I will ai, ml, dl, python, ocr, tensorflow, pytorch, keras, opencv
I will create powerful AI , Machine Learning, and Deep Learning models using Python . I specialize in building classification, regression (linear, logistic, polynomial), clustering (K-Means, DBSCAN), and forecasting models using libraries like Scikit-learn, TensorFlow , PyTorch , Keras , XGBoost, LightGBM, Pandas, NumPy, Matplotlib, and Seaborn.
I will create powerful AI , Machine Learning, and Deep Learning models using Python . I specialize in building classification, regression (linear, logistic, polynomial), clustering (K-Means, DBSCAN), and forecasting models using libraries like Scikit-learn, TensorFlow , PyTorch , Keras , XGBoost, LightGBM, Pandas, NumPy, Matplotlib, and Seaborn.
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keras - ocr ¶ keras - ocr provides out-of-the-box OCR models and an end-to-end training pipeline to build new OCR models. Please see the examples for more information. Installation ¶ keras - ocr supports Python >= 3.6 and TensorFlow >= 2.0.0.
Get started with computer vision! This guide covers OpenCV , TensorFlow / Keras , and PyTorch setup, ensuring your environment is ready for AI -powered image analysis.
Optical Character Recognition using TensorFlow
TensorFlow is an open-source machine learning library developed by the Google Brain team. We will be using TensorFlow for implementing OCR as TensorFlow provides a flexible and extensive framework to build customized OCR models. Importing Libraries For the implementation, we will be using open cv, numpy, matplotlib, tensorflow , and keras .
CnOCR: Awesome Chinese/English OCR Python toolkits based on PyTorch . It comes with 20+ well-trained models for different application scenarios and can be used directly after installation.
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Complete end-to-end training ¶ You may wish to train your own end-to-end OCR pipeline. Here's an example for how you might do it. Note that the image generator has many options not documented here (such as adding backgrounds and image augmentation). Check the documentation for the keras_ocr.tools.get_image_generator function for more details. Please note that, right now, we use a very ...
Integrating with Tensorflow
Discover how to integrate OpenCV and Tensorflow , two powerful computer vision tools, for seamless development of deep learning applications. Follow our comprehensive guide with code examples to understand the theory behind integration, how to preprocess images and use pre-trained models, and why integrating OpenCV and Tensorflow can provide higher accuracy and performance in your applications.
