def create_output_opencv(input_map, coords, output_file, full_map=False):
if full_map:
output_slice = slice(None)
else:
output_slice = create_slice(
*find_path_bounds(input_map.shape[0], coords))
cv2.imwrite(output_file, input_map[output_slice])
def _get_scaled_context(self):
# Context defines the area that the template matching will be limited to.
# This area gets larger each time a match is missed to account for movement processing.
context_slice = slice(None)
if self.last_known_position:
max_reachable_dist = self._calculate_max_travel_distance()
context_coords, context_size = find_path_bounds(
self.gray_map.shape[0],
[scale_coords(self.last_known_position, self.scale)],
crop_border=0,
min_size=max_reachable_dist)
context_slice = create_slice(context_coords, context_size)
return context_slice
def run(self):
self.percent_max_update.emit(0)
self.percent_update.emit(0)
match = PUBGISMatch(self.minimap_iterator)
self.minimap_update.emit(self.preview_map)
for percent, timestamp, full_position in match.process_match():
if percent is not None:
self.percent_max_update.emit(100)
self.percent_update.emit(percent)
plot_coordinate_line(self.preview_map, self.full_positions,
full_position, self.parent.path_color(),
self.parent.thickness_spinbox.value())
self.full_positions.append(full_position)
self.timestamps.append(timestamp)
if self.output_flags & OutputFlags.LIVE_PREVIEW:
preview_coords, preview_size = find_path_bounds(
PUBGISMatch.full_map.shape[0], self.full_positions)
preview_slice = create_slice(preview_coords, preview_size)
alpha = self.parent.path_color.alpha
blended = cv2.addWeighted(self.base_map_alpha[preview_slice],
1 - alpha,
self.preview_map[preview_slice],
alpha, 0)
self.minimap_update.emit(blended)
if self.isInterruptionRequested():
self.minimap_iterator.stop()
if self.isInterruptionRequested():
self.percent_max_update.emit(100)
self.percent_update.emit(100)
alpha = self.parent.path_color.alpha
if self.output_flags & OutputFlags.FULL_MAP:
blended = cv2.addWeighted(self.base_map_alpha, 1 - alpha,
self.preview_map, alpha, 0)
create_output_opencv(blended,
self.full_positions,
self.output_file,
full_map=True)
elif self.output_flags & OutputFlags.CROPPED_MAP:
blended = cv2.addWeighted(self.base_map_alpha, 1 - alpha,
self.preview_map, alpha, 0)
create_output_opencv(blended, self.full_positions,
self.output_file)
if self.output_flags & OutputFlags.JSON:
pre, _ = os.path.splitext(self.output_file)
json_file = pre + ".json"
data = create_json_data(self.full_positions, self.timestamps)
output_json(json_file, data)
def test_find_path_bounds(map_size, input_coords, expected_bounds):
assert find_path_bounds(map_size, input_coords) == expected_bounds