The load() function returns a new object, and as such does not use the one it is called on.
This commit updates the uses of model.load in this program so it will work as intended and not throw an error.
[evolution] Stitching for OpenCV 4.0
* stitching: wrap Stitcher::create for bindings
* provide method for consistent stitcher usage across languages
* samples: add python stitching sample
* port cpp stitching sample to python
* stitching: consolidate Stitcher create methods
* remove Stitcher::createDefault, it returns Stitcher, not Ptr<Stitcher> -> inconsistent API
* deprecate cv::createStitcher and cv::createStitcherScans in favor of Stitcher::create
* stitching: avoid anonymous enum in Stitcher
* ORIG_RESOL should be double
* add documentatiton
* stitching: improve documentation in Stitcher
* stitching: expose estimator in Stitcher
* remove ABI hack
* stitching: drop try_use_gpu flag
* OCL will be used automatically through T-API in OCL-enable paths
* CUDA won't be used unless user sets CUDA-enabled classes manually
* stitching: drop FeaturesFinder
* use Feature2D instead of FeaturesFinder
* interoperability with features2d module
* detach from dependency on xfeatures2d
* features2d: fix compute and detect to work with UMat vectors
* correctly pass UMats as UMats to allow OCL paths
* support vector of UMats as output arg
* stitching: use nearest interpolation for resizing masks
* fix warnings
* moved DIS optical flow from opencv_contrib to opencv, moved TVL1 from opencv to opencv_contrib
* fixed compile warning
* TVL1 optical flow example moved to opencv_contrib
- accepts script parameter (allows drag & drop from 'explorer')
- use script dir instead of current dir (can launch samples from 'samples/dnn')
- added 'pause' to show error messages (about missing numpy) instead of instant closing
* fix faster_rcnn sample crashed at PoolingInvoker operator() of pooling_layer.
* find_odj onmouse bug about find matched point status.
* reverted AutoBuffer back to std::vector
Following were the errors in the digits_video.py
1 ) The code was not working because data type of x was float however in "cv2.rectangle" we require integer .
2 ) After pressing the "esc" button the image windows did not destroy
So I amended following things:
1 ) ~converted data type of x to int.~ Used Python integer division (//)
2 ) used cv2.destroyAllWindows() to close all windows after the press of "esc" by user.