Background Modules¶
-
bg_models.
apply_dilation
(image, kernel_size, kernel_type)[source]¶ Apply dilation to image with the specified kernel type and image
Parameters: - image – image to which apply opening
- kernel_size – size of the structuring element
- kernel_type – structuring element
Returns: image with opening applied
Return type: np.uint8
-
bg_models.
apply_opening
(image, kernel_size, kernel_type)[source]¶ Apply opening to image with the specified kernel type and image
Parameters: - image – image to which apply opening
- kernel_size – size of the structuring element
- kernel_type – structuring element
Returns: image with opening applied
Return type: np.uint8
-
bg_models.
compute_background_running_average
(frame, average, alpha, holes_frame)[source]¶ Calculate background using running average technique new background is equal to:
\(bg_{new} = (1-alpha)*bg_{old} + alpha*frame\)Parameters: - frame (np.uint16) – current frame for background update
- average (np.float32) – background model to update
- alpha (float) – update learning rate
- frame_holes_mask (np mask) –
Returns: updated background model
Return type: np.float32
-
bg_models.
compute_foreground_mask_from_func
(f_bg, current_frame, alpha)[source]¶ Extract binary foreground mask (1 foreground, 0 background) from f_bg background modeling function and update background model.
Parameters: - f_bg – background modeling function
- current_frame – current frame from which extract foreground
- alpha – update learning rate
Returns: foreground mask
Return type: np.uint8
-
bg_models.
cut_foreground
(image, mask)[source]¶ Cut the foreground from the image using the mask supplied
Parameters: - image – image from which cut foreground
- mask – mask of the foreground
Returns: image with only the foreground
Raise: IndexError error if the size of the image is wrong
-
bg_models.
get_bounding_boxes
(image)[source]¶ Return Bounding Boxes in the format x,y,w,h where (x,y) is the top left corner
Parameters: image – image from which retrieve the bounding boxes Returns: bounding boxes list Return type: list
-
bg_models.
get_bounding_boxes2
(image)[source]¶ Return Bounding Boxes in the format x,y,w,h where (x,y) is the top left corner
Parameters: image – image from which retrieve the bounding boxes Returns: bounding boxes array, where each element has the form (x, y, w, h, counter) with counter = 1 Return type: np.array