本文整理匯總了Python中vehicle.Vehicle.contains方法的典型用法代碼示例。如果您正苦於以下問題：Python Vehicle.contains方法的具體用法？Python Vehicle.contains怎麽用？Python Vehicle.contains使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類vehicle.Vehicle的用法示例。
在下文中一共展示了Vehicle.contains方法的1個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: process_pipeline
# 需要導入模塊: from vehicle import Vehicle [as 別名]
# 或者: from vehicle.Vehicle import contains [as 別名]
def process_pipeline(frame, verbose=False):
detected_vehicles = []
img_blend_out = frame.copy()
# return bounding boxes detected by SSD
ssd_bboxes = process_frame_bgr_with_SSD(frame, ssd_model, bbox_helper, allow_classes=[7], min_confidence=0.3)
for row in ssd_bboxes:
label, confidence, x_min, y_min, x_max, y_max = row
x_min = int(round(x_min * frame.shape[1]))
y_min = int(round(y_min * frame.shape[0]))
x_max = int(round(x_max * frame.shape[1]))
y_max = int(round(y_max * frame.shape[0]))
proposed_vehicle = Vehicle(x_min, y_min, x_max, y_max)
if not detected_vehicles:
detected_vehicles.append(proposed_vehicle)
else:
for i, vehicle in enumerate(detected_vehicles):
if vehicle.contains(*proposed_vehicle.center):
pass # go on, bigger bbox already detected in that position
elif proposed_vehicle.contains(*vehicle.center):
detected_vehicles[i] = proposed_vehicle # keep the bigger window
else:
detected_vehicles.append(proposed_vehicle)
# draw bounding boxes of detected vehicles on frame
for vehicle in detected_vehicles:
vehicle.draw(img_blend_out, color=(0, 255, 255), thickness=2)
h, w = frame.shape[:2]
off_x, off_y = 30, 30
thumb_h, thumb_w = (96, 128)
# add a semi-transparent rectangle to highlight thumbnails on the left
mask = cv2.rectangle(frame.copy(), (0, 0), (w, 2 * off_y + thumb_h), (0, 0, 0), thickness=cv2.FILLED)
img_blend_out = cv2.addWeighted(src1=mask, alpha=0.3, src2=img_blend_out, beta=0.8, gamma=0)
# create list of thumbnails s.t. this can be later sorted for drawing
vehicle_thumbs = []
for i, vehicle in enumerate(detected_vehicles):
x_min, y_min, x_max, y_max = vehicle.coords
vehicle_thumbs.append(frame[y_min:y_max, x_min:x_max, :])
# draw detected car thumbnails on the top of the frame
for i, thumbnail in enumerate(sorted(vehicle_thumbs, key=lambda x: np.mean(x), reverse=True)):
vehicle_thumb = cv2.resize(thumbnail, dsize=(thumb_w, thumb_h))
start_x = 300 + (i+1) * off_x + i * thumb_w
img_blend_out[off_y:off_y + thumb_h, start_x:start_x + thumb_w, :] = vehicle_thumb
# write the counter of cars detected
font = cv2.FONT_HERSHEY_SIMPLEX
cv2.putText(img_blend_out, 'Vehicles in sight: {:02d}'.format(len(detected_vehicles)),
(20, off_y + thumb_h // 2), font, 0.8, (255, 255, 255), 2, cv2.LINE_AA)
return img_blend_out