Inference error and query

[li8bot]

After training the model, when trying to run inference with Cornernet using

boxes = gtf.Predict("./output/v4/101.jpg", vis_thresh=0.9, output_img="output.jpg")

following error is thrown. Is there a way to disable output image creation?

/usr/local/lib/python3.6/dist-packages/torch/nn/functional.py:2506: UserWarning: Default upsampling behavior when mode=bilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.
  "See the documentation of nn.Upsample for details.".format(mode))
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-25-923121f2acd1> in <module>()
----> 1 boxes = gtf.Predict("./output/v4/101.jpg", vis_thresh=0.9, output_img="output.jpg")
      2 from IPython.display import Image
      3 Image(filename='output.jpg')

1 frames
/content/Monk_Object_Detection/6_cornernet_lite/lib/core/vis_utils.py in draw_bboxes(image, bboxes, font_size, thresh, colors)
     23     for cat_name in bboxes:
     24         keep_inds = bboxes[cat_name][:, -1] > thresh
---> 25         cat_size  = cv2.getTextSize(cat_name +' : %.2f' % bboxes[cat_name][:, -1], cv2.FONT_HERSHEY_SIMPLEX, font_size, 2)[0]
     26 
     27         if colors is None:

TypeError: only size-1 arrays can be converted to Python scalars

[abhi-kumar]

@li8bot please check if the issue is resolved

[abhi-kumar]

Closing due to inactivity