from crafter import Crafter
crafter = Crafter()
prediction = crafter('test.png')
#for p1, p2, p3, p4 in prediction['boxes']:
#    print(p1, p2, p3, p4)
print(prediction['times'])

from craft_text_detector import (
    read_image,
    load_craftnet_model,
    load_refinenet_model,
    get_prediction,
    export_detected_regions,
    export_extra_results,
    empty_cuda_cache
)

# set image path and export folder directory
image = 'test.png'
output_dir = 'outputs/'

# read image
image = read_image(image)

# load models
refine_net = load_refinenet_model(cuda=False)
craft_net = load_craftnet_model(cuda=False)

# perform prediction
prediction_result = get_prediction(
    image=image,
    craft_net=craft_net,
    refine_net=refine_net,
    text_threshold=0.7,
    link_threshold=0.4,
    low_text=0.4,
    cuda=False,
    long_size=700 #1280
)

# export detected text regions
exported_file_paths = export_detected_regions(
    image=image,
    regions=prediction_result["boxes"],
    output_dir=output_dir,
    rectify=True
)

Traceback (most recent call last):
  File "/home/pi/crafter/convert/craftnet.py", line 52, in <module>
    craftnet_to_onnx(craftnet, "crafter/resources/craftnet.onnx")
  File "/home/pi/crafter/convert/craftnet.py", line 47, in craftnet_to_onnx
    np.testing.assert_allclose(feature.numpy(), ort_outs[1], rtol=1e-03, atol=1e-05)
  File "/home/pi/.local/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 1527, in assert_allclose
    assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
  File "/home/pi/.local/lib/python3.9/site-packages/numpy/testing/_private/utils.py", line 844, in assert_array_compare
    raise AssertionError(msg)
AssertionError: 
Not equal to tolerance rtol=0.001, atol=1e-05

Mismatched elements: 1 / 609280 (0.000164%)
Max absolute difference: 1.9073486e-05
Max relative difference: 0.05192127
 x: array([[[[0.000000e+00, 0.000000e+00, 0.000000e+00, ..., 0.000000e+00,
          0.000000e+00, 0.000000e+00],
         [0.000000e+00, 0.000000e+00, 0.000000e+00, ..., 0.000000e+00,...
 y: array([[[[0.000000e+00, 0.000000e+00, 0.000000e+00, ..., 0.000000e+00,
          0.000000e+00, 0.000000e+00],
         [0.000000e+00, 0.000000e+00, 0.000000e+00, ..., 0.000000e+00,...