def process_file(file_path):
df = pd.read_csv(file_path, index_col='TRIP_ID')
unique_id = uuid.uuid4().hex
_out_path = os.path.join(gpx_folder, unique_id)
if not os.path.isdir(_out_path):
os.mkdir(_out_path)
count = 1
with tqdm(total=len(df)) as pbar:
for trip_id, row in df.iterrows():
polyline = ast.literal_eval(row['POLYLINE'])
lon, lat = [i for i, j in polyline], [j for i, j in polyline]
_df = pd.DataFrame({'x': lon, 'y': lat})
out_path = os.path.join(_out_path, trip_id)
out_path = f'{out_path}.gpx'
if os.path.exists(out_path):
print(f'Duplicate trip ID found {trip_id}')
Converter.dataframe_to_gpx(_df,
lats_colname='y',
longs_colname='x',
output_file=out_path)
count += 1
if not count % 500:
pbar.update(500)
pbar.update(500)
print(f'Finished processing file {file_path}')
def convert(self):
"""
Extract GPS points from a route map picture with python/OpenCV and save it in a gpx file
"""
trace_mask = self.compute_trace_mask()
pixel_points = self.compute_trace_points(trace_mask)
if DEBUG:
cv2.imshow("trace_mask", trace_mask)
cv2.imshow("Points", self.img)
gps_coords = self.pixels_to_gps_coord(pixel_points)
np.savetxt("foo.csv",
np.asarray(gps_coords),
delimiter=",",
header="latitude,longitude",
comments='')
Converter(input_file='foo.csv').csv_to_gpx(lats_colname='latitude',
longs_colname='longitude',
output_file='foo.gpx')
if DEBUG:
cv2.waitKey(0)
def converter():
return Converter(input_file='examples/test_data/test1.gpx')
from gpx_converter import Converter # convert multiple csv files to gpx ( notice to use it as a static method ) Converter.convert_multi_csv_to_gpx(dirpath='test_data/')
from gpx_converter import Converter # convert gpx to a pandas dataframe res = Converter(input_file='test_data/test1.gpx').gpx_to_dataframe()
def gpx_read(file_path):
rundf = Converter(input_file=file_path).gpx_to_dataframe()
return rundf
from gpx_converter import Converter
# convert csv to gpx
Converter(input_file='test_data/test1.csv').csv_to_gpx(lats_colname='latitudes',
longs_colname='longitudes',
output_file='test_data/converted.gpx')
from gpx_converter import Converter # convert gpx to a csv file Converter(input_file='test_data/test1.gpx').gpx_to_csv(output_file='test_data/converted_to_csv.csv')
def test_gpx_to_dataframe():
result = Converter(
input_file='examples/test_data/test1.gpx').gpx_to_pandas_dataframe()
assert result is not None
from gpx_converter import Converter
# convert gpx to a csv file
# Converter(input_file='test_data/test1.gpx').gpx_to_csv(output_file='test_data/converted_to_csv.csv')
# convert gpx to a pandas dataframe
res = Converter(input_file='test_data/test1.gpx').gpx_to_pandas_dataframe()
# convert csv to gpx
Converter(input_file='test_data/test1.csv').csv_to_gpx(
lats_colname='latitudes',
longs_colname='longitudes',
output_file='test_data/converted.gpx')
# convert multiple csv files to gpx ( notice to use it as a static method )
Converter.convert_multi_csv_to_gpx(dirpath='test_data/')
from gpx_converter import Converter
# convert gpx to a pandas dataframe
res = Converter('test_data/test1.gpx').gpx_to_dictionary(
latitude_key='latitude', longitude_key='longitude')
print(res)
from gpx_converter import Converter
# convert gpx to a csv file
Converter(input_file='test_data/test_file.gpx').gpx_to_csv(
output_file='test_data/test_file.csv')