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Benchmark

This document gives the performance of the series models for Chinese and English recognition.

Test Data

We collected 300 images for different real application scenarios to evaluate the overall OCR system, including contract samples, license plates, nameplates, train tickets, test sheets, forms, certificates, street view images, business cards, digital meter, etc. The following figure shows some images of the test set.

Measurement

Explanation:

  • The long size of the input for the text detector is 960.

  • The evaluation time-consuming stage is the complete stage from image input to result output, including image pre-processing and post-processing.

  • Intel Xeon 6148 is the server-side CPU model. Intel MKL-DNN is used in the test to accelerate the CPU prediction speed.

  • Snapdragon 855 is a mobile processing platform model.

Compares the model size and F-score:

Model Name Model Size
of the
Whole System(M)		 Model Size
of the Text
Detector(M)		 Model Size
of the Direction
Classifier(M)		 Model Size
of the Text
Recognizer (M)		 F-score
PP-OCRv2 11.6 3.0 0.9 8.6 0.5224
PP-OCR mobile 8.1 2.6 0.9 4.6 0.503
PP-OCR server 155.1 47.2 0.9 107 0.570

Compares the time-consuming on CPU and T4 GPU (ms):

Model Name CPU T4 GPU
PP-OCRv2 330 111
PP-OCR mobile 356 116
PP-OCR server 1056 200

More indicators of PP-OCR series models can be referred to PP-OCR Benchmark