Automated solutions for batch image processing
For large number of image conversion needs, automation can be achieved by the following methods:
- Command line batch processing:
Write shell scripts to call the project API:
for img in ./input/*.jpg;
do
curl -X POST -F “image=@$img” http://localhost:5000/api/convert?style=ghibli
done - Python Automation:
Use watchdog to monitor folders to automatically process new files:
from watchdog.observers import Observer
from watchdog.events import FileSystemEventHandler
class Handler(FileSystemEventHandler):
def on_created(self, event):
# Call Conversion API - Queue Management:
Combining Celery to implement distributed task queues and monitor task progress through flower
Setting priority processing and high and low resolution operating modes - Exporting organizations:
Automatic generation of time-stamped batch catalogs
Integrated exif tool preserves original shot information
Adding style tags to the output filename
For ultra-high volume tasks (1000+), it is recommended to use Redis for caching and incremental JPEG generation to reduce I/O load.
This answer comes from the article4o-ghibli-at-home: locally run Ghibli-style image conversion tool》
May not be reproduced without permission:AI productivity tools » How to realize batch image conversion with 4o-ghibli-at-home to enhance work efficiency?
