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Check out the documentation for more information.
Panorama Video Process - Data and Outputs
This dataset contains the test data and outputs from three modes for memory tests.
Structure
test_data/: 15 selected test samples from https://huggingface.co/datasets/quchenyuan/360x_dataset_LR/tree/mainoutputs/two-turn/: processed-video bytwo-turnmode + metadata + visualized final away duration distributionoutputs/away-target-away-target same/: processed-video byaway-target-away-target samemode + metadata + visualized final away duration distributionoutputs/away-target-away-target opposite/: processed-video byaway-target-away-target oppositemode + metadata + visualized final away duration distribution
Modes
1. two_turn: target-away-target
Temporal order:
target hold
-> smooth turn to away
-> away hold
-> smooth turn back to target
-> final target hold
The goal of this condition is: the target is seen from the very first frame, then the view leaves the target, and finally, within the prediction window, the view turns back to the same target from the away direction.
2. away_target_away_target + same
Temporal order:
entry away hold
-> smooth turn to target
-> middle target hold
-> smooth turn to exit away
-> exit away hold
-> smooth turn back to target
-> final target hold
same means the entry away and exit away use the same away yaw and away FOV.
3. away_target_away_target + opposite
The temporal order is the same as same:
entry away hold
-> smooth turn to target
-> middle target hold
-> smooth turn to exit away
-> exit away hold
-> smooth turn back to target
-> final target hold
opposite means the entry away and exit away lie in opposite directions relative to the target: if the entry away is the target yaw plus a positive delta, then the exit away uses a negative delta, and vice versa. The FOV sizes of the two away segments are identical, but their yaws differ.
Usage
from huggingface_hub import snapshot_download
path = snapshot_download(
repo_id="sunmengxi/panorama-video-process",
repo_type="dataset"
)
print(path)
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