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ordaktaktak/
Document-Scanner

Name: Document-Scanner
Availability: InStock

1505.04597

mit

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Document Scanner :bookmark_tabs:

U-Net Like Pretrained Model For Scene Document Detection (pytorch, Semantic Segmentation)

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Usage
Examples

Dependencies

Install Dependencies $ pip install -r requirements.txt
Download model weights Here, place it in Structure/

Usage:

scanner = Scanner("Structure/Scanner-Detector.pth", config_)

Load model.

python

  org = cv2.imread(fname)
  org_gray = cv2.cvtColor(org, cv2.COLOR_RGB2GRAY)
  org_resize = cv2.resize(org_gray, (256, 256), interpolation = cv2.INTER_AREA)

Read image in gray scale and resize it to 256*256.

mask = scanner.ScanView(org_resize)

Detect document area.

python

  paper, approx = ExtractPaper(org_gray, mask)
  org = DrawBox(org, approx)

Extract document and draw bounding box on original image.

paper = EnhacePaper(paper)

Enhance extracted document.

ordaktaktak/Document-Scanner

Document Scanner :bookmark_tabs:

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Dependencies

Usage:

ordaktaktak/
Document-Scanner