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working dynamic regions, but messy

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Blake Blackshear
2019-12-31 14:59:22 -06:00
parent be1673b00a
commit 9cc46a71cb
6 changed files with 564 additions and 94 deletions
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45
frigate/util.py
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@@ -16,22 +16,22 @@ def ReadLabelFile(file_path):
return ret
def calculate_region(frame_shape, xmin, ymin, xmax, ymax):
# size is 50% larger than longest edge
size = max(xmax-xmin, ymax-ymin)
# size is larger than longest edge
size = int(max(xmax-xmin, ymax-ymin)*1.5)
# if the size is too big to fit in the frame
if size > min(frame_shape[0], frame_shape[1]):
size = min(frame_shape[0], frame_shape[1])
# x_offset is midpoint of bounding box minus half the size
x_offset = int(((xmax-xmin)/2+xmin)-size/2)
x_offset = int((xmax-xmin)/2.0+xmin-size/2.0)
# if outside the image
if x_offset < 0:
x_offset = 0
elif x_offset > (frame_shape[1]-size):
x_offset = (frame_shape[1]-size)
# x_offset is midpoint of bounding box minus half the size
y_offset = int(((ymax-ymin)/2+ymin)-size/2)
# y_offset is midpoint of bounding box minus half the size
y_offset = int((ymax-ymin)/2.0+ymin-size/2.0)
# if outside the image
if y_offset < 0:
y_offset = 0
@@ -40,13 +40,44 @@ def calculate_region(frame_shape, xmin, ymin, xmax, ymax):
return (size, x_offset, y_offset)
def compute_intersection_rectangle(box_a, box_b):
return {
'xmin': max(box_a['xmin'], box_b['xmin']),
'ymin': max(box_a['ymin'], box_b['ymin']),
'xmax': min(box_a['xmax'], box_b['xmax']),
'ymax': min(box_a['ymax'], box_b['ymax'])
}
def compute_intersection_over_union(box_a, box_b):
# determine the (x, y)-coordinates of the intersection rectangle
intersect = compute_intersection_rectangle(box_a, box_b)
# compute the area of intersection rectangle
inter_area = max(0, intersect['xmax'] - intersect['xmin'] + 1) * max(0, intersect['ymax'] - intersect['ymin'] + 1)
if inter_area == 0:
return 0.0
# compute the area of both the prediction and ground-truth
# rectangles
box_a_area = (box_a['xmax'] - box_a['xmin'] + 1) * (box_a['ymax'] - box_a['ymin'] + 1)
box_b_area = (box_b['xmax'] - box_b['xmin'] + 1) * (box_b['ymax'] - box_b['ymin'] + 1)
# compute the intersection over union by taking the intersection
# area and dividing it by the sum of prediction + ground-truth
# areas - the interesection area
iou = inter_area / float(box_a_area + box_b_area - inter_area)
# return the intersection over union value
return iou
# convert shared memory array into numpy array
def tonumpyarray(mp_arr):
return np.frombuffer(mp_arr.get_obj(), dtype=np.uint8)
def draw_box_with_label(frame, x_min, y_min, x_max, y_max, label, score, area):
def draw_box_with_label(frame, x_min, y_min, x_max, y_max, label, info):
color = COLOR_MAP[label]
display_text = "{}: {}% {}".format(label,int(score*100),int(area))
display_text = "{}: {}".format(label, info)
cv2.rectangle(frame, (x_min, y_min),
(x_max, y_max),
color, 2)