To install project made
git clone
pip install -r requirements.txt
All user methods are in
Danila class
makes object and loads all neuro models
danila = Danila()
returns string - class of rama using CNN network
def rama_classify(self, image_path)
returns image_path in danilav1 root with drawn rectangle and text - rama and its class
def rama_detect(self, image_path)
returns image_path in danilav1 root with cut_rama
def rama_cut(self, image_path)
returns image-path of cut rama with drawn text areas
def text_detect_cut(self, image_path)
returns image-path of image with drawn text areas
def text_detect_cut(self, image_path)
scripts illustrates methods using
demo_1
demo_2
demo_3
demo_4
demo_5
to start work you should
add directory yolo
cd yolo/
git clone https://github.com/ultralytics/yolov5.git
you should paste directory models just in root
https://disk.yandex.ru/client/disk/%D0%9A%D0%BE%D0%BC%D0%BF%D1%8C%D1%8E%D1%82%D0%B5%D1%80%20NUFDR0019114/%D0%A0%D0%90%D0%9C%D0%90
Metadata
Release files for danila 1.0.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| danila-1.0.0.tar.gz | 3.4 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| danila-1.0.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 5.9 kB
Release files / danila-1.0.0.tar.gz
| Download URL | danila-1.0.0.tar.gz |
|---|---|
| Size | 3.4 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Release files / danila-1.0.0-py3-none-any.whl
| Download URL | danila-1.0.0-py3-none-any.whl |
|---|---|
| Size | 2.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
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twine/5.0.0 CPython/3.9.13
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