Algorithms
This tutorial lists the OCR algorithms supported by PaddleOCR, as well as the models and metrics of each algorithm on English public datasets. It is mainly used for algorithm introduction and algorithm performance comparison. For more models on other datasets including Chinese, please refer to PP-OCRv3 models list.
Developers are welcome to contribute more algorithms! Please refer to add new algorithm guideline.
1. Two-stage OCR Algorithms
1.1 Text Detection Algorithms
Supported text detection algorithms (Click the link to get the tutorial):
On the ICDAR2015 dataset, the text detection result is as follows:
On Total-Text dataset, the text detection result is as follows:
Model |
Backbone |
Precision |
Recall |
Hmean |
Download link |
SAST |
ResNet50_vd |
89.63% |
78.44% |
83.66% |
trained model |
On CTW1500 dataset, the text detection result is as follows:
Model |
Backbone |
Precision |
Recall |
Hmean |
Download link |
FCE |
ResNet50_dcn |
88.39% |
82.18% |
85.27% |
trained model |
DRRG |
ResNet50_vd |
89.92% |
80.91% |
85.18% |
trained model |
Note: Additional data, like icdar2013, icdar2017, COCO-Text, ArT, was added to the model training of SAST. Download English public dataset in organized format used by PaddleOCR from:
1.2 Text Recognition Algorithms
Supported text recognition algorithms (Click the link to get the tutorial):
Refer to DTRB, the training and evaluation result of these above text recognition (using MJSynth and SynthText for training, evaluate on IIIT, SVT, IC03, IC13, IC15, SVTP, CUTE) is as follow:
1.3 Text Super-Resolution Algorithms
Supported text super-resolution algorithms (Click the link to get the tutorial):
On the TextZoom public dataset, the effect of the algorithm is as follows:
1.4 Formula Recognition Algorithm
Supported formula recognition algorithms (Click the link to get the tutorial):
On the CROHME handwritten formula dataset, the effect of the algorithm is as follows:
2. End-to-end OCR Algorithms
Supported end-to-end algorithms (Click the link to get the tutorial):
3. Table Recognition Algorithms
Supported table recognition algorithms (Click the link to get the tutorial):
On the PubTabNet dataset, the algorithm result is as follows:
Supported KIE algorithms (Click the link to get the tutorial):
On wildreceipt dataset, the algorithm result is as follows:
On XFUND_zh dataset, the algorithm result is as follows: