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Home / v0.9.0
Name Modified Size InfoDownloads / Week
Parent folder
digitStruct.mat 2024-09-25 63.0 kB
vitstr_small-d28b8d92.weights.h5 2024-08-30 86.0 MB
vitstr_base-9ad6eb84.weights.h5 2024-08-30 341.5 MB
sar_resnet31-5a58806c.weights.h5 2024-08-30 229.5 MB
parseq-4152a87e.weights.h5 2024-08-30 95.8 MB
master-d7fdaeff.weights.h5 2024-08-30 235.8 MB
crnn_vgg16_bn-9c188f45.weights.h5 2024-08-30 63.4 MB
crnn_mobilenet_v3_small-54850265.weights.h5 2024-08-30 8.8 MB
crnn_mobilenet_v3_large-c64045e5.weights.h5 2024-08-30 18.7 MB
linknet_resnet50-6bf6c8b5.weights.h5 2024-08-30 116.0 MB
linknet_resnet34-9d772be5.weights.h5 2024-08-30 87.1 MB
linknet_resnet18-615a82c5.weights.h5 2024-08-30 46.5 MB
fast_tiny-d7379d7b.weights.h5 2024-08-30 54.8 MB
fast_small-44b27eb6.weights.h5 2024-08-30 60.0 MB
fast_base-f2c6c736.weights.h5 2024-08-30 66.6 MB
db_resnet50-649fa22b.weights.h5 2024-08-30 101.7 MB
db_mobilenet_v3_large-ee2e1dbe.weights.h5 2024-08-30 18.0 MB
vit_s-69bc459e.weights.h5 2024-08-30 85.8 MB
vit_b-c64705bd.weights.h5 2024-08-30 341.1 MB
vgg16_bn_r-b4d69212.weights.h5 2024-08-30 59.3 MB
textnet_tiny-a29eeb4a.weights.h5 2024-08-30 43.6 MB
textnet_small-1c2df0e3.weights.h5 2024-08-30 48.7 MB
textnet_base-8b4b89bc.weights.h5 2024-08-30 55.3 MB
resnet50-82358f34.weights.h5 2024-08-30 95.8 MB
resnet34_wide-b18fdf79.weights.h5 2024-08-30 341.4 MB
resnet34-03967df9.weights.h5 2024-08-30 85.8 MB
resnet31-ab75f78c.weights.h5 2024-08-30 184.6 MB
resnet18-f42d3854.weights.h5 2024-08-30 45.2 MB
mobilenet_v3_small_r-dd50218d.weights.h5 2024-08-30 7.0 MB
mobilenet_v3_small_page_orientation-0071d55d.weights.h5 2024-08-30 6.5 MB
mobilenet_v3_small_crop_orientation-ef019b6b.weights.h5 2024-08-30 6.5 MB
mobilenet_v3_small-3fcebad7.weights.h5 2024-08-30 7.0 MB
mobilenet_v3_large_r-eef2e3c6.weights.h5 2024-08-30 18.0 MB
mobilenet_v3_large-d857506e.weights.h5 2024-08-30 18.0 MB
magc_resnet31-16aa7d71.weights.h5 2024-08-30 185.0 MB
mobilenet_v3_small_crop_orientation-c164fc5a.zip 2024-08-16 5.7 MB
README.md 2024-08-08 9.3 kB
v0.9.0 source code.tar.gz 2024-08-08 3.6 MB
v0.9.0 source code.zip 2024-08-08 3.9 MB
Totals: 39 Items   3.3 GB 0

Note: docTR 0.9.0 requires python >= 3.9 Note: docTR 0.9.0 requires either TensorFlow >= 2.11.0 or PyTorch >= 1.12.0.

What's Changed

Soft Breaking Changes 🛠

  • The default detection model changed from db_resnet50 to fast_base. NOTE: Can be reverted by passing the detection model predictor = ocr_predictor(det_arch="db_resnet50", pretrained=True)
  • The default value of resolve_blocks changed from True to False NOTE: Can be reverted by passing resolve_blocks=True to the ocr_predictor

New features

  • Fast models got pretrained checkpoints by @odulcy-mindee @felixdittrich92
  • Introducing a contributions module which replaces the obj detection and builds a place for more pipelines by @felixdittrich92
  • Improved orientation detection by @felixdittrich92 @odulcy-mindee
  • Improved and updated API template by @felixdittrich92
  • Include objectness_score in results by @felixdittrich92
  • Add word crop general orientation to output by @felixdittrich92
  • Split library into parts (optional dependencies) by @felixdittrich92
  • Add page orientation predictor by @felixdittrich92 @odulcy-mindee
  • Add onnx inference doc by @felixdittrich92

✨ Installation ✨

We have splitted docTR into some optional parts to make it a bit more lightweight and to exclude parts which are not required for inference. Optional parts are: * visualization (to support .show()) * html support (to support .from_url(...)) * contribution module

# for TensorFlow without any optional dependencies
pip install "python-doctr[tf]"

# for PyTorch without any optional dependencies
pip install "python-doctr[torch]"

# Installs pytorch and all available optional parts
pip install "python-doctr[torch,viz,html,contib]"

✨ ONNX and OnnxTR ✨

We have build a standalone library to provide a super lightweight way to use existing docTR onnx exported models or your custom onces.

benefits: - kown docTR interface (ocr_predictor, etc.) - no PyTorch or TensorFlow required - build on top of onnxruntime - more lightweight package with faster inference latency and less required resources - 8-Bit quantized models for faster inference on CPU

Give it a try and check it out: OnnxTR docTR docs: ONNX / OnnxTR

Screenshot from 2024-08-09 09-15-37

What's Changed

Breaking Changes 🛠

New Features

Bug Fixes

Improvements

Miscellaneous

New Contributors

Full Changelog: https://github.com/mindee/doctr/compare/v0.8.1...v0.9.0

Source: README.md, updated 2024-08-08