'value': 'Start'
},
{
'type': 'checkbox',
'name': 'Checkbox',
'value': True
},
{
'type': 'select',
'name': 'Select',
'value': 1,
'values': ['Red', 'Green', 'Blue']
},
]
properties_window = viz.properties(properties)
def properties_callback(event):
if event['event_type'] == 'PropertyUpdate':
prop_id = event['propertyId']
value = event['value']
if prop_id == 0:
new_value = value + '_updated'
elif prop_id == 1:
new_value = value + '0'
elif prop_id == 2:
new_value = 'Stop' if properties[prop_id][
'value'] == 'Start' else 'Start'
else:
new_value = value
properties[prop_id]['value'] = new_value
class AMFVisdom:
DEFAULT_CONFIG = {"bounding_box_threshold": 200}
def __init__(self, video):
self.viz = Visdom(port=8090)
self.viz_config = self.DEFAULT_CONFIG
self.ctl = None
self.frame_list, video_meta = extract_video(video)
self.frame_fps = video_meta["fps"]
self.amf = AdvancedMotionFilter(
ssc_model="model/scene_knn_model",
frame_width=video_meta["width"],
frame_height=video_meta["height"],
)
def init_control_panel(self):
def update(name):
return self.viz.properties(
[
{
"type":
"number",
"name":
"Bounding Box Threshold",
"value":
self.viz_config.get("bounding_box_threshold", 200),
},
{
"type": "checkbox",
"name": "History Variance",
"value": self.amf.amf_history_variance,
},
{
"type": "number",
"name": "History Variance Threshold",
"value": self.amf.amf_variance_threshold,
},
{
"type": "number",
"name": "History Variance Sample Amount",
"value": self.amf.amf_variance_sample_amount,
},
{
"type": "checkbox",
"name": "Large Background Movement",
"value": self.amf.amf_drop_large_bg_motion,
},
{
"type": "checkbox",
"name": "Dynamic Bounding Box",
"value": self.amf.amf_dynamic_bbx,
},
],
win=name,
env="amf_stream",
)
def trigger(context):
if context["event_type"] != "PropertyUpdate":
return
if context["target"] != self.ctl.panel:
return
property_name = (context.get("pane_data").get("content")[
context.get("propertyId")].get("name"))
if property_name == "Bounding Box Threshold":
self.viz_config["bounding_box_threshold"] = int(
context.get("value"))
elif property_name == "History Variance":
self.amf.amf_history_variance = context.get("value")
elif property_name == "History Variance Threshold":
self.amf.amf_variance_threshold = int(context.get("value"))
elif property_name == "History Variance Sample Amount":
self.amf.amf_variance_sample_amount = int(context.get("value"))
elif property_name == "Large Background Movement":
self.amf.amf_drop_large_bg_motion = context.get("value")
elif property_name == "Dynamic Bounding Box":
self.amf.amf_dynamic_bbx = context.get("value")
self.ctl.panel = update("Control Panel")
self.ctl = VisdomControlPanel(self.viz, update, trigger,
"Control Panel")
def motion_detection(self, frame):
mask = self.amf.apply(frame.copy())
display_frame = frame.copy()
motion_bbxes = self.amf.detect_motion(
mask, self.viz_config.get("bounding_box_threshold", 200))
for bbx in motion_bbxes:
box = BoundingBox(*bbx)
self.amf.draw_detection_box(box, display_frame)
self.viz.image(
mask,
win="mask_window",
opts=dict(
width=320,
height=250,
),
env="amf_stream",
)
return display_frame
def predict_frame_scene(self, frame):
mask = self.amf.apply(frame)
mask_metadata = self.amf.calculate_mask_metadata(mask)
frame_scene = self.amf.ssc.predict(
mask_metadata.avg,
mask_metadata.std,
self.amf.frame_width,
self.amf.frame_height,
)
return frame_scene
def show_ssc_graph(self):
print("Show SSC Graph")
ssc_prediction = []
for frame in self.frame_list:
resized_frame = frame_resize(frame.copy())
frame_scene = self.predict_frame_scene(resized_frame)
ssc_prediction.append(frame_scene)
n = len(self.frame_list)
x = np.linspace(0, n - 1, num=n)
scene_y = np.array(ssc_prediction)
self.viz.line(
X=x,
Y=scene_y,
opts=dict(title="ssc prediction graph", showlegend=True),
env="amf_ssc",
win="ssc_prediction_graph",
)
def stream_video(self):
for frame in self.frame_list:
resized_frame = frame_resize(frame.copy())
display_frame = self.motion_detection(resized_frame)
disp_image = frame_convert(display_frame)
self.viz.image(
disp_image,
win="video_window",
opts=dict(
width=320,
height=250,
),
env="amf_stream",
)
time.sleep(1.0 / self.frame_fps)
def start(self):
print("Visdom Playground Activating")
self.viz.close(env="amf_stream")
self.init_control_panel()
while True:
self.stream_video()
},
{
'type': 'checkbox',
'name': 'Checkbox',
'value': True
},
{
'type': 'select',
'name': 'Select',
'value': 1,
'values': ['Red', 'Green', 'Blue']
},
]
# 新建属性窗口, 并返回窗口 id
properties_window_id = viz.properties(properties,
win='win03',
opts={'title': 'prop-demo'})
def properties_callback(event):
if event['event_type'] == 'PropertyUpdate': # 属性更新事件
prop_id = event[
'propertyId'] # 属性 id, 为定义窗口时传入的 properties 列表中相应属性的 idx
value = event['value'] # 新的属性值
if prop_id in [0, 1]: # 字符属性 和 数字属性 无需在本地字典中更新, 更新也不会影响显示
new_value = value + '_updated' # 可以什么也不干
new_value = value + '0'
elif prop_id == 2: # Button属性 名称可以在本地字典修改
new_value = 'Stop' if properties[prop_id][
'value'] == 'Start' else 'Start'
else: # 3 checkbox, 4 select属性, 需要本地修改, 并重新写入
new_value = value
elif len(event['key']) == 1:
curr_txt += event['key']
viz.text(curr_txt, win=callback_text_window)
viz.register_event_handler(type_callback, callback_text_window)
# Properties window
properties = [
{'type': 'text', 'name': 'Text input', 'value': 'initial'},
{'type': 'number', 'name': 'Number input', 'value': '12'},
{'type': 'button', 'name': 'Button', 'value': 'Start'},
{'type': 'checkbox', 'name': 'Checkbox', 'value': True},
{'type': 'select', 'name': 'Select', 'value': 1, 'values': ['Red', 'Green', 'Blue']},
]
properties_window = viz.properties(properties)
def properties_callback(event):
if event['event_type'] == 'PropertyUpdate':
prop_id = event['propertyId']
value = event['value']
if prop_id == 0:
new_value = value + '_updated'
elif prop_id == 1:
new_value = value + '0'
elif prop_id == 2:
new_value = 'Stop' if properties[prop_id]['value'] == 'Start' else 'Start'
else:
new_value = value
properties[prop_id]['value'] = new_value
viz.properties(properties, win=properties_window)
