imagecrop
Image extraction using a template. Uses homography and feature matching, storing results in a SQLite database in the user’s home directory for faster reprocessing.
Usage
from image_extract.extract import Extracter
ex = Extracter()
ex.crop_images(image_directory, crop_template, file_extension[, match_points])Successful crops are extracted to a directory called successful_crops, directly underneath image_directory. Each template used creates a subdirectory, named after its md5 hash:
image_directory
- img1.jpg
- …
- imgn.jpg
- successful_crops
- 2a1bdab44c5e81af34f47f3395a3da7e
- img1_cropped.jpgThe optional match_points argument controls the number of matching points which must be detected in order for a template match to be deemed successful. It’s set to 30 by default.
Summaries
Call ex.summary(path) to see information on extracted crops for a given directory.
Deleting Extracted Crops
Call ex.delete(path[, template_md5]) to delete extracted crops for a given template. If no template md5 value is given, all extracted crops in that directory are removed.
Accuracy
For best results, the template image should be of the same (or similar) resolution as the image from which the crop is to be extracted.
1 maintainer
Metadata
1 maintainer
Release files for imagecrop 0.0.16
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| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| imagecrop-0.0.16-py2-none-any.whl | Python 2 | none | any | Details for imagecrop-0.0.16-py2-none-any.whl |
Release files / imagecrop-0.0.16-py2-none-any.whl
| Download URL | imagecrop-0.0.16-py2-none-any.whl |
|---|---|
| Size | 10.1 kB |
| Tags | Python 2 |
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7a01383d722a7bb06de2b50f873ba82d7dc3679ed652aaab9099b5fe7288b495
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Security for imagecrop 0.0.16
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