معرفی شرکت ها
ctu-0.2.1
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشترتوضیحات
A python package to perform same transformation to coco-annotation as performed on the image.
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | ctu-0.2.1 |
| نام | ctu |
| نسخه کتابخانه | 0.2.1 |
| نگهدارنده | ['Mohit Rajput'] |
| ایمیل نگهدارنده | ['mohitrajput901@gmail.com'] |
| نویسنده | Mohit Rajput |
| ایمیل نویسنده | mohitrajput901@gmail.com |
| آدرس صفحه اصلی | https://github.com/Cargill-AI/coco-transform-util |
| آدرس اینترنتی | https://pypi.org/project/ctu/ |
| مجوز | - |
# coco-transform-util
A python package to perform same transformation to coco-annotation as performed on the image.
## Installation
### Way 1
```bash
$ git clone https://github.com/Cargill-AI/coco-transform-util.git
$ cd coco-transform-util
$ python3 setup.py install
```
### Way 2
```bash
$ pip3 install git+https://github.com/Cargill-AI/coco-transform-util.git
<<< Username: <user_id or email>
<<< Password: <personal access token or SSH key>
```
Personal Access token looks like this `83b318cg875a5g302e5fdaag74afc8ceb6a91a2e`.
Reference: [How to generate Personal Access token](https://docs.github.com/en/github/authenticating-to-github/keeping-your-account-and-data-secure/creating-a-personal-access-token)
### Check installation
```python
import ctu
print(ctu.__version__)
```
## Benefits and Use Cases
1. Faster Model Training: Decrease the size of images and accordingly its annotation will be changed using this.
2. Flexibility: Rescaling of images and annotations to meet the need of Model/Framework.
3. Cost Saving: Lesser Computation requirement as images can be downscaled.
4. Interpretability: Annotation Visualization is also a part of this package.
5. Data Augmentation: \<more practical in future\>
6. Ability to handle other cases: Added Functionality such as cropping or padding of the annotation can help in multiple other cases such as:
- cropping out each object image & annotation from an original image
- cropping unnecessary area to zoom in on some particular area.
- converting images to 1:1 aspect ratio by using padding and/or cropping.
## How to use it?
### Core
There are four core modules inside that helps in performing operations on COCO Annotation. These can imported as shown below:
```python
from ctu import WholeCoco2SingleImgCoco, Coco2CocoRel, CocoRel2CocoSpecificSize, AggreagateCoco
```
It's recommended that you have look at `samples/example_core_modules.py` to understand and explore how to use these.
### Wrapper
Making use of wrappers can also come in handly to perform multiple operations in a much simpler and interpretable manner using the functions provided below:
```python
from ctu import (
sample_modif_step_di, get_modif_imag, get_modif_coco_annotation,
accept_and_process_modif_di, ImgTransform, Visualize
)
```
It's recommended that you have look at `samples/example_highlevel_function.py` to understand and explore how to use these.
Some sample data has also been provided with this package at `example_data/*` to explore these functionalities.
## Demo / Sample
A sample HTML created from Jupyter-Notebook, contating some sample results has been added to the path `samples/Demo-SampleOutput.html`.
## Version History
- v0.1: Core Modules: `WholeCoco2SingleImgCoco, Coco2CocoRel, CocoRel2CocoSpecificSize`. External Dependency on AMLEET package.
- v0.2: Removed the dependency on AMLEET package. Develop Core Module: `AggreagateCoco`. Addition of field "area" under "annotations" in coco.
- v0.3: Completed: Remove the out of frame coordinates in annotation. Update & add fields in "annotation" \> "images". Ability to create transparent and general mask `create_mask`. **In Development:** Ability to export transformed image, mask and annotation per image wise and as a whole too.
## Future
- Update the image fields in "images" key. (done)
- Crop out the annotation which are out-of-frame based on recent image shape. (done)
- Annotation Visualization + Mask creation can become a core feature to this library. (done)
- Rotate 90 degree left/right.
- Flip horizontally or vertically.
- COCO to other annotation format can also be a feature to this package.
## Push to pypi
```bash
$ python3 setup.py sdist
$ twine upload dist/*
```
نحوه نصب
نصب پکیج whl ctu-0.2.1:
pip install ctu-0.2.1.whl
نصب پکیج tar.gz ctu-0.2.1:
pip install ctu-0.2.1.tar.gz