Picwish Photo Enhancer
Project description
PicWish API for Python 🎨✨
Enhance, generate, and process images without tokens, accounts, or watermarks, and enjoy unlimited usage!
Features
- ✅ Text-to-Image Generation: Create images from text prompts with customizable themes, sizes, and quality.
- ✅ Image Enhancement: Improve image quality without watermark.
- ✅ Background Removal: Remove background from images.
- ✅ OCR (Optical Character Recognition): Extract text from images with support for multiple languages and various output formats.
Installation
To get started, install the picwish
package using pip:
pip install picwish
Quick Examples 🚀
1. Text-to-Image Generation
Generate images based on a text prompt with customizable settings:
import asyncio
from picwish import PicWish, T2ITheme, T2IQuality
async def main():
picwish = PicWish()
# Generate images from text prompt
results = await picwish.text_to_image(
prompt='A girl',
theme=T2ITheme.ANIME,
width=616,
height=616,
batch_size=4,
quality=T2IQuality.HIGH
)
for result in results:
await result.download(f'{result.id}.png')
asyncio.run(main())
2. Image Enhancement
Enhance the quality of an image without a watermark:
import asyncio
from picwish import PicWish
async def main():
picwish = PicWish()
# Enhance an image
enhanced_image = await picwish.enhance('/path/to/input.jpg')
await enhanced_image.download('enhanced_output.jpg')
asyncio.run(main())
3. Background Removal
Remove the background from an image:
import asyncio
from picwish import PicWish
async def main():
picwish = PicWish()
# Remove background from an image
background_removed_image = await picwish.remove_background('/path/to/input.jpg')
await background_removed_image.download('background_removed_output.png')
asyncio.run(main())
4. OCR (Optical Character Recognition)
Extract text from images with support for multiple languages and output formats:
import asyncio
from picwish import PicWish, OCRFormat
async def main():
picwish = PicWish()
ocr_result = await picwish.ocr(
'input.jpg',
format=OCRFormat.TXT
)
print(await ocr_result.text())
# -----------------
# Download as PNG
ocr_result = await picwish.ocr(
'input.jpg',
format=OCRFormat.PDF
)
print(await ocr_result.download('result.pdf'))
asyncio.run(main())
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
picwish-0.4.0.tar.gz
(10.3 kB
view details)
Built Distribution
picwish-0.4.0-py3-none-any.whl
(10.7 kB
view details)
File details
Details for the file picwish-0.4.0.tar.gz
.
File metadata
- Download URL: picwish-0.4.0.tar.gz
- Upload date:
- Size: 10.3 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.10.5
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 7c17c472dc358999443f5a9a90b9c3d319747df625886211d427483d9275a98e |
|
MD5 | 47c54297bdeb422ef06b32a05a55f50b |
|
BLAKE2b-256 | 270a596e788b7cf5b69cf2b978021e08e49008f08739dc8061ca5ca7e8a77bac |
File details
Details for the file picwish-0.4.0-py3-none-any.whl
.
File metadata
- Download URL: picwish-0.4.0-py3-none-any.whl
- Upload date:
- Size: 10.7 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/4.0.2 CPython/3.10.5
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 67aeb4599a0a1f47a1ef1c846a23bb4c1b15b0199df582bbf63e0b6b4b0af77c |
|
MD5 | fb1e03c6201592394a9a219cda33d603 |
|
BLAKE2b-256 | 59c77f1ab2e1bfd7996c0b4a2eb500626a8ba984e25af7e0f0f7f1571fc38a5c |