easyidp.visualize.draw_polygon_on_img#

easyidp.visualize.draw_polygon_on_img(img_name, img_path, poly_coord, corrected_poly_coord=None, title=None, save_as=None, show=False, color='red', alpha=0.5, dpi=72)#

Plot one polygon on given image.

Parameters:

  • img_name (str) – the image file name.

  • img_path (str) – the file path of image

  • poly_coord (np.ndarray) – the 2D polygon pixel coordinate on the image

  • corrected_poly_coord (np.ndarray, optional) – the corrected 2D polygon pixel coordiante on the image (if have), by default None

  • title (str, optional) – The image title displayed on the top, by default None -> Projection on [img_name]

  • save_as (str, optional) – file path to save the output figure, by default None

  • show (bool, optional) – whether display (in jupyter notebook) or popup (in command line) the figure, by default False

  • color (str, optional) – the polygon line color, by default ‘red’

  • alpha (float, optional) – the polygon transparency, by default 0.5

  • dpi (int, optional) – the dpi of produced figure, by default 72

Example

Data prepare

>>> import easyidp as idp

>>> p4d = idp.Pix4D(
...     test_data.pix4d.lotus_folder,
...     raw_img_folder=test_data.pix4d.lotus_photos,
...     param_folder=test_data.pix4d.lotus_param
... )

>>> plot =  np.array([   # N1E1 plot geo coordinate
...     [ 368020.2974959 , 3955511.61264302,      97.56272272],
...     [ 368022.24288365, 3955512.02973983,      97.56272272],
...     [ 368022.65361232, 3955510.07798313,      97.56272272],
...     [ 368020.69867274, 3955509.66725421,      97.56272272],
...     [ 368020.2974959 , 3955511.61264302,      97.56272272]
... ])

Then do backward projection, find the previous ROI positions on the raw images.

>>> out_dict = p4d.back2raw_crs(plot, distort_correct=True)
>>> out_dict["DJI_0177.JPG"]
array([[ 137.10982937, 2359.55887614],
       [ 133.56116243, 2107.13954299],
       [ 384.767746  , 2097.05639105],
       [ 388.10993307, 2350.41225998],
       [ 137.10982937, 2359.55887614]])

The using this function to check one polygon on raw images

>>> img_name = "DJI_0198.JPG"
>>> photo = p4d.photos[img_name]

>>> idp.visualize.draw_polygon_on_img(
...     img_name, photo.path, out_dict[img_name],
...     save_as="p4d_back2raw_single_view.png")

It will get the following figure:

p4d_back2raw_single_view.png'

Add an corrected polygon (here manual shifting 10 pixels just as example), and change the color and alpha info:

>>> corrected_poly = out_dict[img_name] + np.array([10,10])

>>> idp.visualize.draw_polygon_on_img(
...     img_name, photo.path, out_dict[img_name], corrected_poly,
...     save_as="p4d_back2raw_single_view2.png",
...     color='blue', alpha=0.3)

It will get the following figure:

p4d_back2raw_single_view2.png'