https://github.com/yzfly/dark48
https://github.com/yzfly/dark48
Last synced: 3 months ago
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- Host: GitHub
- URL: https://github.com/yzfly/dark48
- Owner: yzfly
- Created: 2022-08-13T08:29:28.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2024-04-15T15:08:56.000Z (about 1 year ago)
- Last Synced: 2024-12-31T01:43:43.772Z (5 months ago)
- Language: Python
- Size: 1.57 MB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Dark-48
Dark-48: a dark video dataset for action recognition in the dark.
Dark-48 is a dark video dataset created for action recognition in the dark, collected from [Kinetics700](https://arxiv.org/abs/2010.10864) and [MiT](https://arxiv.org/abs/1801.03150), contains 8815 dark videos belong to 48 action classes. To overcome the limitations (fewer scenes and fewer categories) of the existing dark video action recognition dataset (e.g. [ARID](https://xuyu0010.github.io/arid.html)) , we build this dataset to provide more dark videos, more categories and richer scenes.
## Download
The full dataset can be downloaded from:
* [baidu](https://pan.baidu.com/s/1Hs-0S908vr8INvlvnQLnig?pwd=dk18), code: `dk18`
* [Google Drive](https://drive.google.com/drive/folders/1Z53fzDePkJQjPNH2VTvaIly_Yq09g9Hm?usp=sharing)
## Categories
The action categories for Dark-48 data set are:
'''
adult+female+singing,
adult+male+singing,
adult+male+speaking,
applauding,
ascending,
balancing,
bouncing,
breathing fire,
bubbling,
burning,
cheering,
child+singing,
clapping,
combusting,
coughing,
dancing,
descending,
driving,
dropping,
drumming,
erupting,
floating,
headbanging,
juggling,
juggling fire,
karaoke,
performing,
playing,
playing laser tag,
playing+music,
playing+videogames,
raining,
riding mechanical bull,
rising,
rocking,
shooting off fireworks,
shouting,
silent disco,
singing,
smoking,
spelunking,
spilling,
spinning,
spinning poi,
storming,
talking,
turning,
whistling
'''
Here the examples for each category:
## Statistics
## Dark Video Evaluation
The source code of the proposed dark video evaluation method for dark videos collection.
```
import os
import cv2
import numpy as np
from decord import VideoReader
def dark_img(img, threshold = 0.877):
YCrCb = cv2.cvtColor(img, cv2.COLOR_RGB2YCrCb)
Y = YCrCb[:,:,0]
# Determine whether image is bright or dimmed
exp_in = 112 # Expected global average intensity
M,N = img.shape[:2]
mean_in = np.sum(Y/(M*N))
t = (mean_in - exp_in)/ exp_in
# Check image
if t < -threshold: # Dimmed Image
return True
else:
return False
def dark_video(video, segments=8, threshold = 0.877):
vr = VideoReader(video)
seg = int(len(vr) / segments)
sample_id = [seg*i+int(seg/2) for i in range(0, segments)]
frames = vr.get_batch(sample_id).asnumpy()
video_t = 0
for i in range(len(sample_id)):
img = frames[i]
img_t = dark_img(img)
video_t += img_t
if video_t/segments >= threshold:
return True
else:
return False
```
## Contact
If you have any questions about the Dark-48 dataset, please contact:
```
yzliu.me at gmail.com
```