├── .gitattributes
├── wide.jpg
├── normal.jpg
├── pattern.png
├── pairs
├── .DS_Store
├── left_01.png
├── left_02.png
├── left_03.png
├── left_04.png
├── left_05.png
├── left_06.png
├── left_07.png
├── left_08.png
├── left_09.png
├── left_10.png
├── left_11.png
├── left_12.png
├── left_13.png
├── left_14.png
├── left_15.png
├── left_16.png
├── left_17.png
├── left_18.png
├── left_19.png
├── left_20.png
├── left_21.png
├── left_22.png
├── left_24.png
├── left_25.png
├── left_26.png
├── left_27.png
├── left_28.png
├── left_29.png
├── left_30.png
├── left_31.png
├── left_32.png
├── left_33.png
├── left_34.png
├── left_35.png
├── left_36.png
├── left_37.png
├── left_38.png
├── left_39.png
├── left_40.png
├── left_41.png
├── left_42.png
├── left_43.png
├── left_44.png
├── left_45.png
├── left_46.png
├── left_47.png
├── left_48.png
├── left_49.png
├── left_50.png
├── right_01.png
├── right_02.png
├── right_03.png
├── right_04.png
├── right_05.png
├── right_06.png
├── right_07.png
├── right_08.png
├── right_09.png
├── right_10.png
├── right_11.png
├── right_12.png
├── right_13.png
├── right_14.png
├── right_15.png
├── right_16.png
├── right_17.png
├── right_18.png
├── right_19.png
├── right_20.png
├── right_21.png
├── right_22.png
├── right_23.png
├── right_24.png
├── right_25.png
├── right_26.png
├── right_27.png
├── right_28.png
├── right_29.png
├── right_30.png
├── right_31.png
├── right_32.png
├── right_33.png
├── right_34.png
├── right_35.png
├── right_36.png
├── right_37.png
├── right_38.png
├── right_39.png
├── right_40.png
├── right_41.png
├── right_42.png
├── right_43.png
├── right_44.png
├── right_45.png
├── right_46.png
├── right_47.png
├── right_48.png
├── right_49.png
└── right_50.png
├── scenes
├── photo.png
├── dm-tune.jpg
├── dm-tune-example.jpg
├── scene_1280x480_1.png
├── scene_1280x480_2.png
├── scene_1280x480_3.png
├── scene_1280x480_4.png
├── scene_1280x480_5.png
├── scene_1280x480_6.png
├── scene_1280x480_7.png
├── scene_1280x480_8.png
├── scene_1280x480_9.png
├── scene_1280x480_10.png
├── scene_1280x480_11.png
├── scene_1280x480_12.png
├── scene_1280x480_13.png
├── scene_1280x480_14.png
├── scene_1280x480_15.png
├── scene_1280x480_16.png
├── scene_1280x480_17.png
├── scene_1280x480_18.png
├── scene_1280x480_19.png
├── scene_1280x480_20.png
├── scene_1280x480_21.png
├── scene_1280x480_22.png
├── scene_1280x480_23.png
├── scene_1280x480_24.png
├── scene_1280x480_25.png
├── scene_1280x480_26.png
├── scene_1280x480_27.png
├── scene_1280x480_28.png
├── scene_1280x480_29.png
├── scene_1280x480_30.png
├── scene_1280x480_31.png
├── scene_1280x480_32.png
├── scene_1280x480_33.png
├── scene_1280x480_34.png
├── scene_1280x480_35.png
├── scene_1280x480_36.png
├── scene_1280x480_37.png
├── scene_1280x480_38.png
├── scene_1280x480_39.png
├── scene_1280x480_40.png
├── scene_1280x480_41.png
├── scene_1280x480_42.png
├── scene_1280x480_43.png
├── scene_1280x480_44.png
├── scene_1280x480_45.png
├── scene_1280x480_46.png
├── scene_1280x480_47.png
├── scene_1280x480_48.png
├── scene_1280x480_49.png
└── scene_1280x480_50.png
├── rectifyed_left.jpg
├── rectifyed_right.jpg
├── undistorted_left.jpg
├── undistorted_right.jpg
├── calibration_data
├── .DS_Store
└── 240p
│ ├── camera_calibration_left.npz
│ ├── camera_calibration_right.npz
│ └── stereo_camera_calibration.npz
├── 3dmap_set.txt
├── README.md
├── 3_pairs_cut.py
├── 1_test.py
├── buster-opencv-notice.md
├── 2_chess_cycle.py
├── 6_dm_video.py
├── 7_2d_map.py
├── 5_dm_tune.py
├── 4_calibration_fisheye.py
└── LICENSE
/.gitattributes:
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1 | # Auto detect text files and perform LF normalization
2 | * text=auto
3 |
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/wide.jpg:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/wide.jpg
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/normal.jpg:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/normal.jpg
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/pattern.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pattern.png
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/pairs/.DS_Store:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/.DS_Store
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/pairs/left_01.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_01.png
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/pairs/left_02.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_02.png
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/pairs/left_03.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_03.png
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/pairs/left_04.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_04.png
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/pairs/left_05.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_05.png
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/pairs/left_06.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_06.png
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/pairs/left_07.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_07.png
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/pairs/left_08.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_08.png
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/pairs/left_09.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_09.png
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/pairs/left_10.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_10.png
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/pairs/left_11.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_11.png
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/pairs/left_12.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_12.png
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/pairs/left_13.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_13.png
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/pairs/left_14.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_14.png
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/pairs/left_15.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_15.png
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/pairs/left_16.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_16.png
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/pairs/left_17.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_17.png
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/pairs/left_18.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_18.png
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/pairs/left_19.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_19.png
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/pairs/left_20.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_20.png
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/pairs/left_21.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_21.png
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/pairs/left_22.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_22.png
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/pairs/left_24.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_24.png
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/pairs/left_25.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_25.png
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/pairs/left_26.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_26.png
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/pairs/left_27.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_27.png
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/pairs/left_28.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_28.png
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/pairs/left_29.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_29.png
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/pairs/left_30.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_30.png
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/pairs/left_31.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_31.png
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/pairs/left_32.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_32.png
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/pairs/left_33.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_33.png
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/pairs/left_34.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_34.png
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/pairs/left_35.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_35.png
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/pairs/left_36.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_36.png
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/pairs/left_37.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_37.png
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/pairs/left_38.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_38.png
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/pairs/left_39.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_39.png
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/pairs/left_40.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_40.png
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/pairs/left_41.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_41.png
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/pairs/left_42.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_42.png
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/pairs/left_43.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_43.png
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/pairs/left_44.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_44.png
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/pairs/left_45.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_45.png
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/pairs/left_46.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_46.png
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/pairs/left_47.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_47.png
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/pairs/left_48.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_48.png
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/pairs/left_49.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_49.png
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/pairs/left_50.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/left_50.png
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/scenes/photo.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/scenes/photo.png
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/pairs/right_01.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_01.png
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/pairs/right_02.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_02.png
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/pairs/right_03.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_03.png
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/pairs/right_04.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_04.png
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/pairs/right_05.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_05.png
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/pairs/right_06.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_06.png
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/pairs/right_07.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_07.png
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/pairs/right_08.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_08.png
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/pairs/right_09.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_09.png
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/pairs/right_10.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_10.png
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/pairs/right_11.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_11.png
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/pairs/right_12.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_12.png
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/pairs/right_13.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_13.png
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/pairs/right_14.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_14.png
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/pairs/right_15.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_15.png
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/pairs/right_16.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_16.png
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/pairs/right_17.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_17.png
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/pairs/right_18.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_18.png
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/pairs/right_19.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_19.png
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/pairs/right_20.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_20.png
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/pairs/right_21.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_21.png
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/pairs/right_22.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_22.png
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/pairs/right_23.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_23.png
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/pairs/right_24.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_24.png
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/pairs/right_25.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_25.png
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/pairs/right_26.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_26.png
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/pairs/right_27.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_27.png
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/pairs/right_28.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_28.png
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/pairs/right_29.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_29.png
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/pairs/right_30.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_30.png
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/pairs/right_31.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_31.png
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/pairs/right_32.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_32.png
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/pairs/right_33.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_33.png
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/pairs/right_34.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_34.png
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/pairs/right_35.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_35.png
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/pairs/right_36.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_36.png
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/pairs/right_37.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_37.png
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/pairs/right_38.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_38.png
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/pairs/right_39.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_39.png
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/pairs/right_40.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_40.png
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/pairs/right_41.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_41.png
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/pairs/right_42.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_42.png
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/pairs/right_43.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_43.png
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/pairs/right_44.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_44.png
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/pairs/right_45.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_45.png
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/pairs/right_46.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_46.png
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/pairs/right_47.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_47.png
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/pairs/right_48.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_48.png
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/pairs/right_49.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_49.png
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/pairs/right_50.png:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/pairs/right_50.png
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/rectifyed_left.jpg:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/rectifyed_left.jpg
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/rectifyed_right.jpg:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/rectifyed_right.jpg
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/scenes/dm-tune.jpg:
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https://raw.githubusercontent.com/realizator/stereopi-fisheye-robot/HEAD/scenes/dm-tune.jpg
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1 | {
2 | "SADWindowSize":7,
3 | "minDisparity":42,
4 | "numberOfDisparities":16,
5 | "preFilterCap":29,
6 | "preFilterSize":7,
7 | "speckleRange":0,
8 | "speckleWindowSize":2,
9 | "textureThreshold":31,
10 | "uniquenessRatio":9
11 | }
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/README.md:
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1 | StereoPi fisheye robot tutorial scripts
2 | ===========
3 |
4 | Set of StereoPi Fisheye Robot tutorial scripts for StereoPi board with CM3/3+ inside.
5 |
6 | Was tested in the following environment:
7 | * Raspbian Buster (kernel 4.19.57-v7+)
8 | * Python 3.7.3
9 | * OpenCV 3.4.3 or 4.1.0.25 (pre-compiled, 'pip' from Python Wheels)
10 | * Picamera 1.13
11 |
12 | Related article: https://medium.com/stereopi/a-robot-on-stereopi-part-1-fisheye-cameras-92aa56e73a94
13 | Related 2nd article: https://stereopi.com/blog/opencv-comparing-speed-c-and-python-code-raspberry-pi-stereo-vision
14 |
15 | ### Updated Buster image (Python and C++ code) 4.7 Gb, for a 16 Gb eMMC or micro SD card:
16 |
17 | [Google drive](https://drive.google.com/file/d/1xlkvZMl9gJGm4Gy1oVlGknHywDnvy5gS/view?usp=sharing)
18 |
19 | ### Buster Raspbian OpenCV image, OCT 2024 (Python code only, 2.28Gb, needs 8Gb micro SD or eMMC):
20 |
21 | [MediaFire](https://www.mediafire.com/folder/nzr90vj8wp1l3/StereoPi_Images)
22 |
23 |
24 | ### Want to prepare OpenCV Raspbian Buster image by yourself?
25 |
26 | Follow this guide: [buster-opencv-notice.md](https://github.com/realizator/stereopi-fisheye-robot/blob/master/buster-opencv-notice.md)
27 |
28 | If you did Raspbian update, and stereoscopic capture command (like 'raspistill -3d sbs') hangs your StereoPi - please do 'sudo rpi-update' to fix it.
29 |
30 | ### Brief scripts description:
31 |
32 | **1_test.py** - starts camera preview, save captured image if 'Q' button is pressed.
33 | align.
34 |
35 | **2_chess_cycle.py** - takes a series of photos for stereopair calibration, shows count
36 | down timer. You need a printed chessboard with 9x6 parameters (file "pattern.png" included).
37 |
38 | **3_pairs_cut.py** - just cuts all captured photos to left and right images.
39 |
40 | **4_calibration_fisheye.py** - calibrate StereoPi cameas setup using pairs from script 4.
41 |
42 | **5_dm_tune.py** - script for fine tune of disparity map settings.
43 |
44 | **6_dm_video.py** - builds disparity map in real time.
45 |
46 |
47 | **7_2d_map.py** - builds 2D map from the depth map.
48 |
49 |
50 |
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/3_pairs_cut.py:
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1 | # Copyright (C) 2019 Eugene a.k.a. Realizator, stereopi.com, virt2real team
2 | #
3 | # This file is part of StereoPi tutorial scripts.
4 | #
5 | # StereoPi tutorial is free software: you can redistribute it
6 | # and/or modify it under the terms of the GNU General Public License
7 | # as published by the Free Software Foundation, either version 3 of the
8 | # License, or (at your option) any later version.
9 | #
10 | # StereoPi tutorial is distributed in the hope that it will be useful,
11 | # but WITHOUT ANY WARRANTY; without even the implied warranty of
12 | # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
13 | # GNU General Public License for more details.
14 | #
15 | # You should have received a copy of the GNU General Public License
16 | # along with StereoPi tutorial.
17 | # If not, see .
18 | #
19 | # <><><> SPECIAL THANKS: <><><>
20 | #
21 | # Thanks to Adrian and http://pyimagesearch.com, as a lot of
22 | # code in this tutorial was taken from his lessons.
23 | #
24 | # Thanks to RPi-tankbot project: https://github.com/Kheiden/RPi-tankbot
25 | #
26 | # Thanks to rakali project: https://github.com/sthysel/rakali
27 |
28 |
29 | import cv2
30 | import os
31 |
32 | # Global variables preset
33 | total_photos = 50
34 |
35 | # Photos to be cutted resolution
36 | photo_width = 1280
37 | photo_height = 480
38 |
39 | # Left and right images resolution
40 | img_width = 640
41 | img_height = 480
42 |
43 | # Visualization options
44 | ShowImages = False
45 |
46 | # Counter setup
47 | photo_counter = 0
48 |
49 | # Main pair cut cycle
50 | if (os.path.isdir("./pairs")==False):
51 | os.makedirs("./pairs")
52 | while photo_counter != total_photos:
53 | photo_counter +=1
54 | filename = './scenes/scene_'+str(photo_width)+'x'+str(photo_height)+\
55 | '_'+str(photo_counter) + '.png'
56 | if os.path.isfile(filename) == False:
57 | print ("No file named "+filename)
58 | continue
59 | pair_img = cv2.imread(filename,-1)
60 |
61 | if (ShowImages):
62 | cv2.imshow("ImagePair", pair_img)
63 | cv2.waitKey(0)
64 | imgLeft = pair_img [0:img_height,0:img_width] #Y+H and X+W
65 | imgRight = pair_img [0:img_height,img_width:photo_width]
66 | leftName = './pairs/left_'+str(photo_counter).zfill(2)+'.png'
67 | rightName = './pairs/right_'+str(photo_counter).zfill(2)+'.png'
68 | cv2.imwrite(leftName, imgLeft)
69 | cv2.imwrite(rightName, imgRight)
70 | print ('Pair No '+str(photo_counter)+' saved.')
71 |
72 | print ('End cycle')
73 |
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/1_test.py:
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1 | # Copyright (C) 2019 Eugene a.k.a. Realizator, stereopi.com, virt2real team
2 | #
3 | # This file is part of StereoPi tutorial scripts.
4 | #
5 | # StereoPi tutorial is free software: you can redistribute it
6 | # and/or modify it under the terms of the GNU General Public License
7 | # as published by the Free Software Foundation, either version 3 of the
8 | # License, or (at your option) any later version.
9 | #
10 | # StereoPi tutorial is distributed in the hope that it will be useful,
11 | # but WITHOUT ANY WARRANTY; without even the implied warranty of
12 | # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
13 | # GNU General Public License for more details.
14 | #
15 | # You should have received a copy of the GNU General Public License
16 | # along with StereoPi tutorial.
17 | # If not, see .
18 | #
19 | # <><><> SPECIAL THANKS: <><><>
20 | #
21 | # Thanks to Adrian and http://pyimagesearch.com, as a lot of
22 | # code in this tutorial was taken from his lessons.
23 | #
24 | # Thanks to RPi-tankbot project: https://github.com/Kheiden/RPi-tankbot
25 | #
26 | # Thanks to rakali project: https://github.com/sthysel/rakali
27 |
28 |
29 | import picamera
30 | from picamera import PiCamera
31 | import time
32 | import cv2
33 | import numpy as np
34 | import os
35 | from datetime import datetime
36 |
37 | # User quit method message
38 | print("You can press 'Q' to quit this script.")
39 |
40 | # File for captured image
41 | filename = './scenes/photo.png'
42 |
43 | # Camera settimgs
44 | cam_width = 1280
45 | cam_height = 480
46 |
47 | # Final image capture settings
48 | scale_ratio = 0.5
49 |
50 | # Camera resolution height must be dividable by 16, and width by 32
51 | cam_width = int((cam_width+31)/32)*32
52 | cam_height = int((cam_height+15)/16)*16
53 | print ("Camera resolution: "+str(cam_width)+" x "+str(cam_height))
54 |
55 | # Buffer for captured image settings
56 | img_width = int (cam_width * scale_ratio)
57 | img_height = int (cam_height * scale_ratio)
58 | capture = np.zeros((img_height, img_width, 4), dtype=np.uint8)
59 | print ("Scaled image resolution: "+str(img_width)+" x "+str(img_height))
60 |
61 | # Initialize the camera
62 | camera = PiCamera(stereo_mode='side-by-side',stereo_decimate=False)
63 | camera.resolution=(cam_width, cam_height)
64 | camera.framerate = 20
65 | #camera.hflip = True
66 |
67 | t0 = datetime.now()
68 | counter = 0
69 | avgtime = 0
70 | # Capture frames from the camera
71 | for frame in camera.capture_continuous(capture, format="bgra", use_video_port=True, resize=(img_width,img_height)):
72 | counter+=1
73 | cv2.imshow("pair", frame)
74 | key = cv2.waitKey(1) & 0xFF
75 | # if the `q` key was pressed, break from the loop and save last image
76 | if key == ord("q") :
77 | t1 = datetime.now()
78 | timediff = t1-t0
79 | print ("Average time between frames: " + str(avgtime))
80 | print ("Frames: " + str(counter) + " Time: " + str(timediff.total_seconds())+ " Average FPS: " + str(counter/timediff.total_seconds()))
81 | if (os.path.isdir("./scenes")==False):
82 | os.makedirs("./scenes")
83 | cv2.imwrite(filename, frame)
84 | exit(0)
85 | break
86 |
87 |
88 |
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/buster-opencv-notice.md:
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1 | ### Critical notice!
2 | In the latest Raspbian kernels stereoscopic support has been occasionally broken by implementing new AWB algorithm. You can read some details [here](https://github.com/raspberrypi/firmware/issues/1253). Kernels affected: 4.19.57 and up to 4.19.97. Our Raspbian image provided has no such a problem (as it is based on older kernel).
3 |
4 | The solution (**obsolete**):
5 |
6 | after boot run once this command before accessing your cameras:
7 | ```
8 | sudo vcdbg set awb_mode 0
9 | ```
10 | This will turn AWB algo to the previous mode, and stereo works again untill next reboot. So run this command after reboot, or add it to your autorun script.
11 |
12 | New solution (**recommended**):
13 |
14 | `sudo rpi-update`
15 |
16 | As of 10 of April, 2020, issue is fixed in the latest firmware update. So just use rpi-update.
17 |
18 |
19 | # Installing OpenCV 3.x or 4.x on Raspbian Buster:
20 |
21 | #### 1. Download Raspbian Buster and write image to your micro SD card.
22 |
23 |
24 | #### 2. Enable two cameras support:
25 | Put [dt-blob.bin](http://wiki.stereopi.com/files/dt-blob.bin.zip) file to /BOOT partition. Do not forget to extract it from ZIP archive.
26 |
27 | #### 3. First boot
28 |
29 | After the first boot you'll see setup wizard.
30 |
31 | Choose all settings you need, install all recommended updates and reboot the StereoPi.
32 |
33 | Please do 'sudo rpi-update' after that. This will fix stereoscopic mode.
34 |
35 | Enable camera:
36 |
37 | `sudo raspi-config`
38 |
39 | Go to "Interfacing options", choose "Enable camera", press "Yes", reboot your system.
40 |
41 | #### 4. Set python 3 as a default:
42 |
43 | `sudo nano ~/.bashrc`
44 |
45 | add this row at the end of file:
46 |
47 | `alias python='/usr/bin/python3'`
48 |
49 | Save the file (Esc X X, "yes").
50 |
51 | Activate new settings:
52 |
53 | `source ~/.bashrc`
54 |
55 | Check if the settings are applied correctly.
56 |
57 | `python`
58 |
59 | You should see "Python 3.7.3" in the first row.
60 |
61 | If you see "Python 2.7.x" - please repeat previous steps.
62 |
63 | (Type exit(0) to exit Python command line).
64 |
65 | #### 5. Install OpenCV with PiWheels:
66 |
67 | Workaround: to avoid "undefined symbol: __atomic_fetch_add8" error while "import cv2",
68 | please install specific version of OpenCV.
69 |
70 | For OpenCV 3.x use:
71 |
72 | `sudo pip3 install opencv-python==3.4.6.27`
73 |
74 | For OpenCV 4.x use:
75 |
76 | `sudo pip3 install opencv-contrib-python==4.1.0.25`
77 |
78 | #### 6. Install additional libs:
79 |
80 | ```
81 | sudo apt-get install libhdf5-dev
82 | sudo apt-get install libhdf5-serial-dev
83 | sudo apt-get install libatlas-base-dev
84 | sudo apt-get install libjasper-dev
85 | sudo apt-get install libqtgui4
86 | sudo apt-get install libqt4-test
87 | ```
88 |
89 | You may also need matplotlib. Go this way:
90 |
91 | `sudo pip3 install matplotlib`
92 |
93 | #### 7. To check if everything Ok try to run our first test script:
94 |
95 | `python 1_test.py`
96 |
97 | You should see preview image. Press 'Q' for exit.
98 |
99 | #### 8. Check raspistill 3D mode:
100 |
101 | `raspistill -3d sbs -o 1.jpg`
102 |
103 | You should see 5 seconds preview, and stereoscopic image "1.jpg" should be saved after
104 | running this code.
105 |
106 | #### 9. How to avoid occasional stereoscopic support breaking?
107 |
108 | Stereoscopic support is broken on kernels from 4.19.57 and up to 4.19.97
109 |
110 | To fix it, just use "sudo rpi-update". This fix works from ~10 of April, 2020.
111 |
112 | Stay tuned!
113 |
114 | And good luck with your OpenCV experiments! :-)
115 |
--------------------------------------------------------------------------------
/2_chess_cycle.py:
--------------------------------------------------------------------------------
1 | # Copyright (C) 2019 Eugene a.k.a. Realizator, stereopi.com, virt2real team
2 | #
3 | # This file is part of StereoPi tutorial scripts.
4 | #
5 | # StereoPi tutorial is free software: you can redistribute it
6 | # and/or modify it under the terms of the GNU General Public License
7 | # as published by the Free Software Foundation, either version 3 of the
8 | # License, or (at your option) any later version.
9 | #
10 | # StereoPi tutorial is distributed in the hope that it will be useful,
11 | # but WITHOUT ANY WARRANTY; without even the implied warranty of
12 | # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
13 | # GNU General Public License for more details.
14 | #
15 | # You should have received a copy of the GNU General Public License
16 | # along with StereoPi tutorial.
17 | # If not, see .
18 | #
19 | # <><><> SPECIAL THANKS: <><><>
20 | #
21 | # Thanks to Adrian and http://pyimagesearch.com, as a lot of
22 | # code in this tutorial was taken from his lessons.
23 | #
24 | # Thanks to RPi-tankbot project: https://github.com/Kheiden/RPi-tankbot
25 | #
26 | # Thanks to rakali project: https://github.com/sthysel/rakali
27 |
28 | import os
29 | import time
30 | from datetime import datetime
31 | import picamera
32 | from picamera import PiCamera
33 | import cv2
34 | import numpy as np
35 |
36 | # User quit method message
37 | print("You can press 'Q' to quit this script.")
38 |
39 | # Photo session settings
40 | total_photos = 50 # Number of images to take
41 | countdown = 5 # Interval for count-down timer, seconds
42 | font=cv2.FONT_HERSHEY_SIMPLEX # Cowntdown timer font
43 |
44 | # Camera settimgs
45 | cam_width = 1280 # Cam sensor width settings
46 | cam_height = 480 # Cam sensor height settings
47 |
48 | # Final image capture settings
49 | scale_ratio = 1
50 |
51 | # Camera resolution height must be dividable by 16, and width by 32
52 | cam_width = int((cam_width+31)/32)*32
53 | cam_height = int((cam_height+15)/16)*16
54 | print ("Camera resolution: "+str(cam_width)+" x "+str(cam_height))
55 |
56 | # Buffer for captured image settings
57 | img_width = int (cam_width * scale_ratio)
58 | img_height = int (cam_height * scale_ratio)
59 | capture = np.zeros((img_height, img_width, 4), dtype=np.uint8)
60 | print ("Scaled image resolution: "+str(img_width)+" x "+str(img_height))
61 |
62 | # Initialize the camera
63 | camera = PiCamera(stereo_mode='side-by-side', stereo_decimate=False)
64 | camera.resolution=(cam_width, cam_height)
65 | camera.framerate = 20
66 | #camera.hflip = True
67 |
68 | # Lets start taking photos!
69 | counter = 0
70 | t2 = datetime.now()
71 | print ("Starting photo sequence")
72 | for frame in camera.capture_continuous(capture, format="bgra", \
73 | use_video_port=True, resize=(img_width,img_height)):
74 | t1 = datetime.now()
75 | cntdwn_timer = countdown - int ((t1-t2).total_seconds())
76 |
77 | # If cowntdown is zero - let's record next image
78 | if cntdwn_timer == -1:
79 | counter += 1
80 | filename = './scenes/scene_'+str(img_width)+'x'+str(img_height)+'_'+\
81 | str(counter) + '.png'
82 | cv2.imwrite(filename, frame)
83 | print (' ['+str(counter)+' of '+str(total_photos)+'] '+filename)
84 | t2 = datetime.now()
85 | time.sleep(1)
86 | cntdwn_timer = 0 # To avoid "-1" timer display
87 | next
88 |
89 | # Draw cowntdown counter, seconds
90 | cv2.putText(frame, str(cntdwn_timer), (50,50), font, 2.0, (0,0,255),4, cv2.LINE_AA)
91 | cv2.imshow("pair", frame)
92 | key = cv2.waitKey(1) & 0xFF
93 |
94 | # Press 'Q' key to quit, or wait till all photos are taken
95 | if (key == ord("q")) | (counter == total_photos):
96 | break
97 |
98 |
99 | print ("Photo sequence finished")
100 |
101 |
--------------------------------------------------------------------------------
/6_dm_video.py:
--------------------------------------------------------------------------------
1 | # Copyright (C) 2019 Eugene a.k.a. Realizator, stereopi.com, virt2real team
2 | #
3 | # This file is part of StereoPi tutorial scripts.
4 | #
5 | # StereoPi tutorial is free software: you can redistribute it
6 | # and/or modify it under the terms of the GNU General Public License
7 | # as published by the Free Software Foundation, either version 3 of the
8 | # License, or (at your option) any later version.
9 | #
10 | # StereoPi tutorial is distributed in the hope that it will be useful,
11 | # but WITHOUT ANY WARRANTY; without even the implied warranty of
12 | # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
13 | # GNU General Public License for more details.
14 | #
15 | # You should have received a copy of the GNU General Public License
16 | # along with StereoPi tutorial.
17 | # If not, see .
18 | #
19 | # <><><> SPECIAL THANKS: <><><>
20 | #
21 | # Thanks to Adrian and http://pyimagesearch.com, as a lot of
22 | # code in this tutorial was taken from his lessons.
23 | #
24 | # Thanks to RPi-tankbot project: https://github.com/Kheiden/RPi-tankbot
25 | #
26 | # Thanks to rakali project: https://github.com/sthysel/rakali
27 |
28 |
29 | from picamera import PiCamera
30 | import time
31 | import cv2
32 | import numpy as np
33 | import json
34 | from datetime import datetime
35 |
36 | print ("You can press Q to quit this script!")
37 | time.sleep (5)
38 |
39 | # Depth map default preset
40 | SWS = 5
41 | PFS = 5
42 | PFC = 29
43 | MDS = -30
44 | NOD = 160
45 | TTH = 100
46 | UR = 10
47 | SR = 14
48 | SPWS = 100
49 |
50 | # Use the whole image or a stripe for depth map?
51 | useStripe = False
52 | dm_colors_autotune = True
53 | disp_max = -100000
54 | disp_min = 10000
55 |
56 | # Camera settimgs
57 | cam_width = 1280
58 | cam_height = 480
59 |
60 | # Final image capture settings
61 | scale_ratio = 0.5
62 |
63 | # Camera resolution height must be dividable by 16, and width by 32
64 | cam_width = int((cam_width+31)/32)*32
65 | cam_height = int((cam_height+15)/16)*16
66 | print ("Used camera resolution: "+str(cam_width)+" x "+str(cam_height))
67 |
68 | # Buffer for captured image settings
69 | img_width = int (cam_width * scale_ratio)
70 | img_height = int (cam_height * scale_ratio)
71 | capture = np.zeros((img_height, img_width, 4), dtype=np.uint8)
72 | print ("Scaled image resolution: "+str(img_width)+" x "+str(img_height))
73 |
74 | # Initialize the camera
75 | camera = PiCamera(stereo_mode='side-by-side',stereo_decimate=False)
76 | camera.resolution=(cam_width, cam_height)
77 | camera.framerate = 20
78 | #camera.hflip = True
79 |
80 | # Initialize interface windows
81 | cv2.namedWindow("Image")
82 | cv2.moveWindow("Image", 50,100)
83 | cv2.namedWindow("left")
84 | cv2.moveWindow("left", 450,100)
85 | cv2.namedWindow("right")
86 | cv2.moveWindow("right", 850,100)
87 |
88 |
89 | disparity = np.zeros((img_width, img_height), np.uint8)
90 | sbm = cv2.StereoBM_create(numDisparities=0, blockSize=21)
91 |
92 |
93 | def stereo_depth_map(rectified_pair):
94 | global disp_max
95 | global disp_min
96 | dmLeft = rectified_pair[0]
97 | dmRight = rectified_pair[1]
98 | disparity = sbm.compute(dmLeft, dmRight)
99 | local_max = disparity.max()
100 | local_min = disparity.min()
101 | if (dm_colors_autotune):
102 | disp_max = max(local_max,disp_max)
103 | disp_min = min(local_min,disp_min)
104 | local_max = disp_max
105 | local_min = disp_min
106 | print(disp_max, disp_min)
107 | disparity_grayscale = (disparity-local_min)*(65535.0/(local_max-local_min))
108 | #disparity_grayscale = (disparity+208)*(65535.0/1000.0) # test for jumping colors prevention
109 | disparity_fixtype = cv2.convertScaleAbs(disparity_grayscale, alpha=(255.0/65535.0))
110 | disparity_color = cv2.applyColorMap(disparity_fixtype, cv2.COLORMAP_JET)
111 | cv2.imshow("Image", disparity_color)
112 | key = cv2.waitKey(1) & 0xFF
113 | if key == ord("q"):
114 | quit();
115 | return disparity_color
116 |
117 | def load_map_settings( fName ):
118 | global SWS, PFS, PFC, MDS, NOD, TTH, UR, SR, SPWS, loading_settings
119 | print('Loading parameters from file...')
120 | f=open(fName, 'r')
121 | data = json.load(f)
122 | SWS=data['SADWindowSize']
123 | PFS=data['preFilterSize']
124 | PFC=data['preFilterCap']
125 | MDS=data['minDisparity']
126 | NOD=data['numberOfDisparities']
127 | TTH=data['textureThreshold']
128 | UR=data['uniquenessRatio']
129 | SR=data['speckleRange']
130 | SPWS=data['speckleWindowSize']
131 | #sbm.setSADWindowSize(SWS)
132 | sbm.setPreFilterType(1)
133 | sbm.setPreFilterSize(PFS)
134 | sbm.setPreFilterCap(PFC)
135 | sbm.setMinDisparity(MDS)
136 | sbm.setNumDisparities(NOD)
137 | sbm.setTextureThreshold(TTH)
138 | sbm.setUniquenessRatio(UR)
139 | sbm.setSpeckleRange(SR)
140 | sbm.setSpeckleWindowSize(SPWS)
141 | f.close()
142 | print ('Parameters loaded from file '+fName)
143 |
144 |
145 | load_map_settings ("3dmap_set.txt")
146 | try:
147 | npzfile = np.load('./calibration_data/{}p/stereo_camera_calibration.npz'.format(img_height))
148 | except:
149 | print("Camera calibration data not found in cache, file ", './calibration_data/{}p/stereo_camera_calibration.npz'.format(img_height))
150 | exit(0)
151 |
152 | imageSize = tuple(npzfile['imageSize'])
153 | leftMapX = npzfile['leftMapX']
154 | leftMapY = npzfile['leftMapY']
155 | rightMapX = npzfile['rightMapX']
156 | rightMapY = npzfile['rightMapY']
157 |
158 |
159 |
160 | # capture frames from the camera
161 | for frame in camera.capture_continuous(capture, format="bgra", use_video_port=True, resize=(img_width,img_height)):
162 | t1 = datetime.now()
163 | pair_img = cv2.cvtColor (frame, cv2.COLOR_BGR2GRAY)
164 | imgLeft = pair_img [0:img_height,0:int(img_width/2)] #Y+H and X+W
165 | imgRight = pair_img [0:img_height,int(img_width/2):img_width] #Y+H and X+W
166 | imgL = cv2.remap(imgLeft, leftMapX, leftMapY, interpolation=cv2.INTER_LINEAR, borderMode=cv2.BORDER_CONSTANT)
167 | imgR = cv2.remap(imgRight, rightMapX, rightMapY, interpolation=cv2.INTER_LINEAR, borderMode=cv2.BORDER_CONSTANT)
168 |
169 | if (useStripe):
170 | imgRcut = imgR [80:160,0:int(img_width/2)]
171 | imgLcut = imgL [80:160,0:int(img_width/2)]
172 | else:
173 | imgRcut = imgR
174 | imgLcut = imgL
175 |
176 | rectified_pair = (imgLcut, imgRcut)
177 | disparity = stereo_depth_map(rectified_pair)
178 | # show the frame
179 | cv2.imshow("left", imgLcut)
180 | cv2.imshow("right", imgRcut)
181 |
182 | t2 = datetime.now()
183 | print ("DM build time: " + str(t2-t1))
184 |
185 |
186 |
--------------------------------------------------------------------------------
/7_2d_map.py:
--------------------------------------------------------------------------------
1 | # Copyright (C) 2019 Eugene a.k.a. Realizator, stereopi.com, virt2real team
2 | #
3 | # This file is part of StereoPi tutorial scripts.
4 | #
5 | # StereoPi tutorial is free software: you can redistribute it
6 | # and/or modify it under the terms of the GNU General Public License
7 | # as published by the Free Software Foundation, either version 3 of the
8 | # License, or (at your option) any later version.
9 | #
10 | # StereoPi tutorial is distributed in the hope that it will be useful,
11 | # but WITHOUT ANY WARRANTY; without even the implied warranty of
12 | # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
13 | # GNU General Public License for more details.
14 | #
15 | # You should have received a copy of the GNU General Public License
16 | # along with StereoPi tutorial.
17 | # If not, see .
18 | #
19 | # <><><> SPECIAL THANKS: <><><>
20 | #
21 | # Thanks to Adrian and http://pyimagesearch.com, as a lot of
22 | # code in this tutorial was taken from his lessons.
23 | #
24 | # Thanks to RPi-tankbot project: https://github.com/Kheiden/RPi-tankbot
25 | #
26 | # Thanks to rakali project: https://github.com/sthysel/rakali
27 |
28 |
29 | from picamera import PiCamera
30 | import time
31 | import cv2
32 | import numpy as np
33 | import json
34 | from datetime import datetime
35 |
36 | print ("You can press 'Q' to quit this script!")
37 | time.sleep (5)
38 |
39 | # Visualization settings
40 | showDisparity = True
41 | showUndistortedImages = True
42 | showColorizedDistanceLine = True
43 |
44 | # Depth map default preset
45 | SWS = 5
46 | PFS = 5
47 | PFC = 29
48 | MDS = -30
49 | NOD = 160
50 | TTH = 100
51 | UR = 10
52 | SR = 14
53 | SPWS = 100
54 |
55 | # Camera settimgs
56 | cam_width = 1280
57 | cam_height = 480
58 |
59 | # Final image capture settings
60 | scale_ratio = 0.5
61 |
62 | # Camera resolution height must be dividable by 16, and width by 32
63 | cam_width = int((cam_width+31)/32)*32
64 | cam_height = int((cam_height+15)/16)*16
65 | print ("Used camera resolution: "+str(cam_width)+" x "+str(cam_height))
66 |
67 | # Buffer for captured image settings
68 | img_width = int (cam_width * scale_ratio)
69 | img_height = int (cam_height * scale_ratio)
70 | capture = np.zeros((img_height, img_width, 4), dtype=np.uint8)
71 | print ("Scaled image resolution: "+str(img_width)+" x "+str(img_height))
72 |
73 | # Depth Map colors autotune
74 | autotune_min = 10000000
75 | autotune_max = -10000000
76 |
77 | # 3D points settings
78 | focal_length = 165.0 #taken from K matrix
79 | tx = 65 #taken from K matrix after calibration
80 | q = np.array([
81 | [1, 0, 0, -img_width/2],
82 | [0, 1, 0, -img_height/2],
83 | [0, 0, 0, focal_length],
84 | [0, 0, -1/tx,0]
85 | ])
86 |
87 |
88 | # Initialize the camera
89 | camera = PiCamera(stereo_mode='side-by-side',stereo_decimate=False)
90 | camera.resolution=(cam_width, cam_height)
91 | camera.framerate = 20
92 | #camera.hflip = True
93 |
94 | # Initialize interface windows
95 | cv2.namedWindow("Image")
96 | cv2.moveWindow("Image", 50,100)
97 | cv2.namedWindow("left")
98 | cv2.moveWindow("left", 450,100)
99 | cv2.namedWindow("right")
100 | cv2.moveWindow("right", 850,100)
101 |
102 |
103 | disparity = np.zeros((img_width, img_height), np.uint8)
104 | sbm = cv2.StereoBM_create(numDisparities=0, blockSize=21)
105 |
106 | def stereo_depth_map(rectified_pair):
107 | dmLeft = rectified_pair[0]
108 | dmRight = rectified_pair[1]
109 | disparity = sbm.compute(dmLeft, dmRight)
110 | local_max = disparity.max()
111 | local_min = disparity.min()
112 | #print(local_max, local_min)
113 | disparity_grayscale = (disparity-autotune_min)*(65535.0/(autotune_max-autotune_min))
114 | disparity_fixtype = cv2.convertScaleAbs(disparity_grayscale, alpha=(255.0/65535.0))
115 | disparity_color = cv2.applyColorMap(disparity_fixtype, cv2.COLORMAP_JET)
116 | if (showDisparity):
117 | cv2.imshow("Image", disparity_color)
118 | key = cv2.waitKey(1) & 0xFF
119 | if key == ord("q"):
120 | quit();
121 | return disparity_color, disparity_fixtype, disparity
122 |
123 | def load_map_settings( fName ):
124 | global SWS, PFS, PFC, MDS, NOD, TTH, UR, SR, SPWS, loading_settings
125 | print('Loading parameters from file...')
126 | f=open(fName, 'r')
127 | data = json.load(f)
128 | SWS=data['SADWindowSize']
129 | PFS=data['preFilterSize']
130 | PFC=data['preFilterCap']
131 | MDS=data['minDisparity']
132 | NOD=data['numberOfDisparities']
133 | TTH=data['textureThreshold']
134 | UR=data['uniquenessRatio']
135 | SR=data['speckleRange']
136 | SPWS=data['speckleWindowSize']
137 | #sbm.setSADWindowSize(SWS)
138 | sbm.setPreFilterType(1)
139 | sbm.setPreFilterSize(PFS)
140 | sbm.setPreFilterCap(PFC)
141 | sbm.setMinDisparity(MDS)
142 | sbm.setNumDisparities(NOD)
143 | sbm.setTextureThreshold(TTH)
144 | sbm.setUniquenessRatio(UR)
145 | sbm.setSpeckleRange(SR)
146 | sbm.setSpeckleWindowSize(SPWS)
147 | f.close()
148 | print ('Depth map settings has been loaded from the file '+fName)
149 |
150 | # Loading depth map settings
151 | load_map_settings ("3dmap_set.txt")
152 |
153 | # Loading stereoscopic calibration data
154 | try:
155 | npzfile = np.load('./calibration_data/{}p/stereo_camera_calibration.npz'.format(img_height))
156 | except:
157 | print("Camera calibration data not found in cache, file ", './calibration_data/{}p/stereo_camera_calibration.npz'.format(img_height))
158 | exit(0)
159 |
160 | imageSize = tuple(npzfile['imageSize'])
161 | leftMapX = npzfile['leftMapX']
162 | leftMapY = npzfile['leftMapY']
163 | rightMapX = npzfile['rightMapX']
164 | rightMapY = npzfile['rightMapY']
165 | QQ = npzfile['dispartityToDepthMap']
166 |
167 | map_width = 320
168 | map_height = 240
169 |
170 | min_y = 10000
171 | max_y = -10000
172 | min_x = 10000
173 | max_x = -10000
174 | # Capture the frames from the camera
175 | for frame in camera.capture_continuous(capture, format="bgra", use_video_port=True, resize=(img_width,img_height)):
176 | t1 = datetime.now()
177 | pair_img = cv2.cvtColor (frame, cv2.COLOR_BGR2GRAY)
178 | imgLeft = pair_img [0:img_height,0:int(img_width/2)] #Y+H and X+W
179 | imgRight = pair_img [0:img_height,int(img_width/2):img_width] #Y+H and X+W
180 | imgL = cv2.remap(imgLeft, leftMapX, leftMapY, interpolation=cv2.INTER_LINEAR, borderMode=cv2.BORDER_CONSTANT)
181 | imgR = cv2.remap(imgRight, rightMapX, rightMapY, interpolation=cv2.INTER_LINEAR, borderMode=cv2.BORDER_CONSTANT)
182 |
183 | # Taking a strip from our image for lidar-like mode (and saving CPU)
184 | imgRcut = imgR [80:160,0:int(img_width/2)]
185 | imgLcut = imgL [80:160,0:int(img_width/2)]
186 | rectified_pair = (imgLcut, imgRcut)
187 |
188 | # Disparity map calculation
189 | disparity, disparity_bw, native_disparity = stereo_depth_map(rectified_pair)
190 |
191 | maximized_line = native_disparity
192 |
193 | maxInColumns = np.amax(maximized_line,0)
194 | points = cv2.reprojectImageTo3D(maxInColumns, QQ)
195 | xy_projection = np.zeros((map_height , map_width, 1), dtype=np.uint8)
196 |
197 | # "Jumping colors" protection for depth map visualization
198 | if autotune_max < np.amax(maximized_line):
199 | autotune_max = np.amax(maximized_line)
200 | if autotune_min > np.amin(maximized_line):
201 | autotune_min = np.amin(maximized_line)
202 |
203 | # Choose "closest" points in each column
204 | maximized_line[0:80,] = maxInColumns
205 |
206 | # Colorizing final line
207 | max_line_tune = (maximized_line-autotune_min)*(65535.0/(autotune_max-autotune_min))
208 | max_line_gray = cv2.convertScaleAbs(max_line_tune, alpha=(255.0/65535.0))
209 |
210 | # Put all points to the 2D map
211 |
212 | # Change map_zoom to adjust visible range!
213 | map_zoom_y = int(map_height/(max_y-min_y))
214 | map_zoom_x = int(map_height/(max_x-min_x))
215 | for n, points in enumerate(points):
216 | cur_y = -points[0][0]
217 | cur_x = points[0][1]
218 | max_y = max(cur_y, max_y)
219 | min_y = min(cur_y, min_y)
220 | max_x = max(cur_x, max_x)
221 | min_x = min(cur_x, min_x)
222 | xx = int(cur_x*map_zoom_x) + int(map_width/2) # zero point is in the middle of the map
223 | yy = map_height - int((cur_y-min_y)*map_zoom_y) # zero point is at the bottom of the map
224 |
225 | # If the point fits on our 2D map - let's draw it!
226 | if (xx < map_width) and (xx >= 0) and (yy < map_height) and (yy >= 0):
227 | xy_projection[yy, xx] = max_line_gray[0,n]
228 |
229 | #print ("min_y = " + str(min_y) + " max_y = " + str(max_y) + " zoom_x = " + str(map_zoom_x) + " zoom_y = " + str(map_zoom_y))
230 | xy_projection_color = cv2.applyColorMap(xy_projection, cv2.COLORMAP_JET)
231 | max_line_color = cv2.applyColorMap(max_line_gray, cv2.COLORMAP_JET)
232 |
233 | # show the frame
234 | #print ("Autotune: min =", autotune_min, " max =", autotune_max)
235 | if (showUndistortedImages):
236 | cv2.imshow("left", imgLcut)
237 | cv2.imshow("right", imgRcut)
238 | if (showColorizedDistanceLine):
239 | cv2.imshow("Max distance line", max_line_color)
240 | cv2.imshow("XY projection", xy_projection_color)
241 | t2 = datetime.now()
242 | #print ("DM build time: " + str(t2-t1))
243 |
244 |
245 |
--------------------------------------------------------------------------------
/5_dm_tune.py:
--------------------------------------------------------------------------------
1 | # Copyright (C) 2019 Eugene a.k.a. Realizator, stereopi.com, virt2real team
2 | #
3 | # This file is part of StereoPi tutorial scripts.
4 | #
5 | # StereoPi tutorial is free software: you can redistribute it
6 | # and/or modify it under the terms of the GNU General Public License
7 | # as published by the Free Software Foundation, either version 3 of the
8 | # License, or (at your option) any later version.
9 | #
10 | # StereoPi tutorial is distributed in the hope that it will be useful,
11 | # but WITHOUT ANY WARRANTY; without even the implied warranty of
12 | # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
13 | # GNU General Public License for more details.
14 | #
15 | # You should have received a copy of the GNU General Public License
16 | # along with StereoPi tutorial.
17 | # If not, see .
18 | #
19 | # <><><> SPECIAL THANKS: <><><>
20 | #
21 | # Thanks to Adrian and http://pyimagesearch.com, as a lot of
22 | # code in this tutorial was taken from his lessons.
23 | #
24 | # Thanks to RPi-tankbot project: https://github.com/Kheiden/RPi-tankbot
25 | #
26 | # Thanks to rakali project: https://github.com/sthysel/rakali
27 |
28 |
29 | import cv2
30 | import os
31 | from picamera.array import PiRGBArray
32 | from picamera import PiCamera
33 | from matplotlib import pyplot as plt
34 | from matplotlib.widgets import Slider, Button
35 | import numpy as np
36 | import json
37 | import time
38 |
39 | # Global variables preset
40 | imageToDisp = './scenes/dm-tune.jpg'
41 | photo_width = 640
42 | photo_height = 240
43 | image_width = 320
44 | image_height = 240
45 |
46 | image_size = (image_width,image_height)
47 |
48 | if os.path.isfile(imageToDisp) == False:
49 | print ('Can not read image from file \"'+imageToDisp+'\"')
50 | # No image! Let's take it...
51 | print ("Taking photo...")
52 | camera = PiCamera(stereo_mode='side-by-side',stereo_decimate=False)
53 | camera.resolution=(photo_width, photo_height)
54 | #camera.hflip = True
55 | time.sleep(1)
56 | camera.capture(imageToDisp)
57 | print ("Done!")
58 |
59 | pair_img = cv2.imread(imageToDisp,0)
60 | # Read image and split it in a stereo pair
61 | print('Read and split image...')
62 | imgLeft = pair_img [0:photo_height,0:image_width] #Y+H and X+W
63 | imgRight = pair_img [0:photo_height,image_width:photo_width] #Y+H and X+W
64 |
65 | # Implementing calibration data
66 | print('Read calibration data and rectifying stereo pair...')
67 |
68 | try:
69 | npzfile = np.load('./calibration_data/{}p/stereo_camera_calibration.npz'.format(image_height))
70 | except:
71 | print("Camera calibration data not found in cache, file " & './calibration_data/{}p/stereo_camera_calibration.npz'.format(480))
72 | exit(0)
73 |
74 | imageSize = tuple(npzfile['imageSize'])
75 | leftMapX = npzfile['leftMapX']
76 | leftMapY = npzfile['leftMapY']
77 | rightMapX = npzfile['rightMapX']
78 | rightMapY = npzfile['rightMapY']
79 |
80 | width_left, height_left = imgLeft.shape[:2]
81 | width_right, height_right = imgRight.shape[:2]
82 |
83 | if 0 in [width_left, height_left, width_right, height_right]:
84 | print("Error: Can't remap image.")
85 |
86 | imgL = cv2.remap(imgLeft, leftMapX, leftMapY, interpolation=cv2.INTER_LINEAR, borderMode=cv2.BORDER_CONSTANT)
87 | imgR = cv2.remap(imgRight, rightMapX, rightMapY, interpolation=cv2.INTER_LINEAR, borderMode=cv2.BORDER_CONSTANT)
88 |
89 | cv2.imshow('Left CALIBRATED', imgL)
90 | cv2.imshow('Right CALIBRATED', imgR)
91 | cv2.waitKey(0)
92 |
93 | rectified_pair = (imgL, imgR)
94 |
95 |
96 | # Depth map function
97 | SWS = 7
98 | PFS = 7
99 | PFC = 29
100 | MDS = -3
101 | NOD = 48
102 | TTH = 13
103 | UR = 3
104 | SR = 14
105 | SPWS = 2
106 |
107 | def stereo_depth_map(rectified_pair):
108 | print ('SWS='+str(SWS)+' PFS='+str(PFS)+' PFC='+str(PFC)+' MDS='+\
109 | str(MDS)+' NOD='+str(NOD)+' TTH='+str(TTH))
110 | print (' UR='+str(UR)+' SR='+str(SR)+' SPWS='+str(SPWS))
111 | c, r = rectified_pair[0].shape
112 | disparity = np.zeros((c, r), np.uint8)
113 | sbm = cv2.StereoBM_create(numDisparities=16, blockSize=15)
114 | #sbm.SADWindowSize = SWS
115 | sbm.setPreFilterType(1)
116 | sbm.setPreFilterSize(PFS)
117 | sbm.setPreFilterCap(PFC)
118 | sbm.setMinDisparity(MDS)
119 | sbm.setNumDisparities(NOD)
120 | sbm.setTextureThreshold(TTH)
121 | sbm.setUniquenessRatio(UR)
122 | sbm.setSpeckleRange(SR)
123 | sbm.setSpeckleWindowSize(SPWS)
124 | dmLeft = rectified_pair[0]
125 | dmRight = rectified_pair[1]
126 | #cv2.FindStereoCorrespondenceBM(dmLeft, dmRight, disparity, sbm)
127 | disparity = sbm.compute(dmLeft, dmRight)
128 | #disparity_visual = cv.CreateMat(c, r, cv.CV_8U)
129 | local_max = disparity.max()
130 | local_min = disparity.min()
131 | print ("MAX " + str(local_max))
132 | print ("MIN " + str(local_min))
133 | disparity_visual = (disparity-local_min)*(1.0/(local_max-local_min))
134 | local_max = disparity_visual.max()
135 | local_min = disparity_visual.min()
136 | print ("MAX " + str(local_max))
137 | print ("MIN " + str(local_min))
138 | #cv.Normalize(disparity, disparity_visual, 0, 255, cv.CV_MINMAX)
139 | #disparity_visual = np.array(disparity_visual)
140 | return disparity_visual
141 |
142 |
143 | # Set up and draw interface
144 | # Draw left image and depth map
145 | axcolor = 'lightgoldenrodyellow'
146 | fig = plt.subplots(1,2)
147 | plt.subplots_adjust(left=0.15, bottom=0.5)
148 | plt.subplot(1,2,1)
149 | dmObject = plt.imshow(rectified_pair[0], 'gray')
150 |
151 | saveax = plt.axes([0.3, 0.38, 0.15, 0.04]) #stepX stepY width height
152 | buttons = Button(saveax, 'Save settings', color=axcolor, hovercolor='0.975')
153 |
154 |
155 | def save_map_settings( event ):
156 | buttons.label.set_text ("Saving...")
157 | print('Saving to file...')
158 | result = json.dumps({'SADWindowSize':SWS, 'preFilterSize':PFS, 'preFilterCap':PFC, \
159 | 'minDisparity':MDS, 'numberOfDisparities':NOD, 'textureThreshold':TTH, \
160 | 'uniquenessRatio':UR, 'speckleRange':SR, 'speckleWindowSize':SPWS},\
161 | sort_keys=True, indent=4, separators=(',',':'))
162 | fName = '3dmap_set.txt'
163 | f = open (str(fName), 'w')
164 | f.write(result)
165 | f.close()
166 | buttons.label.set_text ("Save to file")
167 | print ('Settings saved to file '+fName)
168 |
169 | buttons.on_clicked(save_map_settings)
170 |
171 |
172 | loadax = plt.axes([0.5, 0.38, 0.15, 0.04]) #stepX stepY width height
173 | buttonl = Button(loadax, 'Load settings', color=axcolor, hovercolor='0.975')
174 | def load_map_settings( event ):
175 | global SWS, PFS, PFC, MDS, NOD, TTH, UR, SR, SPWS, loading_settings
176 | loading_settings = 1
177 | fName = '3dmap_set.txt'
178 | print('Loading parameters from file...')
179 | buttonl.label.set_text ("Loading...")
180 | f=open(fName, 'r')
181 | data = json.load(f)
182 | sSWS.set_val(data['SADWindowSize'])
183 | sPFS.set_val(data['preFilterSize'])
184 | sPFC.set_val(data['preFilterCap'])
185 | sMDS.set_val(data['minDisparity'])
186 | sNOD.set_val(data['numberOfDisparities'])
187 | sTTH.set_val(data['textureThreshold'])
188 | sUR.set_val(data['uniquenessRatio'])
189 | sSR.set_val(data['speckleRange'])
190 | sSPWS.set_val(data['speckleWindowSize'])
191 | f.close()
192 | buttonl.label.set_text ("Load settings")
193 | print ('Parameters loaded from file '+fName)
194 | print ('Redrawing depth map with loaded parameters...')
195 | loading_settings = 0
196 | update(0)
197 | print ('Done!')
198 |
199 | buttonl.on_clicked(load_map_settings)
200 |
201 | # Building Depth Map for the first time
202 | disparity = stereo_depth_map(rectified_pair)
203 |
204 | plt.subplot(1,2,2)
205 | dmObject = plt.imshow(disparity, aspect='equal', cmap='jet')
206 |
207 | # Draw interface for adjusting parameters
208 | print('Start interface creation (it takes up to 30 seconds)...')
209 |
210 | SWSaxe = plt.axes([0.15, 0.01, 0.7, 0.025], facecolor=axcolor) #stepX stepY width height
211 | PFSaxe = plt.axes([0.15, 0.05, 0.7, 0.025], facecolor=axcolor) #stepX stepY width height
212 | PFCaxe = plt.axes([0.15, 0.09, 0.7, 0.025], facecolor=axcolor) #stepX stepY width height
213 | MDSaxe = plt.axes([0.15, 0.13, 0.7, 0.025], facecolor=axcolor) #stepX stepY width height
214 | NODaxe = plt.axes([0.15, 0.17, 0.7, 0.025], facecolor=axcolor) #stepX stepY width height
215 | TTHaxe = plt.axes([0.15, 0.21, 0.7, 0.025], facecolor=axcolor) #stepX stepY width height
216 | URaxe = plt.axes([0.15, 0.25, 0.7, 0.025], facecolor=axcolor) #stepX stepY width height
217 | SRaxe = plt.axes([0.15, 0.29, 0.7, 0.025], facecolor=axcolor) #stepX stepY width height
218 | SPWSaxe = plt.axes([0.15, 0.33, 0.7, 0.025], facecolor=axcolor) #stepX stepY width height
219 |
220 | sSWS = Slider(SWSaxe, 'SWS', 5.0, 255.0, valinit=5)
221 | sPFS = Slider(PFSaxe, 'PFS', 5.0, 255.0, valinit=5)
222 | sPFC = Slider(PFCaxe, 'PreFiltCap', 5.0, 63.0, valinit=29)
223 | sMDS = Slider(MDSaxe, 'MinDISP', -100.0, 100.0, valinit=-25)
224 | sNOD = Slider(NODaxe, 'NumOfDisp', 16.0, 256.0, valinit=128)
225 | sTTH = Slider(TTHaxe, 'TxtrThrshld', 0.0, 1000.0, valinit=100)
226 | sUR = Slider(URaxe, 'UnicRatio', 1.0, 20.0, valinit=10)
227 | sSR = Slider(SRaxe, 'SpcklRng', 0.0, 40.0, valinit=15)
228 | sSPWS = Slider(SPWSaxe, 'SpklWinSze', 0.0, 300.0, valinit=100)
229 |
230 |
231 | # Update depth map parameters and redraw
232 | def update(val):
233 | global SWS, PFS, PFC, MDS, NOD, TTH, UR, SR, SPWS
234 | SWS = int(sSWS.val/2)*2+1 #convert to ODD
235 | PFS = int(sPFS.val/2)*2+1
236 | PFC = int(sPFC.val/2)*2+1
237 | MDS = int(sMDS.val)
238 | NOD = int(sNOD.val/16)*16
239 | TTH = int(sTTH.val)
240 | UR = int(sUR.val)
241 | SR = int(sSR.val)
242 | SPWS= int(sSPWS.val)
243 | if ( loading_settings==0 ):
244 | print ('Rebuilding depth map')
245 | disparity = stereo_depth_map(rectified_pair)
246 | dmObject.set_data(disparity)
247 | print ('Redraw depth map')
248 | plt.draw()
249 |
250 |
251 | # Connect update actions to control elements
252 | sSWS.on_changed(update)
253 | sPFS.on_changed(update)
254 | sPFC.on_changed(update)
255 | sMDS.on_changed(update)
256 | sNOD.on_changed(update)
257 | sTTH.on_changed(update)
258 | sUR.on_changed(update)
259 | sSR.on_changed(update)
260 | sSPWS.on_changed(update)
261 |
262 | print('Show interface to user')
263 | plt.show()
264 |
--------------------------------------------------------------------------------
/4_calibration_fisheye.py:
--------------------------------------------------------------------------------
1 | # Copyright (C) 2021 Eugene a.k.a. Realizator, stereopi.com, virt2real team
2 | #
3 | # This file is part of StereoPi tutorial scripts.
4 | #
5 | # StereoPi tutorial is free software: you can redistribute it
6 | # and/or modify it under the terms of the GNU General Public License
7 | # as published by the Free Software Foundation, either version 3 of the
8 | # License, or (at your option) any later version.
9 | #
10 | # StereoPi tutorial is distributed in the hope that it will be useful,
11 | # but WITHOUT ANY WARRANTY; without even the implied warranty of
12 | # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
13 | # GNU General Public License for more details.
14 | #
15 | # You should have received a copy of the GNU General Public License
16 | # along with StereoPi tutorial.
17 | # If not, see .
18 | #
19 | # <><><> SPECIAL THANKS: <><><>
20 | #
21 | # Thanks to Adrian and http://pyimagesearch.com, as a lot of
22 | # code in this tutorial was taken from his lessons.
23 | #
24 | # Thanks to RPi-tankbot project: https://github.com/Kheiden/RPi-tankbot
25 | #
26 | # Thanks to rakali project: https://github.com/sthysel/rakali
27 |
28 |
29 | import os
30 | import cv2
31 | import numpy as np
32 |
33 |
34 |
35 |
36 | # Global variables preset
37 | total_photos = 50
38 |
39 | # Camera resolution
40 | photo_width = 1280
41 | photo_height = 480
42 |
43 | # Image resolution for processing
44 | img_width = 320
45 | img_height = 240
46 | image_size = (img_width,img_height)
47 |
48 | # Chessboard parameters
49 | rows = 6
50 | columns = 9
51 | square_size = 2.5
52 |
53 | # Visualization options
54 | drawCorners = False
55 | showSingleCamUndistortionResults = True
56 | showStereoRectificationResults = True
57 | writeUdistortedImages = True
58 | imageToDisp = './scenes/scene_1280x480_1.png'
59 |
60 | # Calibration settings
61 | CHECKERBOARD = (6,9)
62 |
63 | subpix_criteria = (cv2.TERM_CRITERIA_EPS+cv2.TERM_CRITERIA_MAX_ITER, 30, 0.1)
64 | calibration_flags = cv2.fisheye.CALIB_RECOMPUTE_EXTRINSIC+cv2.fisheye.CALIB_FIX_SKEW
65 |
66 | objp = np.zeros( (CHECKERBOARD[0]*CHECKERBOARD[1], 1, 3) , np.float64)
67 | objp[:,0, :2] = np.mgrid[0:CHECKERBOARD[0], 0:CHECKERBOARD[1]].T.reshape(-1, 2)
68 |
69 | _img_shape = None
70 | objpointsLeft = [] # 3d point in real world space
71 | imgpointsLeft = [] # 2d points in image plane.
72 |
73 | objpointsRight = [] # 3d point in real world space
74 | imgpointsRight = [] # 2d points in image plane.
75 |
76 | if (drawCorners):
77 | print("You can press 'Q' to quit this script.")
78 |
79 |
80 | # Main processing cycle
81 | # We process all calibration images and fill up 'imgpointsLeft' and 'objpointsRight'
82 | # arrays with found coordinates of the chessboard
83 | photo_counter = 0
84 | print ('Main cycle start')
85 |
86 | while photo_counter != total_photos:
87 | photo_counter = photo_counter + 1
88 | print ('Import pair No ' + str(photo_counter))
89 | leftName = './pairs/left_'+str(photo_counter).zfill(2)+'.png'
90 | rightName = './pairs/right_'+str(photo_counter).zfill(2)+'.png'
91 | leftExists = os.path.isfile(leftName)
92 | rightExists = os.path.isfile(rightName)
93 |
94 | # If pair has no left or right image - exit
95 | if ((leftExists == False) or (rightExists == False)) and (leftExists != rightExists):
96 | print ("Pair No ", photo_counter, "has only one image! Left:", leftExists, " Right:", rightExists )
97 | continue
98 |
99 | # If stereopair is complete - go to processing
100 | if (leftExists and rightExists):
101 | imgL = cv2.imread(leftName,1)
102 | loadedY, loadedX, clrs = imgL.shape
103 | grayL = cv2.cvtColor(imgL,cv2.COLOR_BGR2GRAY)
104 | gray_small_left = cv2.resize (grayL, (img_width,img_height), interpolation = cv2.INTER_AREA)
105 | imgR = cv2.imread(rightName,1)
106 | grayR = cv2.cvtColor(imgR,cv2.COLOR_BGR2GRAY)
107 | gray_small_right = cv2.resize (grayR, (img_width,img_height), interpolation = cv2.INTER_AREA)
108 |
109 | # Find the chessboard corners
110 | retL, cornersL = cv2.findChessboardCorners(grayL, CHECKERBOARD, cv2.CALIB_CB_ADAPTIVE_THRESH+cv2.CALIB_CB_FAST_CHECK+cv2.CALIB_CB_NORMALIZE_IMAGE)
111 | retR, cornersR = cv2.findChessboardCorners(grayR, CHECKERBOARD, cv2.CALIB_CB_ADAPTIVE_THRESH+cv2.CALIB_CB_FAST_CHECK+cv2.CALIB_CB_NORMALIZE_IMAGE)
112 |
113 | # Draw images with corners found
114 | if (drawCorners):
115 | cv2.drawChessboardCorners(imgL, (6,9), cornersL, retL)
116 | cv2.imshow('Corners LEFT', imgL)
117 | cv2.drawChessboardCorners(imgR, (6,9), cornersR, retR)
118 | cv2.imshow('Corners RIGHT', imgR)
119 | key = cv2.waitKey(0)
120 | if key == ord("q"):
121 | exit(0)
122 |
123 | # Here is a fix for the OpenCV bug, which is causing this error:
124 | # error:(-215:Assertion failed) fabs(norm_u1) > 0 in function 'InitExtrinsics'
125 | # It means corners are too close to the side of the image. Let's filter them out
126 |
127 | SayMore = False; #Should we print additional debug info?
128 | if ((retL == True) and (retR == True)):
129 | minRx = cornersR[:,:,0].min()
130 | maxRx = cornersR[:,:,0].max()
131 | minRy = cornersR[:,:,1].min()
132 | maxRy = cornersR[:,:,1].max()
133 |
134 | minLx = cornersL[:,:,0].min()
135 | maxLx = cornersL[:,:,0].max()
136 | minLy = cornersL[:,:,1].min()
137 | maxLy = cornersL[:,:,1].max()
138 |
139 | border_threshold_x = loadedX/7
140 | border_threshold_y = loadedY/7
141 | if (SayMore):
142 | print ("thr_X: ", border_threshold_x, "thr_Y:", border_threshold_y)
143 | x_thresh_bad = False
144 | if ((minRx photo_height):
168 | print ("Image resolution is higher than photo resolution, upscale needed. Please check your photo and image parameters!")
169 | exit (0)
170 |
171 | # Refine corners and add to array for processing
172 | if ((retL == True) and (retR == True)):
173 | objpointsLeft.append(objp)
174 | cv2.cornerSubPix(gray_small_left,cornersL,(3,3),(-1,-1),subpix_criteria)
175 | imgpointsLeft.append(cornersL)
176 | objpointsRight.append(objp)
177 | cv2.cornerSubPix(gray_small_right,cornersR,(3,3),(-1,-1),subpix_criteria)
178 | imgpointsRight.append(cornersR)
179 | else:
180 | print ("Pair No", photo_counter, "ignored, as no chessboard found" )
181 | continue
182 |
183 | print ('End cycle')
184 |
185 |
186 | # This function calibrates (undistort) a single camera
187 | def calibrate_one_camera (objpoints, imgpoints, right_or_left):
188 |
189 | # Opencv sample code uses the var 'grey' from the last opened picture
190 | N_OK = len(objpoints)
191 | DIM= (img_width, img_height)
192 | K = np.zeros((3, 3))
193 | D = np.zeros((4, 1))
194 | rvecs = [np.zeros((1, 1, 3), dtype=np.float64) for i in range(N_OK)]
195 | tvecs = [np.zeros((1, 1, 3), dtype=np.float64) for i in range(N_OK)]
196 |
197 | # Single camera calibration (undistortion)
198 | rms, camera_matrix, distortion_coeff, _, _ = \
199 | cv2.fisheye.calibrate(
200 | objpoints,
201 | imgpoints,
202 | grayL.shape[::-1],
203 | K,
204 | D,
205 | rvecs,
206 | tvecs,
207 | calibration_flags,
208 | (cv2.TERM_CRITERIA_EPS+cv2.TERM_CRITERIA_MAX_ITER, 30, 1e-6)
209 | )
210 | # Let's rectify our results
211 | map1, map2 = cv2.fisheye.initUndistortRectifyMap(K, D, np.eye(3), K, DIM, cv2.CV_16SC2)
212 |
213 | # Now we'll write our results to the file for the future use
214 | if (os.path.isdir('./calibration_data/{}p'.format(img_height))==False):
215 | os.makedirs('./calibration_data/{}p'.format(img_height))
216 | np.savez('./calibration_data/{}p/camera_calibration_{}.npz'.format(img_height, right_or_left),
217 | map1=map1, map2=map2, objpoints=objpoints, imgpoints=imgpoints,
218 | camera_matrix=camera_matrix, distortion_coeff=distortion_coeff)
219 | return (True)
220 |
221 |
222 | # Stereoscopic calibration
223 | def calibrate_stereo_cameras(res_x=img_width, res_y=img_height):
224 | # We need a lot of variables to calibrate the stereo camera
225 | """
226 | Based on code from:
227 | https://gist.github.com/aarmea/629e59ac7b640a60340145809b1c9013
228 | """
229 | processing_time01 = cv2.getTickCount()
230 | objectPoints = None
231 |
232 | rightImagePoints = None
233 | rightCameraMatrix = None
234 | rightDistortionCoefficients = None
235 |
236 | leftImagePoints = None
237 | leftCameraMatrix = None
238 | leftDistortionCoefficients = None
239 |
240 | rotationMatrix = None
241 | translationVector = None
242 |
243 | imageSize= (res_x, res_y)
244 |
245 | TERMINATION_CRITERIA = (cv2.TERM_CRITERIA_EPS+cv2.TERM_CRITERIA_MAX_ITER, 30, 0.01)
246 | OPTIMIZE_ALPHA = 0.25
247 |
248 | try:
249 | npz_file = np.load('./calibration_data/{}p/stereo_camera_calibration.npz'.format(res_y))
250 | except:
251 | pass
252 |
253 | for cam_num in [0, 1]:
254 | right_or_left = ["_right" if cam_num==1 else "_left"][0]
255 |
256 | try:
257 | print ('./calibration_data/{}p/camera_calibration{}.npz'.format(res_y, right_or_left))
258 | npz_file = np.load('./calibration_data/{}p/camera_calibration{}.npz'.format(res_y, right_or_left))
259 |
260 | list_of_vars = ['map1', 'map2', 'objpoints', 'imgpoints', 'camera_matrix', 'distortion_coeff']
261 | print(sorted(npz_file.files))
262 |
263 | if sorted(list_of_vars) == sorted(npz_file.files):
264 | print("Camera calibration data has been found in cache.")
265 | map1 = npz_file['map1']
266 | map2 = npz_file['map2']
267 | objectPoints = npz_file['objpoints']
268 | if right_or_left == "_right":
269 | rightImagePoints = npz_file['imgpoints']
270 | rightCameraMatrix = npz_file['camera_matrix']
271 | rightDistortionCoefficients = npz_file['distortion_coeff']
272 | if right_or_left == "_left":
273 | leftImagePoints = npz_file['imgpoints']
274 | leftCameraMatrix = npz_file['camera_matrix']
275 | leftDistortionCoefficients = npz_file['distortion_coeff']
276 | else:
277 | print("Camera data file found but data corrupted.")
278 | except:
279 | #If the file doesn't exist
280 | print("Camera calibration data not found in cache.")
281 | return False
282 |
283 |
284 | print("Calibrating cameras together...")
285 |
286 | leftImagePoints = np.asarray(leftImagePoints, dtype=np.float64)
287 | rightImagePoints = np.asarray(rightImagePoints, dtype=np.float64)
288 |
289 | # Stereo calibration
290 | (RMS, _, _, _, _, rotationMatrix, translationVector) = cv2.fisheye.stereoCalibrate(
291 | objectPoints, leftImagePoints, rightImagePoints,
292 | leftCameraMatrix, leftDistortionCoefficients,
293 | rightCameraMatrix, rightDistortionCoefficients,
294 | imageSize, None, None,
295 | cv2.CALIB_FIX_INTRINSIC, TERMINATION_CRITERIA)
296 | # Print RMS result (for calibration quality estimation)
297 | print ("<><><><><><><><><><><><><><><><><><><><>")
298 | print ("<><> RMS is ", RMS, " <><>")
299 | print ("<><><><><><><><><><><><><><><><><><><><>")
300 | print("Rectifying cameras...")
301 | R1 = np.zeros([3,3])
302 | R2 = np.zeros([3,3])
303 | P1 = np.zeros([3,4])
304 | P2 = np.zeros([3,4])
305 | Q = np.zeros([4,4])
306 |
307 | # Rectify calibration results
308 | (leftRectification, rightRectification, leftProjection, rightProjection,
309 | dispartityToDepthMap) = cv2.fisheye.stereoRectify(
310 | leftCameraMatrix, leftDistortionCoefficients,
311 | rightCameraMatrix, rightDistortionCoefficients,
312 | imageSize, rotationMatrix, translationVector,
313 | 0, R2, P1, P2, Q,
314 | cv2.CALIB_ZERO_DISPARITY, (0,0) , 0, 0)
315 |
316 | # Saving calibration results for the future use
317 | print("Saving calibration...")
318 | leftMapX, leftMapY = cv2.fisheye.initUndistortRectifyMap(
319 | leftCameraMatrix, leftDistortionCoefficients, leftRectification,
320 | leftProjection, imageSize, cv2.CV_16SC2)
321 | rightMapX, rightMapY = cv2.fisheye.initUndistortRectifyMap(
322 | rightCameraMatrix, rightDistortionCoefficients, rightRectification,
323 | rightProjection, imageSize, cv2.CV_16SC2)
324 |
325 | np.savez_compressed('./calibration_data/{}p/stereo_camera_calibration.npz'.format(res_y), imageSize=imageSize,
326 | leftMapX=leftMapX, leftMapY=leftMapY,
327 | rightMapX=rightMapX, rightMapY=rightMapY, dispartityToDepthMap = dispartityToDepthMap)
328 | return True
329 |
330 | # Now we have all we need to do stereoscopic fisheye calibration
331 | # Let's calibrate each camera, and than calibrate them together
332 | print ("Left camera calibration...")
333 | result = calibrate_one_camera(objpointsLeft, imgpointsLeft, 'left')
334 | print ("Right camera calibration...")
335 | result = calibrate_one_camera(objpointsRight, imgpointsRight, 'right')
336 | print ("Stereoscopic calibration...")
337 | result = calibrate_stereo_cameras()
338 | print ("Calibration complete!")
339 |
340 | # The following code just shows you calibration results
341 | #
342 | #
343 |
344 | if (showSingleCamUndistortionResults):
345 |
346 | """
347 | # Takes an image in as a numpy array and undistorts it
348 | """
349 | # NOTICE: we use 320x240 as a working resolution, regardless of
350 | # calibration images resolution. So 320x240 parameters are hardcoded
351 | # now.
352 |
353 | #h, w = imgL.shape[:2]
354 | w = 320
355 | h = 240
356 | print("Undistorting picture with (width, height):", (w, h))
357 | try:
358 | npz_file = np.load('./calibration_data/{}p/camera_calibration{}.npz'.format(h, '_left'))
359 | if 'map1' and 'map2' in npz_file.files:
360 | #print("Camera calibration data has been found in cache.")
361 | map1 = npz_file['map1']
362 | map2 = npz_file['map2']
363 | else:
364 | print("Camera data file found but data corrupted.")
365 | exit(0)
366 | except:
367 | print("Camera calibration data not found in cache, file " & './calibration_data/{}p/camera_calibration{}.npz'.format(h, left))
368 | exit(0)
369 |
370 | # We didn't load a new image from file, but use last image loaded while calibration
371 | undistorted_left = cv2.remap(gray_small_left, map1, map2, interpolation=cv2.INTER_LINEAR, borderMode=cv2.BORDER_CONSTANT)
372 |
373 | #h, w = imgR.shape[:2]
374 | print("Undistorting picture with (width, height):", (w, h))
375 | try:
376 | npz_file = np.load('./calibration_data/{}p/camera_calibration{}.npz'.format(h, '_right'))
377 | if 'map1' and 'map2' in npz_file.files:
378 | #print("Camera calibration data has been found in cache.")
379 | map1 = npz_file['map1']
380 | map2 = npz_file['map2']
381 | else:
382 | print("Camera data file found but data corrupted.")
383 | exit(0)
384 | except:
385 | print("Camera calibration RIGHT data not found in cache.")
386 | exit(0)
387 |
388 | undistorted_right = cv2.remap(gray_small_right, map1, map2, interpolation=cv2.INTER_LINEAR, borderMode=cv2.BORDER_CONSTANT)
389 |
390 | cv2.imshow('Left UNDISTORTED', undistorted_left)
391 | cv2.imshow('Right UNDISTORTED', undistorted_right)
392 | cv2.waitKey(0)
393 | if (writeUdistortedImages):
394 | cv2.imwrite("undistorted_left.jpg",undistorted_left)
395 | cv2.imwrite("undistorted_right.jpg",undistorted_right)
396 |
397 |
398 |
399 |
400 | if (showStereoRectificationResults):
401 | # lets rectify pair and look at the result
402 |
403 | # NOTICE: we use 320x240 as a working resolution, regardless of
404 | # calibration images resolution. So 320x240 parameters are hardcoded
405 | # now.
406 | try:
407 | npzfile = np.load('./calibration_data/{}p/stereo_camera_calibration.npz'.format(240))
408 | except:
409 | print("Camera calibration data not found in cache, file " & './calibration_data/{}p/stereo_camera_calibration.npz'.format(240))
410 | exit(0)
411 |
412 | leftMapX = npzfile['leftMapX']
413 | leftMapY = npzfile['leftMapY']
414 | rightMapX = npzfile['rightMapX']
415 | rightMapY = npzfile['rightMapY']
416 |
417 | #read image to undistort
418 | photo_width = 640
419 | photo_height = 240
420 | image_width = 320
421 | image_height = 240
422 | image_size = (image_width,image_height)
423 |
424 | if os.path.isfile(imageToDisp) == False:
425 | print ('Can not read image from file \"'+imageToDisp+'\"')
426 | exit(0)
427 |
428 | pair_img = cv2.imread(imageToDisp,0)
429 |
430 | # If our image has width and height we need?
431 | height_check, width_check = pair_img.shape[:2]
432 |
433 | if (width_check != photo_width) and (height_check != photo_height):
434 | # It's not our size. If it is scaled?
435 | if (width_check/photo_width == height_check/photo_height):
436 | # Well, it's just scaled! Let's resize it to fit our needs
437 | pair_img = cv2.resize (pair_img, dsize=(photo_width, photo_height), interpolation = cv2.INTER_CUBIC)
438 | else:
439 | # Image can not be scaled, as calibration was done for another image size
440 | print ("Wrong image size. Please choose appropriate image.")
441 | exit (0)
442 |
443 | # Read image and split it in a stereo pair
444 | print('Read and split image...')
445 | imgLTest = pair_img [0:photo_height,0:image_width] #Y+H and X+W
446 | imgRTest = pair_img [0:photo_height,image_width:photo_width] #Y+H and X+W
447 |
448 | # If pair has been loaded and splitted correclty?
449 | width_left, height_left = imgLTest.shape[:2]
450 | width_right, height_right = imgRTest.shape[:2]
451 | if 0 in [width_left, height_left, width_right, height_right]:
452 | print("Error: Can't remap image.")
453 |
454 | # Rectifying left and right images
455 | imgL = cv2.remap(imgLTest, leftMapX, leftMapY, interpolation=cv2.INTER_LINEAR, borderMode=cv2.BORDER_CONSTANT)
456 | imgR = cv2.remap(imgRTest, rightMapX, rightMapY, interpolation=cv2.INTER_LINEAR, borderMode=cv2.BORDER_CONSTANT)
457 |
458 | cv2.imshow('Left STEREO CALIBRATED', imgL)
459 | cv2.imshow('Right STEREO CALIBRATED', imgR)
460 | cv2.imwrite("rectifyed_left.jpg",imgL)
461 | cv2.imwrite("rectifyed_right.jpg",imgR)
462 | cv2.waitKey(0)
463 |
--------------------------------------------------------------------------------
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440 | to receive a copy likewise does not require acceptance. However,
441 | nothing other than this License grants you permission to propagate or
442 | modify any covered work. These actions infringe copyright if you do
443 | not accept this License. Therefore, by modifying or propagating a
444 | covered work, you indicate your acceptance of this License to do so.
445 |
446 | 10. Automatic Licensing of Downstream Recipients.
447 |
448 | Each time you convey a covered work, the recipient automatically
449 | receives a license from the original licensors, to run, modify and
450 | propagate that work, subject to this License. You are not responsible
451 | for enforcing compliance by third parties with this License.
452 |
453 | An "entity transaction" is a transaction transferring control of an
454 | organization, or substantially all assets of one, or subdividing an
455 | organization, or merging organizations. If propagation of a covered
456 | work results from an entity transaction, each party to that
457 | transaction who receives a copy of the work also receives whatever
458 | licenses to the work the party's predecessor in interest had or could
459 | give under the previous paragraph, plus a right to possession of the
460 | Corresponding Source of the work from the predecessor in interest, if
461 | the predecessor has it or can get it with reasonable efforts.
462 |
463 | You may not impose any further restrictions on the exercise of the
464 | rights granted or affirmed under this License. For example, you may
465 | not impose a license fee, royalty, or other charge for exercise of
466 | rights granted under this License, and you may not initiate litigation
467 | (including a cross-claim or counterclaim in a lawsuit) alleging that
468 | any patent claim is infringed by making, using, selling, offering for
469 | sale, or importing the Program or any portion of it.
470 |
471 | 11. Patents.
472 |
473 | A "contributor" is a copyright holder who authorizes use under this
474 | License of the Program or a work on which the Program is based. The
475 | work thus licensed is called the contributor's "contributor version".
476 |
477 | A contributor's "essential patent claims" are all patent claims
478 | owned or controlled by the contributor, whether already acquired or
479 | hereafter acquired, that would be infringed by some manner, permitted
480 | by this License, of making, using, or selling its contributor version,
481 | but do not include claims that would be infringed only as a
482 | consequence of further modification of the contributor version. For
483 | purposes of this definition, "control" includes the right to grant
484 | patent sublicenses in a manner consistent with the requirements of
485 | this License.
486 |
487 | Each contributor grants you a non-exclusive, worldwide, royalty-free
488 | patent license under the contributor's essential patent claims, to
489 | make, use, sell, offer for sale, import and otherwise run, modify and
490 | propagate the contents of its contributor version.
491 |
492 | In the following three paragraphs, a "patent license" is any express
493 | agreement or commitment, however denominated, not to enforce a patent
494 | (such as an express permission to practice a patent or covenant not to
495 | sue for patent infringement). To "grant" such a patent license to a
496 | party means to make such an agreement or commitment not to enforce a
497 | patent against the party.
498 |
499 | If you convey a covered work, knowingly relying on a patent license,
500 | and the Corresponding Source of the work is not available for anyone
501 | to copy, free of charge and under the terms of this License, through a
502 | publicly available network server or other readily accessible means,
503 | then you must either (1) cause the Corresponding Source to be so
504 | available, or (2) arrange to deprive yourself of the benefit of the
505 | patent license for this particular work, or (3) arrange, in a manner
506 | consistent with the requirements of this License, to extend the patent
507 | license to downstream recipients. "Knowingly relying" means you have
508 | actual knowledge that, but for the patent license, your conveying the
509 | covered work in a country, or your recipient's use of the covered work
510 | in a country, would infringe one or more identifiable patents in that
511 | country that you have reason to believe are valid.
512 |
513 | If, pursuant to or in connection with a single transaction or
514 | arrangement, you convey, or propagate by procuring conveyance of, a
515 | covered work, and grant a patent license to some of the parties
516 | receiving the covered work authorizing them to use, propagate, modify
517 | or convey a specific copy of the covered work, then the patent license
518 | you grant is automatically extended to all recipients of the covered
519 | work and works based on it.
520 |
521 | A patent license is "discriminatory" if it does not include within
522 | the scope of its coverage, prohibits the exercise of, or is
523 | conditioned on the non-exercise of one or more of the rights that are
524 | specifically granted under this License. You may not convey a covered
525 | work if you are a party to an arrangement with a third party that is
526 | in the business of distributing software, under which you make payment
527 | to the third party based on the extent of your activity of conveying
528 | the work, and under which the third party grants, to any of the
529 | parties who would receive the covered work from you, a discriminatory
530 | patent license (a) in connection with copies of the covered work
531 | conveyed by you (or copies made from those copies), or (b) primarily
532 | for and in connection with specific products or compilations that
533 | contain the covered work, unless you entered into that arrangement,
534 | or that patent license was granted, prior to 28 March 2007.
535 |
536 | Nothing in this License shall be construed as excluding or limiting
537 | any implied license or other defenses to infringement that may
538 | otherwise be available to you under applicable patent law.
539 |
540 | 12. No Surrender of Others' Freedom.
541 |
542 | If conditions are imposed on you (whether by court order, agreement or
543 | otherwise) that contradict the conditions of this License, they do not
544 | excuse you from the conditions of this License. If you cannot convey a
545 | covered work so as to satisfy simultaneously your obligations under this
546 | License and any other pertinent obligations, then as a consequence you may
547 | not convey it at all. For example, if you agree to terms that obligate you
548 | to collect a royalty for further conveying from those to whom you convey
549 | the Program, the only way you could satisfy both those terms and this
550 | License would be to refrain entirely from conveying the Program.
551 |
552 | 13. Use with the GNU Affero General Public License.
553 |
554 | Notwithstanding any other provision of this License, you have
555 | permission to link or combine any covered work with a work licensed
556 | under version 3 of the GNU Affero General Public License into a single
557 | combined work, and to convey the resulting work. The terms of this
558 | License will continue to apply to the part which is the covered work,
559 | but the special requirements of the GNU Affero General Public License,
560 | section 13, concerning interaction through a network will apply to the
561 | combination as such.
562 |
563 | 14. Revised Versions of this License.
564 |
565 | The Free Software Foundation may publish revised and/or new versions of
566 | the GNU General Public License from time to time. Such new versions will
567 | be similar in spirit to the present version, but may differ in detail to
568 | address new problems or concerns.
569 |
570 | Each version is given a distinguishing version number. If the
571 | Program specifies that a certain numbered version of the GNU General
572 | Public License "or any later version" applies to it, you have the
573 | option of following the terms and conditions either of that numbered
574 | version or of any later version published by the Free Software
575 | Foundation. If the Program does not specify a version number of the
576 | GNU General Public License, you may choose any version ever published
577 | by the Free Software Foundation.
578 |
579 | If the Program specifies that a proxy can decide which future
580 | versions of the GNU General Public License can be used, that proxy's
581 | public statement of acceptance of a version permanently authorizes you
582 | to choose that version for the Program.
583 |
584 | Later license versions may give you additional or different
585 | permissions. However, no additional obligations are imposed on any
586 | author or copyright holder as a result of your choosing to follow a
587 | later version.
588 |
589 | 15. Disclaimer of Warranty.
590 |
591 | THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
592 | APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
593 | HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY
594 | OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO,
595 | THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
596 | PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM
597 | IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF
598 | ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
599 |
600 | 16. Limitation of Liability.
601 |
602 | IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
603 | WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS
604 | THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY
605 | GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE
606 | USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF
607 | DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD
608 | PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),
609 | EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF
610 | SUCH DAMAGES.
611 |
612 | 17. Interpretation of Sections 15 and 16.
613 |
614 | If the disclaimer of warranty and limitation of liability provided
615 | above cannot be given local legal effect according to their terms,
616 | reviewing courts shall apply local law that most closely approximates
617 | an absolute waiver of all civil liability in connection with the
618 | Program, unless a warranty or assumption of liability accompanies a
619 | copy of the Program in return for a fee.
620 |
621 | END OF TERMS AND CONDITIONS
622 |
623 | How to Apply These Terms to Your New Programs
624 |
625 | If you develop a new program, and you want it to be of the greatest
626 | possible use to the public, the best way to achieve this is to make it
627 | free software which everyone can redistribute and change under these terms.
628 |
629 | To do so, attach the following notices to the program. It is safest
630 | to attach them to the start of each source file to most effectively
631 | state the exclusion of warranty; and each file should have at least
632 | the "copyright" line and a pointer to where the full notice is found.
633 |
634 |
635 | Copyright (C)
636 |
637 | This program is free software: you can redistribute it and/or modify
638 | it under the terms of the GNU General Public License as published by
639 | the Free Software Foundation, either version 3 of the License, or
640 | (at your option) any later version.
641 |
642 | This program is distributed in the hope that it will be useful,
643 | but WITHOUT ANY WARRANTY; without even the implied warranty of
644 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
645 | GNU General Public License for more details.
646 |
647 | You should have received a copy of the GNU General Public License
648 | along with this program. If not, see .
649 |
650 | Also add information on how to contact you by electronic and paper mail.
651 |
652 | If the program does terminal interaction, make it output a short
653 | notice like this when it starts in an interactive mode:
654 |
655 | Copyright (C)
656 | This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
657 | This is free software, and you are welcome to redistribute it
658 | under certain conditions; type `show c' for details.
659 |
660 | The hypothetical commands `show w' and `show c' should show the appropriate
661 | parts of the General Public License. Of course, your program's commands
662 | might be different; for a GUI interface, you would use an "about box".
663 |
664 | You should also get your employer (if you work as a programmer) or school,
665 | if any, to sign a "copyright disclaimer" for the program, if necessary.
666 | For more information on this, and how to apply and follow the GNU GPL, see
667 | .
668 |
669 | The GNU General Public License does not permit incorporating your program
670 | into proprietary programs. If your program is a subroutine library, you
671 | may consider it more useful to permit linking proprietary applications with
672 | the library. If this is what you want to do, use the GNU Lesser General
673 | Public License instead of this License. But first, please read
674 | .
675 |
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