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add the ability to apply a masking image

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blakeblackshear 2019-02-19 21:15:57 -06:00
parent 2929773c10
commit f54fa2e56c
4 changed files with 9 additions and 2 deletions
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11
detect_objects.py
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@ -190,11 +190,14 @@ def main():
regions = [] regions = []
for region_string in REGIONS.split(':'): for region_string in REGIONS.split(':'):
region_parts = region_string.split(',') region_parts = region_string.split(',')
region_mask_image = cv2.imread("/config/{}".format(region_parts[4]), cv2.IMREAD_GRAYSCALE)
region_mask = np.where(region_mask_image==[0])
regions.append({ regions.append({
'size': int(region_parts[0]), 'size': int(region_parts[0]),
'x_offset': int(region_parts[1]), 'x_offset': int(region_parts[1]),
'y_offset': int(region_parts[2]), 'y_offset': int(region_parts[2]),
'min_object_size': int(region_parts[3]), 'min_object_size': int(region_parts[3]),
'mask': region_mask,
# Event for motion detection signaling # Event for motion detection signaling
'motion_detected': mp.Event(), 'motion_detected': mp.Event(),
# create shared array for storing 10 detected objects # create shared array for storing 10 detected objects
@ -259,7 +262,7 @@ def main():
motion_changed, motion_changed,
frame_shape, frame_shape,
region['size'], region['x_offset'], region['y_offset'], region['size'], region['x_offset'], region['y_offset'],
region['min_object_size'], region['min_object_size'], region['mask'],
True)) True))
motion_process.daemon = True motion_process.daemon = True
motion_processes.append(motion_process) motion_processes.append(motion_process)
@ -426,7 +429,7 @@ def process_frames(shared_arr, shared_output_arr, shared_frame_time, frame_lock,
# do the actual motion detection # do the actual motion detection
def detect_motion(shared_arr, shared_frame_time, frame_lock, frame_ready, motion_detected, motion_changed, def detect_motion(shared_arr, shared_frame_time, frame_lock, frame_ready, motion_detected, motion_changed,
frame_shape, region_size, region_x_offset, region_y_offset, min_motion_area, debug): frame_shape, region_size, region_x_offset, region_y_offset, min_motion_area, mask, debug):
# shape shared input array into frame for processing # shape shared input array into frame for processing
arr = tonumpyarray(shared_arr).reshape(frame_shape) arr = tonumpyarray(shared_arr).reshape(frame_shape)
@ -455,6 +458,10 @@ def detect_motion(shared_arr, shared_frame_time, frame_lock, frame_ready, motion
# convert to grayscale # convert to grayscale
gray = cv2.cvtColor(cropped_frame, cv2.COLOR_BGR2GRAY) gray = cv2.cvtColor(cropped_frame, cv2.COLOR_BGR2GRAY)
# apply image mask
gray[mask] = [255]
# apply gaussian blur # apply gaussian blur
gray = cv2.GaussianBlur(gray, (21, 21), 0) gray = cv2.GaussianBlur(gray, (21, 21), 0)