def get_osm_node(self):
self.osm_edge = load_postgis(self.osm_edge_pg,
geom_wkt=self.geofence.to_wkt())
helper = lambda x: self.link_type_no_dict[
x] if x in self.link_type_no_dict else 99
self.osm_edge.loc[:,
"road_level"] = self.osm_edge.road_type.apply(helper)
node_lst = np.unique(
self.osm_edge.query('road_level < 6')[[
's', 'e'
]].values.flatten()).tolist()
self.osm_node = load_postgis(
self.osm_node_pg,
geom_wkt=self.geofence.to_wkt()).query('nid in @node_lst')
return self.osm_node
def upload_pano_node(self, gdf: gpd.GeoDataFrame = None):
# 经过测试，上传的 list 数据会自动序列化
gdf = gdf if gdf is not None else self.gdf_pano_node
gdf.loc[:, "ID"] = gdf.index
db_pano_base = load_postgis(self.pano_node_pg)
ori_size, new_size = db_pano_base.shape[0], gdf.shape[0]
tmp = gdf.append(db_pano_base).drop_duplicates("ID", keep='first')
if ori_size == tmp.shape[0]:
return True
return gdf_to_postgis(tmp, self.pano_node_pg)
def get_unvisited_point(panos, bbox=None, geom_wkt=None, buffer_dis=15, plot=True):
osm_nodes = load_postgis('topo_osm_shenzhen_node', bbox=bbox, geom_wkt=geom_wkt)
if panos is None or panos.shape[0]==0:
return [ (i[0], i[1]) for i in osm_nodes[['x','y']].values.tolist()]
osm_nodes.loc[:, 'area'] = osm_nodes.to_crs(epsg=900913).buffer(buffer_dis).to_crs(epsg=4326)
osm_nodes.reset_index(inplace=True)
osm_nodes.set_geometry('area', inplace=True)
visited = gpd.sjoin(left_df=osm_nodes, right_df=panos, op='contains')['index'].unique().tolist()
res = osm_nodes.query( f"index not in {visited} " )
if plot:
map_visualize(res)
return [ (i[0], i[1]) for i in res[['x','y']].values.tolist()]
def load_pano_node(self):
print('loading pano data:')
gdf = load_postgis(self.pano_node_pg, geom_wkt=self.geofence.to_wkt())
lst_atts = ['MoveDir']
for att in lst_atts:
gdf.loc[:, att] = gdf[att].astype(np.float)
lst_atts = [
'ImgLayer',
'Links',
'SwitchID',
'TimeLine',
'Roads',
]
for att in tqdm(lst_atts, "Transfer"):
gdf.loc[:, att] = gdf[att].apply(eval)
gdf.index = gdf.ID
return gdf.to_dict('index')
def delete_history_error_dir_panos(download_new_pano=True, update=False):
"""
Deleted photos with incorrect azimuth due to historical reasons
"""
df_panos = load_postgis('panos')
df_panos.set_index('PID', inplace=True)
df_key_panos = load_postgis('pano_base')
df_key_panos.set_index('ID', inplace=True)
df_panos.loc[:, 'DIR_bak'] = df_panos.DIR
df_panos = update_move_dir(df_panos, df_key_panos)
rm_lst = df_panos.query("DIR != -1 and DIR != DIR_bak ").reset_index()[[
'PID', 'DIR_bak'
]].values.tolist()
remove_count = 0
for pid, heading in tqdm(rm_lst):
try:
os.remove(os.path.join(PANO_FOLFER, f"{pid}_{heading}.jpg"))
remove_count += 1
except:
continue
print(f"Delete {remove_count} pano imgs")
if download_new_pano:
pano_imgs_exist = load_exist_pano_imgs()
df_panos = df_panos.drop(
columns=['DIR_bak', 'url']).reset_index().drop_duplicates(
['PID', 'DIR'])
pano_lst = df_panos[['PID', 'DIR']].rename(columns={
'PID': 'pid',
'DIR': 'heading'
})
pano_lst = pano_lst.merge(pano_imgs_exist,
left_on=['pid', 'heading'],
right_on=['pid', 'dir'],
how='left')
pano_lst = pano_lst[pano_lst.fn.isna()][['pid',
'heading']].to_dict('records')
fetch_pano_img_parallel(pano_lst)
if update:
df_panos = df_panos.set_index('PID')
df_panos.loc[:, 'PID'] = df_panos.index
df_panos.loc[:, 'url'] = df_panos.apply(
lambda x: f"http://192.168.135.15:9000/panos/{x.PID}_{x.DIR}.jpg",
axis=1)
attrs_order = [
'PID', 'DIR', 'RID', 'Order', 'Type', 'X', 'Y', 'geometry', 'url',
'lane_num'
]
gdf_to_postgis(df_panos[attrs_order], 'panos')
return