v0.2.0
What's Changed
- Added 8-Bit quantized models
- Added Dockerfile and CI for CPU/GPU Usage
8-Bit quantized models
8-Bit quantized variants of all models was added (expect: the FAST models - which are already reparameterized)
from onnxtr.models import ocr_predictor, detection_predictor, recognition_predictor
predictor = ocr_predictor(det_arch="db_resnet50", reco_arch="crnn_vgg16_bn", load_in_8_bit=True)
det_predictor = detection_predictor("db_resnet50", load_in_8_bit=True)
reco_predictor = recognition_predictor("parseq", load_in_8_bit=True)
- CPU benchmarks:
Library | FUNSD (199 pages) | CORD (900 pages) |
---|---|---|
docTR (CPU) - v0.8.1 | ~1.29s / Page | ~0.60s / Page |
OnnxTR (CPU) - v0.1.2 | ~0.57s / Page | ~0.25s / Page |
OnnxTR (CPU) 8-bit - v0.1.2 | ~0.38s / Page | ~0.14s / Page |
EasyOCR (CPU) - v1.7.1 | ~1.96s / Page | ~1.75s / Page |
PyTesseract (CPU) - v0.3.10 | ~0.50s / Page | ~0.52s / Page |
Surya (line) (CPU) - v0.4.4 | ~48.76s / Page | ~35.49s / Page |