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Comments (2)

suyashcjoshi avatar suyashcjoshi commented on July 20, 2024 1

Thank you so much, that worked. I'll write a blog about this library with a business card example :)

from keras-ocr.

faustomorales avatar faustomorales commented on July 20, 2024

Hi @SuyashJoshi - It looks like you're using an older version of TensorFlow. If you upgrade to TensorFlow >= 2.0.0 with pip install --upgrade tensorflow, I believe it will likely resolve this issue.

For what it's worth, I ran the pipeline on your image using the following code and it did a decent job, I think.

import matplotlib.pyplot as plt

import keras_ocr

# keras-ocr will automatically download pretrained
# weights for the detector and recognizer.
pipeline = keras_ocr.pipeline.Pipeline()

image = keras_ocr.tools.read('https://user-images.githubusercontent.com/395039/71770765-80b5ad80-2ee5-11ea-836e-ec0792bd3be8.jpg')

# Predictions is a list of (text, box) tuples.
predictions = pipeline.recognize(image=image)

# Plot the results.
fig, ax = plt.subplots(figsize=(15, 8))
ax.imshow(keras_ocr.tools.drawBoxes(image, predictions, boxes_format='predictions'))
for text, box in predictions:
    ax.annotate(s=text, xy=box[0], xytext=box[0] -50, arrowprops={'arrowstyle': '->'})
plt.show()
fig.tight_layout()
fig.savefig('example.jpg')

example business card results

from keras-ocr.

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