mirror of
https://github.com/sudoxnym/fdroiddata.git
synced 2026-07-26 16:54:09 +00:00
cf4e8a40ff
```python
import yaml, glob, re, os
from fdroidserver import metadata
pat = re.compile(r'\[(https?://[^ \]]+)\s+([^\]]+)\]')
for f in glob.glob('metadata/*.yml'):
with open(f) as fp:
data = yaml.load(fp)
description = data.get('Description', '')
for m in pat.finditer(data.get('Description', '')):
link = m.group(1)
text = m.group(2)
print(f, link, text, flush=True)
description = description.replace(m.group(), '<a href="%s">%s</a>' % (link, text))
data['Description'] = description
app = metadata.App(data)
metadata.write_metadata(f, app)
```
```
sed -i 's,^ - true, - yes,' metadata/*.yml
sed -i 's,^ - false, - no,' metadata/*.yml
```
closes fdroid-website#510
25 lines
1.1 KiB
YAML
25 lines
1.1 KiB
YAML
Categories:
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- Multimedia
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License: MIT
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SourceCode: https://bitbucket.org/chlun/aicamera
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AutoName: AiCamera
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Description: |-
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This is a camera app for Android that automatically recognises the pixel location of people, cats or dogs in the camera view and blurs the background simulating depth of field. It can also gray out the background leaving only the recognised object in colour.
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The app uses a convolutional neural network to perform the detection. A TensorFlow implementation of the neural network can be found <a href="https://bitbucket.org/chlun/shufflesegmentation/src/master/">here</a>. It was trained on a dataset of images consisting of people, cats and dogs and the trained model then exported as a protobuf file which contains the graph definition and the trained weights.
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RepoType: git
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Repo: https://bitbucket.org/chlun/aicamera.git
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Builds:
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- versionName: '1.0'
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versionCode: 1
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commit: 7ef9c9310cc06e9b524436990777cf27930e8d2b
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subdir: app
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gradle:
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- yes
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AutoUpdateMode: Version v%v
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UpdateCheckMode: Tags
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CurrentVersion: '1.0'
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CurrentVersionCode: 1
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