size = 4 66 | frame = {} 67 | 68 | camera_dict = { "18284509": "", "18284511": "_1", "18284512": "_2"} 69 | 70 | print("start loop") 71 | 72 | while 1: 73 | 74 | key = cv2.waitKey(1) 75 | 76 | if key == 27: # ESC 77 | cv2.destroyAllWindows() 78 | break 79 | elif key == 32: # SPACE 80 | print("take picture") 81 | for key, value in frame.items(): 82 | cv2.imwrite("frame_{:012}{}.jpg".format(count,camera_dict[key]), value) 83 | count = count + 1 84 | 85 | try: 86 | master.TriggerSoftware.Execute() 87 | except PySpin.SpinnakerException as ex: 88 | print("Error: {}".format(ex)) 89 | 90 | for cam in cameras: 91 | try: 92 | i = cam.GetNextImage() 93 | #print(i.GetWidth(), i.GetHeight(), i.GetBitsPerPixel()) 94 | 95 | if i.IsIncomplete(): 96 | pass 97 | else: 98 | cam_id = cam.GetUniqueID() 99 | # see documentation: enum ColorProcessingAlgorithm 100 | image_converted = i.Convert(PySpin.PixelFormat_BGR8, PySpin.DIRECTIONAL_FILTER) 101 | image_data = image_converted.GetData() 102 | cvi = np.frombuffer(image_data, dtype=np.uint8) 103 | cvi = cvi.reshape((i.GetHeight(),i.GetWidth(),3)) 104 | frame[cam_id] = cvi 105 | 106 | res = cv2.resize(cvi, (int(1280/size),int(1024/size))) 107 | cv2.imshow("cam{}".format(cam_id),res) 108 | i.Release() 109 | del i 110 | except PySpin.SpinnakerException as ex: 111 | print("Error: {}".format(ex)) 112 | 113 | # 114 | # cleanup 115 | # 116 | 117 | del master 118 | for cam in cameras: 119 | cam.EndAcquisition() 120 | reset_trigger_mode_software(cam) 121 | cam.DeInit() 122 | del cam 123 | del cameras 124 | del cam_list 125 | 126 | system.ReleaseInstance() 127 | del system -------------------------------------------------------------------------------- /flir/flir_capture_multiple_video.py: -------------------------------------------------------------------------------- 1 | import sys 2 | import time 3 | import PySpin 4 | 5 | import numpy as np 6 | import cv2 7 | 8 | import SaveToAvi 9 | 10 | def set_trigger_mode(cam, triggerSource): 11 | cam.TriggerMode.SetValue(PySpin.TriggerMode_Off) 12 | cam.TriggerSource.SetValue(triggerSource) 13 | cam.TriggerMode.SetValue(PySpin.TriggerMode_On) 14 | 15 | def reset_trigger_mode_software(cam): 16 | cam.TriggerMode.SetValue(PySpin.TriggerMode_Off) 17 | print("reset trigger mode") 18 | 19 | def mode_status(): 20 | if sw_vid: 21 | print("record video") 22 | elif not sw_vid: 23 | if sw_con: 24 | print("record continuous photo") 25 | else: 26 | print("record single photo") 27 | 28 | # 29 | # setup 30 | # 31 | 32 | system = PySpin.System.GetInstance() 33 | cam_list = system.GetCameras() 34 | 35 | master_id = "18284509" 36 | master = None 37 | 38 | print("number of cameras {}".format(cam_list.GetSize())) 39 | 40 | 41 | if cam_list.GetSize() == 0: 42 | print("no cameras found, aborting") 43 | system.ReleaseInstance() 44 | del system 45 | sys.exit() 46 | 47 | cameras = [] 48 | for i in range(cam_list.GetSize()): 49 | try: 50 | cam = cam_list.GetByIndex(i) 51 | cam_id = cam.GetUniqueID() 52 | cam.Init() 53 | 54 | 55 | if cam_id == master_id: 56 | print("master: {}".format(cam_id)) 57 | master = cam 58 | set_trigger_mode(cam, PySpin.TriggerSource_Software) 59 | else: 60 | print("follower: {}".format(cam_id)) 61 | set_trigger_mode(cam, PySpin.TriggerSource_Line3) 62 | cam.AcquisitionMode.SetValue(PySpin.AcquisitionMode_Continuous) 63 | cam.BeginAcquisition() 64 | cameras.append(cam) 65 | except PySpin.SpinnakerException as ex: 66 | print("Error: {}".format(ex)) 67 | 68 | 69 | # 70 | # loop 71 | # 72 | 73 | 74 | count = 0 75 | sw_rec = False 76 | sw_con = False 77 | sw_vid = False 78 | size = 4 79 | frame = {} 80 | 81 | from path import Path 82 | directory = Path("./") 83 | 84 | 85 | camera_dict = { "18284509": "", "18284511": "_1", "18284512": "_2"} 86 | 87 | print("start loop") 88 | 89 | while 1: 90 | 91 | key = cv2.waitKey(1) 92 | 93 | if key == 27: # ESC 94 | cv2.destroyAllWindows() 95 | break 96 | elif key == 32: # SPACE 97 | if sw_con: 98 | sw_rec = not sw_rec 99 | if sw_rec: 100 | print("start recording") 101 | elif not sw_rec: 102 | print("finish recording") 103 | elif not sw_vid: 104 | print("take picture:{}".format(count)) 105 | for key, value in frame.items(): 106 | cv2.imwrite("frame_{:012}{}.jpg".format(count,camera_dict[key]), value) 107 | count = count + 1 108 | elif key == 99: # C 109 | sw_con = not sw_con 110 | mode_status() 111 | elif key == 114: # R 112 | count = 0 113 | print("reset count") 114 | files = directory.walkfiles("*.jpg") 115 | files = directory.walkfiles("*.avi") 116 | for file in files: 117 | file.remove() 118 | print("reset .jpg .avi") 119 | elif key == 118: # V 120 | sw_vid = not sw_vid 121 | mode_status() 122 | 123 | try: 124 | master.TriggerSoftware.Execute() 125 | except PySpin.SpinnakerException as ex: 126 | print("Error: {}".format(ex)) 127 | 128 | for cam in cameras: 129 | try: 130 | i = cam.GetNextImage() 131 | #print(i.GetWidth(), i.GetHeight(), i.GetBitsPerPixel()) 132 | 133 | if i.IsIncomplete(): 134 | pass 135 | else: 136 | cam_id = cam.GetUniqueID() 137 | # see documentation: enum ColorProcessingAlgorithm 138 | image_converted = i.Convert(PySpin.PixelFormat_BGR8, PySpin.DIRECTIONAL_FILTER) 139 | image_data = image_converted.GetData() 140 | cvi = np.frombuffer(image_data, dtype=np.uint8) 141 | cvi = cvi.reshape((i.GetHeight(),i.GetWidth(),3)) 142 | frame[cam_id] = cvi 143 | 144 | if sw_vid: 145 | print("recording video") 146 | #.............................................. 147 | 148 | if not sw_rec: 149 | res = cv2.resize(cvi, (int(1280/size),int(1024/size))) 150 | cv2.imshow("cam{}".format(cam_id),res) 151 | 152 | if sw_rec: 153 | if not sw_vid: 154 | print("take picture:{}".format(count)) 155 | for key, value in frame.items(): 156 | cv2.imwrite("frame_{:012}{}.jpg".format(count,camera_dict[key]), value) 157 | count = count + 1 158 | i.Release() 159 | del i 160 | except PySpin.SpinnakerException as ex: 161 | print("Error: {}".format(ex)) 162 | 163 | # 164 | # cleanup 165 | # 166 | 167 | del master 168 | for cam in cameras: 169 | cam.EndAcquisition() 170 | reset_trigger_mode_software(cam) 171 | cam.DeInit() 172 | del cam 173 | del cameras 174 | del cam_list 175 | 176 | system.ReleaseInstance() 177 | del system -------------------------------------------------------------------------------- /flir/flir_capture_single.py: -------------------------------------------------------------------------------- 1 | import sys 2 | import time 3 | import PySpin 4 | import os 5 | 6 | import numpy as np 7 | import cv2 8 | 9 | 10 | import argparse 11 | 12 | # construct the argument parse and parse the arguments 13 | ap = argparse.ArgumentParser() 14 | ap.add_argument("-c", "--camera", type=str, default="0", help="camera by id") 15 | 16 | args = vars(ap.parse_args()) 17 | 18 | def set_trigger_mode_software(cam): 19 | cam.TriggerMode.SetValue(PySpin.TriggerMode_Off) 20 | cam.TriggerSource.SetValue(PySpin.TriggerSource_Software) 21 | cam.TriggerMode.SetValue(PySpin.TriggerMode_On) 22 | print("set trigger mode software") 23 | 24 | 25 | def reset_trigger_mode_software(cam): 26 | cam.TriggerMode.SetValue(PySpin.TriggerMode_Off) 27 | print("reset trigger mode") 28 | 29 | 30 | # 31 | # setup 32 | # 33 | 34 | system = PySpin.System.GetInstance() 35 | cam_list = system.GetCameras() 36 | 37 | if cam_list.GetSize() == 0: 38 | print("no cameras found, aborting") 39 | system.ReleaseInstance() 40 | del system 41 | sys.exit() 42 | 43 | cameras = [] 44 | for i in range(cam_list.GetSize()): 45 | cam = cam_list.GetByIndex(i) 46 | print("camera {} serial: {}".format(i, cam.GetUniqueID())) 47 | 48 | 49 | 50 | camera_serial = args["camera"] 51 | if camera_serial == "0": 52 | camera_serial = cam_list.GetByIndex(0).GetUniqueID() 53 | print("no camera specified (use -c), using the first one in the list {}".format(camera_serial)) 54 | 55 | 56 | cam = cam_list.GetBySerial(camera_serial) 57 | 58 | try: 59 | cam.Init() 60 | cam.AcquisitionMode.SetValue(PySpin.AcquisitionMode_Continuous) 61 | set_trigger_mode_software(cam) 62 | cam.BeginAcquisition() 63 | 64 | except: 65 | print("error initializing camera {}".format(camera_serial)) 66 | sys.exit() 67 | 68 | 69 | os.mkdir(camera_serial) 70 | 71 | 72 | 73 | # 74 | # loop 75 | # 76 | 77 | count = 0 78 | 79 | while 1: 80 | key = cv2.waitKey(1) 81 | 82 | 83 | 84 | if key == 27: # ESC 85 | cv2.destroyAllWindows() 86 | break 87 | 88 | #cam.TriggerSoftware() 89 | i = cam.GetNextImage() 90 | print(count) 91 | #print(i.GetWidth(), i.GetHeight(), i.GetBitsPerPixel()) 92 | cvi = None 93 | 94 | if i.IsIncomplete(): 95 | pass 96 | else: 97 | # see documentation: enum ColorProcessingAlgorithm 98 | image_converted = i.Convert(PySpin.PixelFormat_BGR8, PySpin.DIRECTIONAL_FILTER) 99 | image_data = image_converted.GetData() 100 | cvi = np.frombuffer(image_data, dtype=np.uint8) 101 | cvi = cvi.reshape((i.GetHeight(),i.GetWidth(),3)) 102 | cv2.imshow("cam1",cvi) 103 | i.Release() 104 | del i 105 | 106 | if key == 32: 107 | cv2.imwrite("{}/capture_{}.jpg".format(camera_serial,count), cvi) 108 | count+= 1 109 | print("saved image {}".format(count)) 110 | # 111 | # cleanup 112 | # 113 | 114 | cam.EndAcquisition() 115 | reset_trigger_mode_software(cam) 116 | cam.DeInit() 117 | del cam 118 | del cam_list 119 | 120 | system.ReleaseInstance() 121 | del system -------------------------------------------------------------------------------- /flir/flir_capture_single_continuous.py: -------------------------------------------------------------------------------- 1 | import sys 2 | import time 3 | import PySpin 4 | import os 5 | 6 | import numpy as np 7 | import cv2 8 | 9 | from queue import Queue 10 | import threading 11 | 12 | import argparse 13 | 14 | # construct the argument parse and parse the arguments 15 | ap = argparse.ArgumentParser() 16 | ap.add_argument("folder", help="folder to save images") 17 | ap.add_argument("-c", "--camera", type=str, default="0", help="use camera by id") 18 | ap.add_argument("-f", "--force", action="store_true", help="force overwrite in folder") 19 | ap.add_argument("--fps", type=int, default=20, help="set framerate in Hertz") 20 | 21 | args = vars(ap.parse_args()) 22 | 23 | fps = args["fps"] 24 | 25 | 26 | 27 | # make folder 28 | target_folder = args['folder'] 29 | if os.path.isdir(target_folder): 30 | if args['force'] == False: 31 | print("{}: error: folder {} exists. Use --force to overwrite files.".format(os.path.basename(sys.argv[0]), target_folder)) 32 | sys.exit() 33 | else: 34 | os.makedirs(target_folder) 35 | 36 | def set_fps(cam, fps): 37 | print("current acquisitionFrameRate", cam.AcquisitionFrameRate.GetValue() ) 38 | cam.AcquisitionFrameRateEnable.SetValue(True) 39 | print("acquisitionFrameRate Enable", cam.AcquisitionFrameRateEnable.GetValue() ) 40 | cam.AcquisitionFrameRate.SetValue(fps) 41 | print("acquisitionFrameRate set to", cam.AcquisitionFrameRate.GetValue() ) 42 | 43 | 44 | def set_trigger_mode_software(cam): 45 | cam.TriggerMode.SetValue(PySpin.TriggerMode_Off) 46 | cam.TriggerSource.SetValue(PySpin.TriggerSource_Software) 47 | cam.TriggerMode.SetValue(PySpin.TriggerMode_On) 48 | print("set trigger mode software") 49 | 50 | 51 | def reset_trigger_mode_software(cam): 52 | cam.TriggerMode.SetValue(PySpin.TriggerMode_Off) 53 | print("reset trigger mode") 54 | 55 | 56 | # 57 | # setup 58 | # 59 | 60 | system = PySpin.System.GetInstance() 61 | cam_list = system.GetCameras() 62 | 63 | if cam_list.GetSize() == 0: 64 | print("no cameras found, aborting") 65 | system.ReleaseInstance() 66 | del system 67 | sys.exit() 68 | 69 | cameras = [] 70 | for i in range(cam_list.GetSize()): 71 | cam = cam_list.GetByIndex(i) 72 | print("camera {} serial: {}".format(i, cam.GetUniqueID())) 73 | 74 | 75 | camera_serial = args["camera"] 76 | if camera_serial == "0": 77 | camera_serial = cam_list.GetByIndex(0).GetUniqueID() 78 | print("no camera specified (use -c). Using the first one in the list {}".format(camera_serial)) 79 | 80 | 81 | cam = cam_list.GetBySerial(camera_serial) 82 | 83 | try: 84 | cam.Init() 85 | cam.AcquisitionMode.SetValue(PySpin.AcquisitionMode_Continuous) 86 | 87 | # we now disable the trigger mode and let the camera capture at fps 88 | # set_trigger_mode_software(cam) 89 | reset_trigger_mode_software(cam) 90 | set_fps(cam, fps) 91 | 92 | cam.BeginAcquisition() 93 | 94 | except: 95 | print("error initializing camera {}".format(camera_serial)) 96 | sys.exit() 97 | 98 | 99 | 100 | print("saving images to folder {}".format(target_folder)) 101 | print("stop recording using ctr-c") 102 | 103 | 104 | 105 | class ImageWorker(threading.Thread): 106 | def __init__(self): 107 | super(ImageWorker, self).__init__() 108 | self.images = Queue() 109 | self._stop_event = threading.Event() 110 | 111 | def addImage(self, img): 112 | self.images.put(img) 113 | def stop(self): 114 | self._stop_event.set() 115 | def stopped(self): 116 | return self._stop_event.is_set() 117 | def run(self): 118 | print("run") 119 | while(1): 120 | if self.images.empty(): 121 | if self.stopped(): 122 | break 123 | else: 124 | time.sleep(0.10) 125 | else: 126 | item = self.images.get() 127 | 128 | if item != None: 129 | filename, i = item 130 | 131 | #i.save(filename) 132 | 133 | image_converted = i.Convert(PySpin.PixelFormat_BGR8, PySpin.DIRECTIONAL_FILTER) 134 | 135 | #writing with spinaker 136 | 137 | image_converted.Save(filename) 138 | 139 | #writing with opencv 140 | 141 | #image_data = image_converted.GetData() 142 | #cvi = np.frombuffer(image_data, dtype=np.uint8) 143 | #cvi = cvi.reshape((i.GetHeight(),i.GetWidth(),3)) 144 | #cv2.imwrite(filename, cvi) 145 | 146 | 147 | # 148 | # loop 149 | # 150 | 151 | 152 | worker = ImageWorker() 153 | worker.start() 154 | 155 | count = 0 156 | fps_report_frequency = fps*2 157 | start_time = time.time() 158 | 159 | try: 160 | while 1: 161 | if cv2.waitKey(1) != -1: 162 | break 163 | 164 | if count % fps_report_frequency == 0: 165 | fps = fps_report_frequency / (time.time() - start_time) # / fps_report_frequency 166 | print("fps {:.3f} image count {}, in buffer {}".format(fps, count,worker.images.qsize() )) 167 | start_time = time.time() 168 | 169 | #cam.TriggerSoftware() 170 | i = cam.GetNextImage() 171 | #print("new one", count) 172 | #print(i.GetWidth(), i.GetHeight(), i.GetBitsPerPixel()) 173 | cvi = None 174 | 175 | if i.IsIncomplete(): 176 | pass 177 | else: 178 | filename = "{}/cam_{:06}.jpg".format(target_folder,count) 179 | worker.addImage( (filename, i) ) 180 | count += 1 181 | i.Release() 182 | del i 183 | 184 | except KeyboardInterrupt: 185 | pass 186 | # 187 | # cleanup 188 | # 189 | 190 | worker.stop() 191 | 192 | while(1): 193 | print("{} images to be processed. waiting for thread to finish".format(worker.images.qsize())) 194 | time.sleep(0.5) 195 | if worker.images.empty(): 196 | break 197 | 198 | 199 | cam.EndAcquisition() 200 | reset_trigger_mode_software(cam) 201 | cam.DeInit() 202 | del cam 203 | del cam_list 204 | 205 | system.ReleaseInstance() 206 | del system 207 | 208 | -------------------------------------------------------------------------------- /flir/flir_detect_aruco.py: -------------------------------------------------------------------------------- 1 | import sys 2 | import time 3 | import PySpin 4 | 5 | import numpy as np 6 | import cv2 7 | 8 | 9 | def detect_aruco_markers(img, dictionary): 10 | corner_criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 100, 0.00001) 11 | gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) 12 | corners, ids, rejectedImgPoints = cv2.aruco.detectMarkers(gray, dictionary) 13 | if len(corners)>0: 14 | for corner in corners: 15 | cv2.cornerSubPix(gray, corner, winSize=(3,3), zeroZone=(-1,-1), criteria=corner_criteria) 16 | return corners, ids 17 | 18 | 19 | def set_trigger_mode(cam, triggerSource): 20 | cam.TriggerMode.SetValue(PySpin.TriggerMode_Off) 21 | cam.TriggerSource.SetValue(triggerSource) 22 | cam.TriggerMode.SetValue(PySpin.TriggerMode_On) 23 | 24 | def reset_trigger_mode_software(cam): 25 | cam.TriggerMode.SetValue(PySpin.TriggerMode_Off) 26 | print("reset trigger mode") 27 | 28 | # 29 | # setup 30 | # 31 | 32 | system = PySpin.System.GetInstance() 33 | cam_list = system.GetCameras() 34 | 35 | master_id = "18284509" 36 | master = None 37 | 38 | print("number of cameras {}".format(cam_list.GetSize())) 39 | 40 | 41 | if cam_list.GetSize() == 0: 42 | print("no cameras found, aborting") 43 | system.ReleaseInstance() 44 | del system 45 | sys.exit() 46 | 47 | cameras = [] 48 | for i in range(cam_list.GetSize()): 49 | try: 50 | cam = cam_list.GetByIndex(i) 51 | cam_id = cam.GetUniqueID() 52 | cam.Init() 53 | 54 | 55 | if cam_id == master_id: 56 | print("master: {}".format(cam_id)) 57 | master = cam 58 | set_trigger_mode(cam, PySpin.TriggerSource_Software) 59 | else: 60 | print("follower: {}".format(cam_id)) 61 | set_trigger_mode(cam, PySpin.TriggerSource_Line3) 62 | cam.AcquisitionMode.SetValue(PySpin.AcquisitionMode_Continuous) 63 | cam.BeginAcquisition() 64 | cameras.append(cam) 65 | except PySpin.SpinnakerException as ex: 66 | print("Error: {}".format(ex)) 67 | 68 | 69 | # 70 | # loop 71 | # 72 | 73 | 74 | count = 0 75 | size = 4 76 | frame = {} 77 | 78 | camera_dict = { "18284509": "", "18284511": "_1", "18284512": "_2"} 79 | 80 | 81 | dictionary = cv2.aruco.getPredefinedDictionary(cv2.aruco.DICT_4X4_250) 82 | 83 | print("start loop") 84 | 85 | while 1: 86 | 87 | key = cv2.waitKey(1) 88 | 89 | if key == 27: # ESC 90 | cv2.destroyAllWindows() 91 | break 92 | 93 | try: 94 | master.TriggerSoftware.Execute() 95 | except PySpin.SpinnakerException as ex: 96 | print("Error: {}".format(ex)) 97 | 98 | for cam in cameras: 99 | try: 100 | i = cam.GetNextImage() 101 | #print(i.GetWidth(), i.GetHeight(), i.GetBitsPerPixel()) 102 | 103 | if i.IsIncomplete(): 104 | pass 105 | else: 106 | cam_id = cam.GetUniqueID() 107 | # see documentation: enum ColorProcessingAlgorithm 108 | image_converted = i.Convert(PySpin.PixelFormat_BGR8, PySpin.DIRECTIONAL_FILTER) 109 | image_data = image_converted.GetData() 110 | cvi = np.frombuffer(image_data, dtype=np.uint8) 111 | cvi = cvi.reshape((i.GetHeight(),i.GetWidth(),3)) 112 | 113 | corners, ids = detect_aruco_markers(frame, dictionary) 114 | 115 | frame[cam_id] = cvi 116 | 117 | res = cv2.resize(cvi, (int(1280/size),int(1024/size))) 118 | cv2.imshow("cam{}".format(cam_id),res) 119 | i.Release() 120 | del i 121 | except PySpin.SpinnakerException as ex: 122 | print("Error: {}".format(ex)) 123 | 124 | # 125 | # cleanup 126 | # 127 | 128 | del master 129 | for cam in cameras: 130 | cam.EndAcquisition() 131 | reset_trigger_mode_software(cam) 132 | cam.DeInit() 133 | del cam 134 | del cameras 135 | del cam_list 136 | 137 | system.ReleaseInstance() 138 | del system -------------------------------------------------------------------------------- /flir/fps_counter.py: -------------------------------------------------------------------------------- 1 | import sys 2 | import time 3 | 4 | 5 | fps_report_frequency = 10 6 | fps = 30 7 | 8 | count = 0 9 | 10 | start = last = time.time() 11 | 12 | last_fps = 0 13 | 14 | while(1): 15 | count += 1 16 | 17 | while time.time() < (start + 1.0/fps): 18 | time.sleep(0.0001) 19 | 20 | start = time.time() 21 | 22 | last_fps += 1.0 / (start-last) 23 | last = time.time() 24 | 25 | if count % fps_report_frequency == 0: 26 | print("fps {0:.3f}".format( last_fps / fps_report_frequency)) 27 | last_fps = 0 28 | -------------------------------------------------------------------------------- /img/kinect_detection.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/daan/calibrating-with-python-opencv/c143ddb341847e540d773f4c7bff8f523842a45f/img/kinect_detection.jpg -------------------------------------------------------------------------------- /kinect-v2/README.rst: -------------------------------------------------------------------------------- 1 | Find Chessboards with Kinect for Windows 2 | ======================================== 3 | 4 | The basic idea is to find points in the color image and use the coordinate mapper to retrieve the 3D position. 5 | These examples use pyKinect2 to interface with the Kinect API, and only work on Windows with the Kinect API installed. 6 | 7 | Installation 8 | ------------ 9 | 10 | Install the kinect v2 SDK https://www.microsoft.com/en-us/download/details.aspx?id=44561 11 | Install python, opencv and contrib (see top level readme) and install pyKinect2. 12 | 13 | note: (october 5 2018: if you install with pip, you need to overwrite the files with the ones from github....) 14 | 15 | Examples 16 | -------- 17 | All scripts wait until the sensor is connected. Once the video feed is shown, stop a script with the escape key. 18 | 19 | - **color.py** shows the color frame. 20 | - **depth.py** shows the depth frame. 21 | - **infrared.py** shows the infrared frame. 22 | - **detect_charuco.py** detects an charuco board in the color frame. Use board.pdf in the top level data folder. 23 | - **color_3d** uses the coordinate mapper to get the 3D position for each pixel in the color frame. 24 | The z value (away from the camera) is drawn scaled down. The depth value of the center point is indicated 25 | 26 | 27 | - **capture_board.py** detects the charuco board and retrieves the 3D coordinates. The space key saves the image, 28 | and coordinates for the board and markers in json. 29 | 30 | 31 | 32 | 33 | -------------------------------------------------------------------------------- /kinect-v2/body.py: -------------------------------------------------------------------------------- 1 | from pykinect2 import PyKinectV2 2 | from pykinect2.PyKinectV2 import * 3 | from pykinect2 import PyKinectRuntime 4 | 5 | import time 6 | import math 7 | import numpy as np 8 | import cv2 9 | import sys 10 | 11 | # 12 | # initial version ported from https://github.com/Kinect/PyKinect2/blob/master/examples/PyKinectBodyGame.py 13 | # removed pygame dependency, draw with opencv 14 | # 15 | # added simple recording of 3D coordinates 16 | # 17 | 18 | color_image_size = (1080,1920) 19 | color_image_shape = (1080,1920,4) 20 | 21 | kinect = PyKinectRuntime.PyKinectRuntime(PyKinectV2.FrameSourceTypes_Color | PyKinectV2.FrameSourceTypes_Body) 22 | 23 | def draw_skeleton(color_flipped, skeleton_id, joints): 24 | for j in joints: 25 | if math.isinf(j.x) or math.isinf(j.y): 26 | continue 27 | cv2.circle(color_flipped, ( 1920-int(j.x), int(j.y)), 5, (0,0,255), -1) 28 | 29 | joints_in_color_space = [] 30 | 31 | while(1): 32 | 33 | if kinect.has_new_body_frame(): 34 | bodies = kinect.get_last_body_frame() 35 | if bodies is not None: 36 | for i in range(0, kinect.max_body_count): 37 | body = bodies.bodies[i] 38 | if not body.is_tracked: 39 | continue 40 | joints = body.joints 41 | 42 | # convert joint coordinates to color space 43 | joints_in_color_space = kinect.body_joints_to_color_space(joints) 44 | 45 | 46 | if joints[0].TrackingState != PyKinectV2.TrackingState_NotTracked and joints[0].TrackingState != PyKinectV2.TrackingState_Inferred: 47 | print( joints[0].Position.x, joints[0].Position.y, joints[0].Position.z ) 48 | 49 | 50 | 51 | 52 | 53 | if kinect.has_new_color_frame(): 54 | color_frame = kinect.get_last_color_frame() 55 | color_frame = color_frame.reshape(color_image_shape) 56 | 57 | color_frame = cv2.cvtColor(color_frame, cv2.COLOR_BGRA2BGR) 58 | color_flipped = cv2.flip(color_frame,1) 59 | 60 | draw_skeleton(color_flipped, i, joints_in_color_space) 61 | 62 | 63 | cv2.imshow('color',color_flipped) 64 | 65 | 66 | if (cv2.waitKey(1) == 27): 67 | cv2.destroyAllWindows() 68 | kinect.close() 69 | break -------------------------------------------------------------------------------- /kinect-v2/cap/frame_0.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/daan/calibrating-with-python-opencv/c143ddb341847e540d773f4c7bff8f523842a45f/kinect-v2/cap/frame_0.jpg -------------------------------------------------------------------------------- /kinect-v2/cap/frame_0.json: -------------------------------------------------------------------------------- 1 | {"points": [{"id": "0", "x": 0.16351009905338287, "y": 0.08542162925004959, "z": 2.576000213623047}, {"id": "1", "x": 0.023896237835288048, "y": 0.08541519939899445, "z": 2.575000047683716}, {"id": "2", "x": -0.1151033565402031, "y": 0.08497083932161331, "z": 2.562000036239624}, {"id": "3", "x": -0.25372666120529175, "y": 0.08488654345273972, "z": 2.561000108718872}, {"id": "4", "x": 0.1686871498823166, "y": 0.2157464176416397, "z": 2.5500001907348633}, {"id": "5", "x": 0.023661363869905472, "y": 0.22280505299568176, "z": 2.5510001182556152}, {"id": "6", "x": -0.11437154561281204, "y": 0.22242294251918793, "z": 2.5470001697540283}, {"id": "7", "x": -0.25221914052963257, "y": 0.2222953587770462, "z": 2.5470001697540283}, {"id": "8", "x": 0.16740942001342773, "y": 0.35805556178092957, "z": 2.5330002307891846}, {"id": "9", "x": 0.023481054231524467, "y": 0.36514201760292053, "z": 2.5340001583099365}, {"id": "10", "x": -0.11327607184648514, "y": 0.3637966513633728, "z": 2.5250000953674316}, {"id": "11", "x": -0.24981747567653656, "y": 0.36360856890678406, "z": 2.5250000953674316}, {"id": "12", "x": 0.17253842949867249, "y": 0.4970284402370453, "z": 2.511000156402588}, {"id": "13", "x": 0.03000449761748314, "y": 0.49676570296287537, "z": 2.509000062942505}, {"id": "14", "x": -0.10572926700115204, "y": 0.4971136450767517, "z": 2.511000156402588}, {"id": "15", "x": -0.25422540307044983, "y": 0.49548789858818054, "z": 2.504000186920166}, {"id": "16", "x": 0.17072491347789764, "y": 0.6395395398139954, "z": 2.4880001544952393}, {"id": "17", "x": 0.029710905626416206, "y": 0.6396704912185669, "z": 2.4880001544952393}, {"id": "18", "x": -0.10457165539264679, "y": 0.639366090297699, "z": 2.4870002269744873}, {"id": "19", "x": -0.25136327743530273, "y": 0.6370757818222046, "z": 2.4790000915527344}, {"id": "20", "x": 0.17566585540771484, "y": 0.7727544903755188, "z": 2.4660000801086426}, {"id": "21", "x": 0.029435863718390465, "y": 0.7734922170639038, "z": 2.4680001735687256}, {"id": "22", "x": -0.10347992181777954, "y": 0.7722011208534241, "z": 2.4640002250671387}, {"id": "23", "x": -0.2483595609664917, "y": 0.7682611346244812, "z": 2.452000141143799}]} -------------------------------------------------------------------------------- /kinect-v2/cap/frame_0_annotated.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/daan/calibrating-with-python-opencv/c143ddb341847e540d773f4c7bff8f523842a45f/kinect-v2/cap/frame_0_annotated.jpg -------------------------------------------------------------------------------- /kinect-v2/capture_board.py: -------------------------------------------------------------------------------- 1 | from pykinect2 import PyKinectV2 2 | from pykinect2.PyKinectV2 import * 3 | from pykinect2 import PyKinectRuntime 4 | 5 | import time 6 | import numpy as np 7 | import cv2 8 | import math 9 | import json 10 | 11 | import sys 12 | import os 13 | 14 | import argparse 15 | 16 | # construct the argument parse and parse the arguments 17 | ap = argparse.ArgumentParser() 18 | ap.add_argument("folder", help="folder to save images") 19 | ap.add_argument("-f", "--force", action="store_true", help="force overwrite in folder") 20 | 21 | args = vars(ap.parse_args()) 22 | 23 | # make folder 24 | target_folder = args['folder'] 25 | if os.path.isdir(target_folder): 26 | if args['force'] == False: 27 | print("{}: error: folder {} exists. Use --force to overwrite files.".format(os.path.basename(sys.argv[0]), target_folder)) 28 | sys.exit() 29 | else: 30 | os.makedirs(target_folder) 31 | 32 | 33 | 34 | 35 | charuco_square_length = 140.0 / 1000 # chessboard square side length (normally in meters) 36 | charuco_marker_length = 88.0 / 1000 # marker side length (same unit than squareLength) 37 | squaresX = 5 38 | squaresY = 7 39 | dictionary = cv2.aruco.getPredefinedDictionary(cv2.aruco.DICT_4X4_250) 40 | board = cv2.aruco.CharucoBoard_create(squaresX,squaresY,charuco_square_length,charuco_marker_length,dictionary) 41 | 42 | depth_image_size = (424, 512) 43 | color_image_size = (1080, 1920) 44 | color_image_shape = (color_image_size[0], color_image_size[1], 4) 45 | color_size = color_image_size[0] * color_image_size[1] 46 | 47 | 48 | # TODO: make a helper file (this is the same code as detect_charuco) 49 | def find_charuco_board(img, board, dictionary): 50 | corner_criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 100, 0.00001) 51 | gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) 52 | corners, ids, rejectedImgPoints = cv2.aruco.detectMarkers(gray, dictionary) 53 | 54 | 55 | if len(corners)>0: 56 | for corner in corners: 57 | cv2.cornerSubPix(gray, corner, winSize=(3,3), zeroZone=(-1,-1), criteria=corner_criteria) 58 | ret, detectedCorners, detectedIds = cv2.aruco.interpolateCornersCharuco(corners,ids,gray,board) 59 | 60 | if detectedIds is None: 61 | return [], [] 62 | 63 | if len(detectedCorners) != len(detectedIds): 64 | print("should not happen") 65 | return [],[] 66 | if detectedCorners is not None and detectedIds is not None and len(detectedCorners)>3: 67 | return detectedCorners, detectedIds 68 | return [], [] 69 | 70 | # TODO: make a helper file (this is the same code as color_3d.py) 71 | class Color2CameraMap(): 72 | def __init__(self, depth_frame): 73 | self._depth_frame = depth_frame 74 | depth_frame_ptr = np.ctypeslib.as_ctypes(depth_frame.flatten()) 75 | # create camera space points for each pixel in the color frame 76 | TYPE_CameraSpacePointArray = PyKinectV2._CameraSpacePoint * color_size 77 | self._camera_points = TYPE_CameraSpacePointArray() 78 | error_state = kinect._mapper.MapColorFrameToCameraSpace( 79 | depth_frame.size, depth_frame_ptr, color_size, self._camera_points) 80 | if error_state != 0: 81 | raise OSError("error {} in mapping: MapcolorFrameToCamera.".format( 82 | error_state)) 83 | 84 | def make_color_image(self, divide_by=6): 85 | image = np.zeros((int(color_image_size[0] / divide_by), 86 | int(color_image_size[1] / divide_by)), np.uint8) 87 | for iy in range(0, color_image_size[0], divide_by): 88 | for ix in range(0, color_image_size[1], divide_by): 89 | z = float(self._camera_points[iy * 1920 + ix].z) 90 | if math.isinf(z) or math.isnan(z): 91 | z = 0 92 | image[int(iy / divide_by), int(ix / divide_by)] = int( 93 | (z / 9.0) * 255) # map 9 meters 94 | # apply a color map 95 | colored = cv2.applyColorMap(image, cv2.COLORMAP_HOT) 96 | return colored 97 | 98 | def get_camera_point(self, color_point, isFlipped = False): 99 | if isFlipped: 100 | color_point[0] = color_image_size[1] - color_point[0] 101 | # find the coordinate in the 3D map 102 | index = int(color_point[1] * color_image_size[1] + color_point[0]) 103 | camera_point = self._camera_points[index] 104 | return [ 105 | float(camera_point.x), 106 | float(camera_point.y), 107 | float(camera_point.z) 108 | ] 109 | 110 | 111 | 112 | kinect = PyKinectRuntime.PyKinectRuntime(PyKinectV2.FrameSourceTypes_Color | PyKinectV2.FrameSourceTypes_Depth) 113 | 114 | font = cv2.FONT_HERSHEY_SIMPLEX 115 | 116 | p3d = None 117 | p2d = None 118 | p2d = [480, 240] 119 | 120 | corners3d = [] 121 | corners = [] 122 | ids = [] 123 | 124 | count = 0 125 | 126 | while(1): 127 | if kinect.has_new_depth_frame(): 128 | depth_frame = kinect.get_last_depth_frame() 129 | 130 | if p2d != None: 131 | try: 132 | map = Color2CameraMap(depth_frame) 133 | p3d = map.get_camera_point( p2d, True ) 134 | corners3d = [] 135 | for c in corners: 136 | x = round(c[0][0]) 137 | y = round(c[0][1]) 138 | c3d = map.get_camera_point( [x,y], True ) 139 | corners3d.append(c3d) 140 | except OSError as err: 141 | print(err) 142 | p3d = None 143 | else: 144 | p3d = None 145 | 146 | if kinect.has_new_color_frame(): 147 | color_frame = kinect.get_last_color_frame() 148 | color_frame = color_frame.reshape(color_image_shape) 149 | 150 | color_frame = cv2.cvtColor(color_frame, cv2.COLOR_BGRA2BGR) 151 | color_flipped = cv2.flip(color_frame,1) 152 | 153 | color_org = color_flipped.copy() 154 | 155 | 156 | corners, ids = find_charuco_board(color_flipped, board, dictionary) 157 | if len(corners) > 0: 158 | cv2.aruco.drawDetectedCornersCharuco(color_flipped, corners, ids) 159 | 160 | # draw lines to depict the first marker (id_0 if not obstructed.....) 161 | x,y = corners[0][0][0], corners[0][0][1] 162 | p2d = [round(x),round(y)] 163 | cv2.line(color_flipped, (0,y),(1920,y),(0,0,255),2) 164 | cv2.line(color_flipped, (x,0),(x,1080),(255,0,0),2) 165 | 166 | cv2.circle(color_flipped, (p2d[0], p2d[1]), 100, (255,255,255)) 167 | 168 | if p2d != None and p3d != None: 169 | # draw the coordinates 170 | cv2.putText(color_flipped,"{0:.3f}".format(p3d[0]), (100,200), font, 4,(0,0,255), 6, cv2.LINE_AA) 171 | cv2.putText(color_flipped,"{0:.3f}".format(p3d[1]), (100,400), font, 4,(0,255,0), 6, cv2.LINE_AA) 172 | cv2.putText(color_flipped,"{0:.3f}".format(p3d[2]), (100,600), font, 4,(255,0,0), 6, cv2.LINE_AA) 173 | 174 | 175 | cv2.imshow('color',color_flipped) 176 | 177 | key = cv2.waitKey(1) 178 | 179 | if key == 27: 180 | cv2.destroyAllWindows() 181 | kinect.close() 182 | break 183 | elif key == 32: 184 | print("take picture") 185 | print(len(ids), len(corners3d)) 186 | cv2.imwrite("{}/frame_{}_annotated.jpg".format(target_folder, count), color_flipped) 187 | 188 | cv2.imwrite("{}/frame_{}.jpg".format(target_folder, count), color_org) 189 | #write the coords 190 | points = [] 191 | for i in range(len(ids)): 192 | p = {} 193 | p['id'] = str(ids[i][0]) 194 | p['x'] = corners3d[i][0] 195 | p['y'] = corners3d[i][1] 196 | p['z'] = corners3d[i][2] 197 | points.append(p) 198 | json_data = { "charucoCorners": points } 199 | with open("{}/frame_{}.json".format(target_folder, count), 'w') as f: 200 | json.dump(json_data, f) 201 | count += 1 202 | 203 | 204 | 205 | 206 | 207 | 208 | -------------------------------------------------------------------------------- /kinect-v2/color.py: -------------------------------------------------------------------------------- 1 | from pykinect2 import PyKinectV2 2 | from pykinect2.PyKinectV2 import * 3 | from pykinect2 import PyKinectRuntime 4 | 5 | import time 6 | import numpy as np 7 | import cv2 8 | import sys 9 | 10 | color_image_size = (1080,1920) 11 | color_image_shape = (1080,1920,4) 12 | 13 | kinect = PyKinectRuntime.PyKinectRuntime(PyKinectV2.FrameSourceTypes_Color) 14 | 15 | while(1): 16 | if kinect.has_new_color_frame(): 17 | color_frame = kinect.get_last_color_frame() 18 | color_frame = color_frame.reshape(color_image_shape) 19 | 20 | color_frame = cv2.cvtColor(color_frame, cv2.COLOR_BGRA2BGR) 21 | color_flipped = cv2.flip(color_frame,1) 22 | 23 | 24 | cv2.imshow('color',color_flipped) 25 | 26 | if (cv2.waitKey(1) == 27): 27 | cv2.destroyAllWindows() 28 | kinect.close() 29 | break -------------------------------------------------------------------------------- /kinect-v2/color_3d.py: -------------------------------------------------------------------------------- 1 | from pykinect2 import PyKinectV2 2 | from pykinect2.PyKinectV2 import * 3 | from pykinect2 import PyKinectRuntime 4 | 5 | import time 6 | import numpy as np 7 | import cv2 8 | import math 9 | 10 | # opencv images are matrices and row-major-order (row, column) 11 | # opencv pts and coordinates are (x,y) 12 | # 13 | # x left to right 14 | # y top to bottom 15 | # 16 | depth_image_size = (424, 512) 17 | color_image_size = (1080, 1920) 18 | color_image_shape = (color_image_size[0], color_image_size[1], 4) 19 | color_size = color_image_size[0] * color_image_size[1] 20 | 21 | 22 | class Color2CameraMap(): 23 | def __init__(self, depth_frame): 24 | self._depth_frame = depth_frame 25 | depth_frame_ptr = np.ctypeslib.as_ctypes(depth_frame.flatten()) 26 | # create camera space points for each pixel in the color frame 27 | TYPE_CameraSpacePointArray = PyKinectV2._CameraSpacePoint * color_size 28 | self._camera_points = TYPE_CameraSpacePointArray() 29 | error_state = kinect._mapper.MapColorFrameToCameraSpace( 30 | depth_frame.size, depth_frame_ptr, color_size, self._camera_points) 31 | if error_state != 0: 32 | raise OSError("error {} in mapping: MapcolorFrameToCamera.".format( 33 | error_state)) 34 | 35 | def make_color_image(self, divide_by=6): 36 | image = np.zeros((int(color_image_size[0] / divide_by), 37 | int(color_image_size[1] / divide_by)), np.uint8) 38 | for iy in range(0, color_image_size[0], divide_by): 39 | for ix in range(0, color_image_size[1], divide_by): 40 | z = float(self._camera_points[iy * 1920 + ix].z) 41 | if math.isinf(z) or math.isnan(z): 42 | z = 0 43 | image[int(iy / divide_by), int(ix / divide_by)] = int( 44 | (z / 9.0) * 255) # map 9 meters 45 | # apply a color map 46 | colored = cv2.applyColorMap(image, cv2.COLORMAP_HOT) 47 | return colored 48 | 49 | def get_camera_point(self, color_point): 50 | # find the coordinate in the image 51 | index = color_point[1] * color_image_size[1] + color_point[0] 52 | camera_point = self._camera_points[index] 53 | return [ 54 | float(camera_point.x), 55 | float(camera_point.y), 56 | float(camera_point.z) 57 | ] 58 | 59 | def get_camera_points(self, color_points): 60 | r = [] 61 | for p in color_points: 62 | r.append(self.get_camera_point(p)) 63 | return r 64 | 65 | 66 | kinect = PyKinectRuntime.PyKinectRuntime(PyKinectV2.FrameSourceTypes_Color 67 | | PyKinectV2.FrameSourceTypes_Depth) 68 | 69 | font = cv2.FONT_HERSHEY_SIMPLEX 70 | 71 | while (1): 72 | if kinect.has_new_depth_frame(): 73 | depth_frame = kinect.get_last_depth_frame() 74 | 75 | try: 76 | map = Color2CameraMap(depth_frame) 77 | divide_by = 6 78 | img = map.make_color_image(divide_by) 79 | 80 | # points are in (x,y) 81 | sample_point = [ int(1920/2), int(1080/2)] 82 | sample_point = [480, 240] 83 | p3d = map.get_camera_point( sample_point ) 84 | print(p3d) 85 | # draw a reference circle at pt 86 | scaled_point = ( int( sample_point[0]/divide_by), int(sample_point[1]/divide_by) ) 87 | cv2.circle(img, scaled_point, int(30/divide_by), (255,255,255)) 88 | # print the distance. 89 | cv2.putText(img," {0:.3f}".format(p3d[2]), scaled_point, font, 8/divide_by,(255,255,255),2,cv2.LINE_AA) 90 | cv2.imshow('color', img) 91 | 92 | except OSError as err: 93 | print(err) 94 | 95 | if (cv2.waitKey(1) == 27): 96 | cv2.destroyAllWindows() 97 | kinect.close() 98 | break 99 | -------------------------------------------------------------------------------- /kinect-v2/depth.py: -------------------------------------------------------------------------------- 1 | from pykinect2 import PyKinectV2 2 | from pykinect2.PyKinectV2 import * 3 | from pykinect2 import PyKinectRuntime 4 | 5 | import time 6 | import numpy as np 7 | import cv2 8 | 9 | depth_image_size = (424,512) 10 | 11 | kinect = PyKinectRuntime.PyKinectRuntime(PyKinectV2.FrameSourceTypes_Depth) 12 | 13 | while(1): 14 | if kinect.has_new_depth_frame(): 15 | depth_frame = kinect.get_last_depth_frame() 16 | depth_frame = depth_frame.reshape(depth_image_size) 17 | 18 | # map the depth frame to uint8 19 | depth_frame = depth_frame * (256.0/np.amax(depth_frame)) 20 | 21 | colorized_frame = cv2.applyColorMap(np.uint8(depth_frame), cv2.COLORMAP_JET) 22 | cv2.imshow('depth',colorized_frame) 23 | 24 | if (cv2.waitKey(1) == 27): 25 | cv2.destroyAllWindows() 26 | kinect.close() 27 | break -------------------------------------------------------------------------------- /kinect-v2/detect_aruco.py: -------------------------------------------------------------------------------- 1 | from pykinect2 import PyKinectV2 2 | from pykinect2.PyKinectV2 import * 3 | from pykinect2 import PyKinectRuntime 4 | 5 | import time 6 | import numpy as np 7 | import cv2 8 | 9 | dictionary = cv2.aruco.getPredefinedDictionary(cv2.aruco.DICT_4X4_250) 10 | 11 | color_image_size = (1080,1920) 12 | color_image_shape = (1080,1920,4) 13 | 14 | def detect_aruco_markers(img, dictionary): 15 | corner_criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 100, 0.00001) 16 | gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) 17 | corners, ids, rejectedImgPoints = cv2.aruco.detectMarkers(gray, dictionary) 18 | if len(corners)>0: 19 | for corner in corners: 20 | cv2.cornerSubPix(gray, corner, winSize=(3,3), zeroZone=(-1,-1), criteria=corner_criteria) 21 | ret, detectedCorners, detectedIds = cv2.aruco.interpolateCornersCharuco(corners,ids,gray,board) 22 | if detectedCorners is not None and detectedIds is not None and len(detectedCorners)>3: 23 | return detectedCorners, detectedIds 24 | return [], [] 25 | 26 | 27 | kinect = PyKinectRuntime.PyKinectRuntime(PyKinectV2.FrameSourceTypes_Color) 28 | 29 | color_frame = None 30 | counter = 0 31 | 32 | while(1): 33 | if kinect.has_new_color_frame(): 34 | color_frame = kinect.get_last_color_frame() 35 | color_frame = color_frame.reshape(color_image_shape) 36 | 37 | color_frame = cv2.cvtColor(color_frame, cv2.COLOR_BGRA2BGR) 38 | color_flipped = cv2.flip(color_frame,1) 39 | 40 | corners, ids = find_aruco_markers(color_flipped, board, dictionary) 41 | 42 | if len(corners) > 0: 43 | cv2.aruco.drawDetectedMarkers(color_flipped, corners, ids) 44 | cv2.imshow('color',color_flipped) 45 | 46 | key = cv2.waitKey(1) 47 | if key == 27: 48 | cv2.destroyAllWindows() 49 | kinect.close() 50 | break 51 | elif key == 32: 52 | if color_frame != None: 53 | cv2.imwrtie("frame_{}.jpg".format(counter), cv2.flip(color_frame,1)) 54 | counter += 1 -------------------------------------------------------------------------------- /kinect-v2/detect_charuco.py: -------------------------------------------------------------------------------- 1 | from pykinect2 import PyKinectV2 2 | from pykinect2.PyKinectV2 import * 3 | from pykinect2 import PyKinectRuntime 4 | 5 | import time 6 | import numpy as np 7 | import cv2 8 | 9 | 10 | squareLength = 35.0 / 1000 # chessboard square side length (normally in meters) 11 | markerLength = 22.0 / 1000 # marker side length (same unit than squareLength) 12 | squaresX = 5 13 | squaresY = 7 14 | 15 | dictionary = cv2.aruco.getPredefinedDictionary(cv2.aruco.DICT_6X6_250) 16 | board = cv2.aruco.CharucoBoard_create(squaresX,squaresY,squareLength,markerLength,dictionary) 17 | 18 | color_image_size = (1080,1920) 19 | color_image_shape = (1080,1920,4) 20 | 21 | def find_charuco_board(img, board, dictionary): 22 | corner_criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 100, 0.00001) 23 | gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) 24 | corners, ids, rejectedImgPoints = cv2.aruco.detectMarkers(gray, dictionary) 25 | if len(corners)>0: 26 | for corner in corners: 27 | cv2.cornerSubPix(gray, corner, winSize=(3,3), zeroZone=(-1,-1), criteria=corner_criteria) 28 | ret, detectedCorners, detectedIds = cv2.aruco.interpolateCornersCharuco(corners,ids,gray,board) 29 | if detectedCorners is not None and detectedIds is not None and len(detectedCorners)>3: 30 | return detectedCorners, detectedIds 31 | return [], [] 32 | 33 | 34 | kinect = PyKinectRuntime.PyKinectRuntime(PyKinectV2.FrameSourceTypes_Color) 35 | 36 | while(1): 37 | if kinect.has_new_color_frame(): 38 | color_frame = kinect.get_last_color_frame() 39 | color_frame = color_frame.reshape(color_image_shape) 40 | 41 | color_frame = cv2.cvtColor(color_frame, cv2.COLOR_BGRA2BGR) 42 | color_flipped = cv2.flip(color_frame,1) 43 | 44 | corners, ids = find_charuco_board(color_flipped, board, dictionary) 45 | if len(corners) > 0: 46 | cv2.aruco.drawDetectedCornersCharuco(color_flipped, corners, ids) 47 | cv2.imshow('color',color_flipped) 48 | 49 | if (cv2.waitKey(1) == 27): 50 | cv2.destroyAllWindows() 51 | kinect.close() 52 | break -------------------------------------------------------------------------------- /kinect-v2/frame_0.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/daan/calibrating-with-python-opencv/c143ddb341847e540d773f4c7bff8f523842a45f/kinect-v2/frame_0.jpg -------------------------------------------------------------------------------- /kinect-v2/frame_0.json: -------------------------------------------------------------------------------- 1 | {"0": {"x": 0.25240445137023926, "y": -0.014789115637540817, "z": 0.8110000491142273}, "1": {"x": 0.20163775980472565, "y": -0.01039130613207817, "z": 0.8080000281333923}, "2": {"x": 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from pykinect2 import PyKinectV2 2 | from pykinect2.PyKinectV2 import * 3 | from pykinect2 import PyKinectRuntime 4 | 5 | import time 6 | import numpy as np 7 | import cv2 8 | 9 | ir_image_size = (424,512) 10 | 11 | kinect = PyKinectRuntime.PyKinectRuntime(PyKinectV2.FrameSourceTypes_Infrared) 12 | 13 | while(1): 14 | if kinect.has_new_infrared_frame(): 15 | ir_frame = kinect.get_last_infrared_frame() 16 | ir_frame = ir_frame.reshape(ir_image_size) 17 | ir_frame = np.uint8(ir_frame/256) 18 | 19 | 20 | cv2.imshow('ir',ir_frame) 21 | 22 | if (cv2.waitKey(1) == 27): 23 | cv2.destroyAllWindows() 24 | kinect.close() 25 | break -------------------------------------------------------------------------------- /kinect-v2/sample-data/frame_0.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/daan/calibrating-with-python-opencv/c143ddb341847e540d773f4c7bff8f523842a45f/kinect-v2/sample-data/frame_0.jpg -------------------------------------------------------------------------------- /kinect-v2/sample-data/frame_0.json: -------------------------------------------------------------------------------- 1 | {"0": {"x": 0.12264157086610794, "y": 0.18982534110546112, "z": 0.8350000381469727}, "1": {"x": 0.1572970598936081, "y": 0.19086092710494995, "z": 0.8400000333786011}, "4": {"x": 0.12553592026233673, "y": 0.16294409334659576, "z": 0.8240000605583191}, "5": {"x": 0.15621362626552582, "y": 0.16245456039905548, "z": 0.8220000267028809}, "6": {"x": 0.19227436184883118, "y": 0.16293714940547943, "z": 0.8250000476837158}, "7": {"x": 0.22411394119262695, "y": 0.16344216465950012, "z": 0.8280000686645508}, "8": {"x": 0.12689535319805145, "y": 0.1330062597990036, "z": 0.8040000200271606}, "11": {"x": 0.22555434703826904, "y": 0.13355059921741486, "z": 0.8090000152587891}, "15": {"x": 0.22570067644119263, "y": 0.10327038168907166, "z": 0.7940000295639038}, "19": {"x": 0.2277611792087555, "y": 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0.8110000491142273}, "15": {"x": 0.2254164218902588, "y": 0.10314031690359116, "z": 0.7930000424385071}, "19": {"x": 0.22805355489253998, "y": 0.0741160660982132, "z": 0.7800000309944153}, "23": {"x": 0.22721485793590546, "y": 0.04575635492801666, "z": 0.7630000114440918}} -------------------------------------------------------------------------------- /kinect-v2/sample-data/frame_3.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/daan/calibrating-with-python-opencv/c143ddb341847e540d773f4c7bff8f523842a45f/kinect-v2/sample-data/frame_3.jpg -------------------------------------------------------------------------------- /kinect-v2/sample-data/frame_3.json: -------------------------------------------------------------------------------- 1 | {"0": {"x": 0.1227884441614151, "y": 0.19005267322063446, "z": 0.8360000252723694}, "1": {"x": 0.15767158567905426, "y": 0.19131536781787872, "z": 0.8420000672340393}, "4": {"x": 0.12507887184619904, "y": 0.1623508334159851, "z": 0.8210000395774841}, "5": {"x": 0.15621362626552582, "y": 0.16245456039905548, "z": 0.8220000267028809}, "6": {"x": 0.1920413076877594, "y": 0.16273964941501617, "z": 0.8240000605583191}, "7": {"x": 0.22551782429218292, "y": 0.16284441947937012, "z": 0.8250000476837158}, "8": {"x": 0.12721101939678192, "y": 0.1333371251821518, "z": 0.8060000538825989}, "11": {"x": 0.22555434703826904, "y": 0.13355059921741486, "z": 0.8090000152587891}, "15": {"x": 0.2254164218902588, "y": 0.10314031690359116, "z": 0.7930000424385071}, "19": {"x": 0.227468803524971, "y": 0.07392602413892746, "z": 0.7780000567436218}, "23": {"x": 0.22721485793590546, "y": 0.04575635492801666, "z": 0.7630000114440918}} -------------------------------------------------------------------------------- /webcam/capture_webcam.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | import cv2 3 | import sys 4 | import argparse 5 | 6 | # construct the argument parse and parse the arguments 7 | ap = argparse.ArgumentParser() 8 | ap.add_argument("-o", "--output", help="path to output image file(s)") 9 | ap.add_argument("-r", "--resolution", type=str, default="1280x720", help="resolution") 10 | ap.add_argument("-c", "--camera", type=str, default="0", help="camera by id") 11 | 12 | args = vars(ap.parse_args()) 13 | 14 | print(args["output"]) 15 | print(args["resolution"]) 16 | 17 | wh = args["resolution"].split("x") 18 | width = int(wh[0]) 19 | height = int(wh[1]) 20 | 21 | camera = 0 22 | 23 | print("opening video capture device {}".format(camera)) 24 | cap = cv2.VideoCapture(int(camera)) 25 | print("resolution {} by {} ".format(int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)), int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT )))) 26 | 27 | count = 0 28 | 29 | while(True): 30 | ret, frame = cap.read() 31 | frame = cv2.resize(frame, (width, height)) 32 | #frame = cv2.flip(frame,1) 33 | cv2.imshow('frame', frame) 34 | 35 | key = cv2.waitKey(10) 36 | print(key) 37 | if key == 32: 38 | print("take picture") 39 | count += 1 40 | cv2.imwrite("frame_{}.jpg".format(count), frame) 41 | 42 | elif key != -1: 43 | break 44 | 45 | cap.release() 46 | 47 | cv2.destroyAllWindows() 48 | 49 | 50 | 51 | 52 | -------------------------------------------------------------------------------- /webcam/detect_aruco.py: -------------------------------------------------------------------------------- 1 | import time 2 | import numpy as np 3 | import cv2 4 | 5 | from shared import * 6 | 7 | dictionary = cv2.aruco.getPredefinedDictionary(cv2.aruco.DICT_4X4_250) 8 | 9 | 10 | 11 | camera = 0 12 | 13 | cap = cv2.VideoCapture(camera) 14 | 15 | color_frame = None 16 | counter = 0 17 | 18 | while(1): 19 | ret, frame = cap.read() 20 | 21 | corners, ids = detect_aruco_markers(frame, dictionary) 22 | 23 | if len(corners) > 0: 24 | cv2.aruco.drawDetectedMarkers(frame, corners, ids) 25 | cv2.imshow('color', frame) 26 | 27 | key = cv2.waitKey(1) 28 | if key == 27: 29 | cv2.destroyAllWindows() 30 | kinect.close() 31 | break 32 | elif key == 32: 33 | if color_frame != None: 34 | cv2.imwrtie("frame_{}.jpg".format(counter), cv2.flip(color_frame,1)) 35 | counter += 1 -------------------------------------------------------------------------------- /webcam/estimate_pose.py: -------------------------------------------------------------------------------- 1 | import glob 2 | import numpy as np 3 | import cv2 4 | from cv2 import aruco 5 | import sys 6 | 7 | import json 8 | import argparse 9 | 10 | def find_charuco_board(img, board, dictionary): 11 | corner_criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 100, 0.00001) 12 | gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) 13 | corners, ids, rejectedImgPoints = cv2.aruco.detectMarkers(gray, dictionary) 14 | if corners is None or ids is None: 15 | return [], [] 16 | 17 | if len(corners)>0: 18 | for corner in corners: 19 | cv2.cornerSubPix(gray, corner, winSize=(3,3), zeroZone=(-1,-1), criteria=corner_criteria) 20 | ret, detectedCorners, detectedIds = cv2.aruco.interpolateCornersCharuco(corners,ids,gray,board) 21 | print("ret", ret) 22 | if detectedCorners is None or detectedIds is None: 23 | return [], [] 24 | if len(detectedCorners) < 3: 25 | return [], [] 26 | 27 | if len(detectedCorners) != len(detectedIds): 28 | print("numver of corners != ids") 29 | return [],[] 30 | return detectedCorners, detectedIds 31 | return [], [] 32 | 33 | 34 | 35 | squareLength = 35.0 / 1000 # chessboard square side length (normally in meters) 36 | markerLength = 22.0 / 1000 # marker side length (same unit than squareLength) 37 | squaresX = 5 38 | squaresY = 7 39 | 40 | dictionary = cv2.aruco.getPredefinedDictionary(cv2.aruco.DICT_6X6_250) 41 | board = cv2.aruco.CharucoBoard_create(squaresX,squaresY,squareLength,markerLength,dictionary) 42 | 43 | # construct the argument parse and parse the arguments 44 | ap = argparse.ArgumentParser() 45 | ap.add_argument("-o", "--output", help="path to output folder") 46 | ap.add_argument("-c", "--camera", type=int, default=0, help="camera by id") 47 | 48 | # read calibration file 49 | fs = cv2.FileStorage("sample-data/calibration.json", cv2.FILE_STORAGE_READ) 50 | if fs.isOpened() == False: 51 | print("couldn't load calibration data") 52 | sys.exit() 53 | 54 | intrinsics = fs.getNode("cameraMatrix").mat() 55 | dist_coeffs = fs.getNode("dist_coeffs").mat() 56 | print("intriniscs", intrinsics) 57 | print("dist coeffs", dist_coeffs) 58 | 59 | args = vars(ap.parse_args()) 60 | camera = args["camera"] 61 | 62 | print("opening video capture device {}".format(camera)) 63 | cap = cv2.VideoCapture(int(camera)) 64 | print("resolution {} by {} ".format(int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)), int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT )))) 65 | 66 | 67 | count = 0 68 | tvecs = [] 69 | font = cv2.FONT_HERSHEY_SIMPLEX 70 | 71 | while(True): 72 | ret, frame = cap.read() 73 | got_board = False 74 | corners, ids = find_charuco_board(frame, board, dictionary) 75 | if len(corners) > 0 : 76 | valid, rvec, tvec = cv2.aruco.estimatePoseCharucoBoard(corners, ids, board, intrinsics, dist_coeffs) 77 | if valid == True: 78 | org_frame = np.copy(frame) 79 | cv2.aruco.drawAxis(frame, intrinsics, dist_coeffs, rvec, tvec, 0.2) 80 | got_board = True 81 | p3d = [tvec[0][0], tvec[1][0], tvec[2][0]] 82 | 83 | # draw the coordinates 84 | cv2.putText(frame,"{0:.3f}".format(p3d[0]), (100,200), font, 4,(0,0,255), 6, cv2.LINE_AA) 85 | cv2.putText(frame,"{0:.3f}".format(p3d[1]), (100,400), font, 4,(0,255,0), 6, cv2.LINE_AA) 86 | cv2.putText(frame,"{0:.3f}".format(p3d[2]), (100,600), font, 4,(255,0,0), 6, cv2.LINE_AA) 87 | 88 | 89 | key = cv2.waitKey(1) 90 | if key == 27: # ESC 91 | cv2.destroyAllWindows() 92 | break 93 | 94 | cv2.imshow('frame', frame) 95 | 96 | 97 | 98 | 99 | -------------------------------------------------------------------------------- /webcam/sample-data/calibration.json: -------------------------------------------------------------------------------- 1 | { 2 | "calibrationDate": "2018-10-08 15:32:40.781436", 3 | "cameraResolution": { 4 | "type_id": "opencv-matrix", 5 | "rows": 2, 6 | "cols": 1, 7 | "dt": "d", 8 | "data": [ 720.0, 1280.0 ] 9 | }, 10 | "cameraMatrix": { 11 | "type_id": "opencv-matrix", 12 | "rows": 3, 13 | "cols": 3, 14 | "dt": "d", 15 | "data": [ 1.0036890509044972e+03, 0.0, 6.3670897816398144e+02, 16 | 0.0, 1.0036890509044972e+03, 4.1429682375533667e+02, 0.0, 17 | 0.0, 1.0 ] 18 | }, 19 | "dist_coeffs": { 20 | "type_id": "opencv-matrix", 21 | "rows": 14, 22 | "cols": 1, 23 | "dt": "d", 24 | "data": [ -8.5188812484719122e-03, -4.4933351860255627e-01, 25 | 5.7140445300074899e-03, -1.2610711736297426e-03, 26 | 2.6073694779700285e-01, -1.3493827802828759e-01, 27 | 1.0285916634349823e-01, -3.4395347152192784e-01, 0.0, 0.0, 28 | 0.0, 0.0, 0.0, 0.0 ] 29 | } 30 | } 31 | -------------------------------------------------------------------------------- /webcam/shared.py: -------------------------------------------------------------------------------- 1 | # 2 | # shared code between samples 3 | # 4 | 5 | import numpy as np 6 | import cv2 7 | def detect_aruco_markers(img, dictionary): 8 | corner_criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 100, 0.00001) 9 | gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) 10 | corners, ids, rejectedImgPoints = cv2.aruco.detectMarkers(gray, dictionary) 11 | if len(corners)>0: 12 | for corner in corners: 13 | cv2.cornerSubPix(gray, corner, winSize=(3,3), zeroZone=(-1,-1), criteria=corner_criteria) 14 | return corners, ids 15 | --------------------------------------------------------------------------------