PaddleOCR/latest/ppocr/visualization

[giscus[bot]]

PaddleOCR/latest/ppocr/visualization

Awesome multilingual OCR toolkits based on PaddlePaddle (practical ultra lightweight OCR system, support 80+ languages recognition, provide data annotation and synthesis tools, support training and deployment among server, mobile, embedded and IoT devices)

https://paddlepaddle.github.io/PaddleOCR/latest/ppocr/visualization.html

[zmxccxy]

怎么得到文档中效果？就是原图和识别后的文字有多色框选效果？

用下面的代码进行可视化，没有多色框选效果。

显示结果

from PIL import Image
result = result[0]
image = original_image.convert('RGB')
boxes = [line[0] for line in result]
txts = [line[1][0] for line in result]
scores = [line[1][1] for line in result]
im_show = draw_ocr(image, boxes, txts, scores)
im_show = Image.fromarray(im_show)
im_show.save('result.jpg')

[GreatV]

The link you provided refers to the PaddleOCR Visualization Module: PaddleOCR/latest/ppocr/visualization. This module is a feature of PaddleOCR, an advanced OCR toolkit based on PaddlePaddle, which supports a variety of functionalities for Optical Character Recognition (OCR). Below is an overview of its key aspects and possible utilities:

About the Visualization Module

The Visualization section in PaddleOCR is designed to help users better understand and interpret the OCR results by providing visual representations of the detection and recognition outputs. Visualization is crucial during model development and debugging, as it allows users to:

1. Verify the text detection results: Check if the bounding boxes are correctly drawn around the detected text regions.
2. Validate recognition outputs: Match the model's recognized text with the actual content.
3. Analyze model performance: Identify areas where the model might be underperforming (e.g., misaligned boxes or incorrect text recognition).

General Features of PaddleOCR

• Multilingual Support: Recognizes text in over 80 languages.
• Lightweight and Efficient: Designed for deployment across various platforms, including servers, mobile, embedded systems, and IoT devices.
• Tools for Annotation and Synthesis: Provides utilities for creating and augmenting datasets, crucial for training OCR models.

Getting Started

If you're new to PaddleOCR, you might want to refer to the Quick Start Guide: PaddleOCR Quick Start. It provides step-by-step instructions for setting up PaddleOCR, running inference, and training custom models.

Suggestions

• If you have specific questions about using the visualization tool or its integration with your OCR pipeline, the Quick Start Guide or discussions like this GitHub thread might offer additional insights.
• For advanced usage, such as customizing the visualization outputs or troubleshooting issues, refer to the PaddleOCR GitHub Repository.

Let me know if you need further assistance!

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Response generated by feifei-bot | chatgpt-4o-latest