Extract sections from your image by using OpenAI CLIP and Facebooks Detr implemented on HuggingFace Transformers
Project description
clipcrop
- Extract sections of images from your image by using OpenAI's CLIP and YoloSmall implemented on HuggingFace Transformers
- Added new capability for segmentation using CLIP and Detr segmentation models
Installation
pip install clipcrop
Clip Crop
Extract sections of images from your image by using OpenAI's CLIP and YoloSmall implemented on HuggingFace Transformers
Extraction
from clipcrop import clipcrop
cc = clipcrop.ClipCrop("/content/sample.jpg")
DFE, DM, CLIPM, CLIPP = cc.load_models()
result = cc.extract_image(DFE, DM, CLIPM, CLIPP, "text content", num=2)
Captcha
Solve captacha images using CLIP and Object detection models. Ensure Tesseract is installed and executable in your path
from clipcrop import clipcrop
cc = clipcrop.ClipCrop(image_path)
DFE, DM, CLIPM, CLIPP = cc.load_models()
result = cc.auto_captcha(CLIPM, CLIPP, 4)
Clip Segmentation
Segment out images using Detr Panoptic segmentation pipeline and leverage CLIP models to derive the most probable one for your query
Extraction
from clipcrop import clipcrop
clipseg = clipcrop.ClipSeg("/content/input.png", "black colored car")
segmentor, clipmodel, clipprocessor = clipseg.load_models()
result = clipseg.segment_image(segmentor, clipmodel, clipprocessor)
Remove Background
from clipcrop import clipcrop
clipseg = clipcrop.ClipSeg("/content/input.png", "black colored car")
result = clipseg.remove_background()
Other projects
- SnapCode : Extract code blocks from images mixed with normal text
- HuggingFaceInference: Inference of different uses cases of finetued models
Contact
- Feel free to contact me on "nkumarvishnu25@gmail.com"
Project details
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