{"library":"rapidocr-onnxruntime","title":"RapidOCR-ONNXRuntime","description":"RapidOCR-ONNXRuntime is a Python library providing cross-platform Optical Character Recognition (OCR) capabilities, leveraging the ONNX Runtime inference engine for high-speed and efficient offline deployments. It converts PaddleOCR models to the ONNX format, offering a performant solution for text recognition. The library supports multiple programming languages, with its Python interface primarily integrated into the broader RapidOCR ecosystem. The current PyPI version is 1.4.4, released in January 2025, and the associated GitHub project is actively maintained with frequent updates.","language":"python","status":"active","last_verified":"Sat May 16","install":{"commands":["pip install rapidocr-onnxruntime"],"cli":null},"imports":["from rapidocr import RapidOCR"],"auth":{"required":false,"env_vars":[]},"quickstart":{"code":"from rapidocr import RapidOCR\nfrom PIL import Image\nimport requests\nfrom io import BytesIO\n\n# Initialize the OCR engine\nengine = RapidOCR()\n\n# Example image URL (replace with your image path or URL)\nimg_url = \"https://www.modelscope.cn/models/RapidAI/RapidOCR/resolve/master/resources/test_files/ch_en_num.jpg\"\n\n# Download and open the image\nresponse = requests.get(img_url)\nimage = Image.open(BytesIO(response.content))\n\n# Perform OCR\nresult = engine(image)\n\n# Print the OCR results\nprint(result)\n\n# Optionally, visualize the result (requires OpenCV installed and a display environment)\n# import cv2\n# import numpy as np\n# image_np = np.array(image)\n# for box, text, score in result:\n#     box = np.array(box).astype(np.int32).reshape((-1, 1, 2))\n#     cv2.polylines(image_np, [box], True, (0, 255, 0), 2)\n#     cv2.putText(image_np, text, (box, box - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)\n# cv2.imshow(\"OCR Result\", image_np)\n# cv2.waitKey(0)\n# cv2.destroyAllWindows()","lang":"python","description":"This quickstart demonstrates how to initialize the RapidOCR engine and perform OCR on an image. The `RapidOCR` class handles model loading and inference using the ONNX Runtime backend provided by `rapidocr-onnxruntime`. The example downloads an image from a URL, processes it, and prints the detected text along with bounding box information.","tag":null,"tag_description":null,"last_tested":null,"results":[]},"compatibility":{"tag":null,"tag_description":null,"last_tested":"2026-05-16","installed_version":"1.4.4","pypi_latest":"1.4.4","is_stale":false,"summary":{"python_range":"3.10–3.9","success_rate":50,"avg_install_s":10.2,"avg_import_s":null,"wheel_type":"wheel"},"results":[{"runtime":"python:3.10-alpine","python_version":"3.10","os_libc":"alpine (musl)","variant":"rapidocr-onnxruntime","exit_code":1,"wheel_type":null,"failure_reason":"build_error","import_side_effects":null,"install_time_s":null,"import_time_s":null,"mem_mb":null,"disk_size":null},{"runtime":"python:3.10-slim","python_version":"3.10","os_libc":"slim (glibc)","variant":"rapidocr-onnxruntime","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"broken","install_time_s":13.2,"import_time_s":null,"mem_mb":null,"disk_size":"447M"},{"runtime":"python:3.11-alpine","python_version":"3.11","os_libc":"alpine (musl)","variant":"rapidocr-onnxruntime","exit_code":1,"wheel_type":null,"failure_reason":"build_error","import_side_effects":null,"install_time_s":null,"import_time_s":null,"mem_mb":null,"disk_size":null},{"runtime":"python:3.11-slim","python_version":"3.11","os_libc":"slim (glibc)","variant":"rapidocr-onnxruntime","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"broken","install_time_s":7.9,"import_time_s":null,"mem_mb":null,"disk_size":"399M"},{"runtime":"python:3.12-alpine","python_version":"3.12","os_libc":"alpine (musl)","variant":"rapidocr-onnxruntime","exit_code":1,"wheel_type":null,"failure_reason":"build_error","import_side_effects":null,"install_time_s":null,"import_time_s":null,"mem_mb":null,"disk_size":null},{"runtime":"python:3.12-slim","python_version":"3.12","os_libc":"slim (glibc)","variant":"rapidocr-onnxruntime","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"broken","install_time_s":7.9,"import_time_s":null,"mem_mb":null,"disk_size":"386M"},{"runtime":"python:3.13-alpine","python_version":"3.13","os_libc":"alpine (musl)","variant":"rapidocr-onnxruntime","exit_code":1,"wheel_type":null,"failure_reason":"build_error","import_side_effects":null,"install_time_s":null,"import_time_s":null,"mem_mb":null,"disk_size":null},{"runtime":"python:3.13-slim","python_version":"3.13","os_libc":"slim (glibc)","variant":"rapidocr-onnxruntime","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"broken","install_time_s":7.5,"import_time_s":null,"mem_mb":null,"disk_size":"383M"},{"runtime":"python:3.9-alpine","python_version":"3.9","os_libc":"alpine (musl)","variant":"rapidocr-onnxruntime","exit_code":1,"wheel_type":null,"failure_reason":"timeout","import_side_effects":null,"install_time_s":null,"import_time_s":null,"mem_mb":null,"disk_size":null},{"runtime":"python:3.9-slim","python_version":"3.9","os_libc":"slim (glibc)","variant":"rapidocr-onnxruntime","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"broken","install_time_s":14.6,"import_time_s":null,"mem_mb":null,"disk_size":"439M"}]}}