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rofunc/README.md

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- [Zed](#zed)
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- [Record](#record)
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- [Playback](#playback)
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- [Export](#export)
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## Hello, robot world!
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| | | `optitrack.visualize` | Show or save gif about the motion | |
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| | ZED | `zed.record` | Record with multiple cameras ||
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| | | `zed.playback` | Playback the recording and save snapshots ||
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| | | `zed.export` | Export the recording to mp4 | |
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| | | `zed.export` | Export the recording to .avi and image sequence | |
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| | Multi-modal | `mmodal.record` | Record multi-modal demonstration data simultaneously | |
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| **Logger** | | `logger.write` | Custom tensorboard-based logger | |
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| **Coordinate** | | `coord.custom_class` | Define the custom class of `Pose` | |
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Saving image 2.png : SUCCESS
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Saving image 3.png : SUCCESS
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...
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```
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```
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#### Export
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```python
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def export(filepath, mode=1):
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"""
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Export the svo file with specific mode.
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Args:
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filepath: SVO file path (input) : path/to/file.svo
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mode: Export mode: 0=Export LEFT+RIGHT AVI.
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1=Export LEFT+DEPTH_VIEW AVI.
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2=Export LEFT+RIGHT image sequence.
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3=Export LEFT+DEPTH_VIEW image sequence.
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4=Export LEFT+DEPTH_16Bit image sequence.
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Returns:
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"""
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```
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Example
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```python
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import rofunc as rf
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rf.zed.export('/home/ubuntu/Data/06_24/Video/20220624_1649/38709363.svo', 2)
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```
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> Since the converting always take a long time, I provide the batch form to convert in parallel.
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```python
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def export_batch(filedir, all_mode=True, mode=None, core_num=10):
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```
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Example:
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```
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rf.zed.export_batch('/home/ubuntu/Data/06_24/Video/20220624_1649', core_num=20)
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```
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Then you can convert all the .svo files under the specific directory with all mode in parallel. Enjoy it!

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