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_laneNum(edges, db_name=None):
df_pid_2_edge = pids_filter(
sort_pids_in_edge(EDGE_TO_PID, df_pred_memo, plot=False)
)
# df_pid_2_edge.query("eid==53560")
df_lane_nums = pd.DataFrame(
df_pid_2_edge[~df_pid_2_edge.outlier]\
.groupby('eid')['lane_num']\
.apply(list)\
.apply(_get_lst_mode)
)
# filter the unpredicted edge
idxs = list(np.setdiff1d( edges.index, df_lane_nums.index))
edges.loc[idxs]
df_pid_2_edge.query("eid in @idxs")
# map_visualize(edges.loc[idxs])
edges_ = edges.merge(df_lane_nums, on='eid', how='left')
edges_.index = edges_.eid
edge_miss = edges_[edges_.lane_num.isna()]
# case 0: normal links
idxs = edge_miss[edge_miss.edge_type == 0].index
# if len(idxs) > 0:
# edges_.loc[idxs, 'lane_num'] = _indentify_lane_num_for_type_0(edge_miss, edges_, df_pid_2_edge )
# case 3: signal controled edge
idxs = edge_miss[edge_miss.edge_type == 0].index
if len(idxs) > 0:
edges_.loc[idxs, 'lane_num'] = _indentify_lane_num_for_type_3(edges_, idxs, df_pid_2_edge, net=net)
if db_name is not None:
gdf_to_postgis(edges_, db_name)
return df_lane_nums, edges_
def upload_pano_link(self):
return gdf_to_postgis(self.gdf_pano_link, 'pano_link')
def save_db():
tmp = eoi.query('lane_num==lane_num')
tmp.loc[:, 'lane_num'] = tmp.lane_num.astype(np.int)
gdf_to_postgis(tmp, 'test_matching')
def upload(self, db_name='test_matching'):
tmp = net.df_edges.merge(self.df_lane, on='eid')
tmp.loc[:, 'lane_num'] = tmp.loc[:, 'lane_num'].astype(np.int)
gdf_to_postgis(tmp, db_name)
return True
df.query(expr, engine='python').fillna(-1).plot(column='lane_num',
legend=True,
categorical=True)
return df
df = process_link(df)
df.lane_num.isna().sum()
df[df.lane_num.isna()].edge_type.value_counts()
df.query("lane_num!=lane_num and edge_type ==0 ").plot()
df.drop(columns='geom_origin', inplace=True)
gdf_to_postgis(df, 'test_matching_all')
gdf_to_geojson(df, 'road_demo')
#%%
idxs = list(np.setdiff1d(df.index, self.df_lane.index))
map_visualize(df.loc[idxs], scale=.1)
df_miss = df.loc[idxs].sort_values(['road_level', 'name', 'eid', 'edge_type'])
df_miss_link = df_miss.query("road_type.str.contains('link')", engine='python')
# map_visualize(df_miss_link, scale=.1)
# atts = [ 'rid', 'name', 's', 'e', 'order', 'road_type', 'dir', 'lanes', 'dist', 'edge_type', 'road_level']
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