'cache': tiles.cache,
'starting_locations': starting_locations,
'gc': tiles.gcs[tile.region],
'edge_counts': {},
})
print('extracted {} subtiles from {} tiles (missing {})'.format(
len(subtiles), len(tiles.train_tiles),
4 * len(tiles.train_tiles) - len(subtiles)))
# initialize paths, one per subtile
print('loading initial paths')
paths = []
for i, subtile in enumerate(subtiles):
start_loc = random.choice(subtile['starting_locations'])
paths.append(model_utils.Path(subtile['gc'], subtile, start_loc=start_loc))
num_sets = (len(paths) + PARALLEL_PATHS - 1) // PARALLEL_PATHS
best_accuracy = None
angle_losses = []
detect_losses = []
action_losses = []
losses = []
def vector_to_action(angle_outputs, stop_outputs):
x = numpy.zeros((64, ), dtype='float32')
if stop_outputs[0] > THRESHOLD:
x[numpy.argmax(angle_outputs)] = 1
return x
r = geom.Rectangle(geom.Point(x * 4096, y * 4096),
geom.Point((x + 1) * 4096, (y + 1) * 4096))
g = graph.read_graph(EXISTING_GRAPH_FNAME)
gc = graph.GraphContainer(g)
g = g.clone()
graph.densify(g, SEGMENT_LENGTH)
tile_data = {
'region': REGION,
'rect': r,
'search_rect': r.add_tol(-WINDOW_SIZE // 2),
'cache': tiles.cache,
'starting_locations': [],
}
#path = model_utils.Path(gc, tile_data, g=g)
path = model_utils.Path(None, tile_data, g=g)
for vertex in g.vertices:
vertex.edge_pos = None
path.prepend_search_vertex(vertex)
big_ims = tile_data['cache'].get(tile_data['region'],
tile_data['rect'])
m6_old = tf_util.apply_conv(session,
m,
big_ims['input'],
scale=4,
channels=64)
m6_new = tf_util.apply_conv(session,
m,
big_ims['input1'],
scale=4,
pos2_pos = match_point(pos2_point)
else:
next_positions = graph.follow_graph(pos1_pos, SEGMENT_LENGTH)
pos2_point = next_positions[0].point()
pos2_pos = next_positions[0]
start_loc = [{
'point': pos1_point,
'edge_pos': pos1_pos,
}, {
'point': pos2_point,
'edge_pos': pos2_pos,
}]
path = model_utils.Path(tile_data['gc'],
tile_data,
start_loc=start_loc)
else:
g = graph.read_graph(EXISTING_GRAPH_FNAME)
graph.densify(g, SEGMENT_LENGTH)
r = g.bounds()
tile_data = {
'region': REGION,
'rect': r.add_tol(WINDOW_SIZE / 2),
'search_rect': r,
'cache': tiles.cache,
'starting_locations': [],
}
path = model_utils.Path(tiles.get_gc(REGION), tile_data, g=g)
skip_vertices = set()
pos2_point = MANUAL_POINT2.add(MANUAL_RELATIVE)
pos2_pos = match_point(pos2_point)
else:
next_positions = graph.follow_graph(pos1_pos, SEGMENT_LENGTH)
pos2_point = next_positions[0].point()
pos2_pos = next_positions[0]
start_loc = [{
'point': pos1_point,
'edge_pos': pos1_pos,
}, {
'point': pos2_point,
'edge_pos': pos2_pos,
}]
path = model_utils.Path(tile_data['gc'], tile_data, start_loc=start_loc)
else:
g = graph.read_graph(EXISTING_GRAPH_FNAME)
r = g.bounds()
tile_data = {
'region': REGION,
'rect': r.add_tol(WINDOW_SIZE/2),
'search_rect': r,
'cache': cache,
'starting_locations': [],
}
path = model_utils.Path(None, tile_data, g=g)
for vertex in g.vertices:
path.prepend_search_vertex(vertex)
compute_targets = SAVE_EXAMPLES or FOLLOW_TARGETS
g = graph.read_graph(EXISTING_GRAPH_FNAME)
if not USE_GRAPH_RECT:
rect = geom.Rectangle(TILE_START, TILE_END)
g = g.edgeIndex().subgraph(rect)
r = rect.add_tol(-WINDOW_SIZE / 2)
else:
r = g.bounds().add_tol(-WINDOW_SIZE / 2)
graph.densify(g, SEGMENT_LENGTH)
tile_data = {
'region': REGION,
'rect': r.add_tol(WINDOW_SIZE / 2),
'search_rect': r,
'cache': tiles.cache,
'starting_locations': [],
}
path = model_utils.Path(tiles.get_gc(REGION), tile_data, g=g)
skip_vertices = set()
if FILTER_BY_TAG:
with open(FILTER_BY_TAG, 'r') as f:
edge_tags = {int(k): v for k, v in json.load(f).items()}
for edge in g.edges:
tags = edge_tags[edge.orig_id()]
if 'highway' not in tags or tags['highway'] in [
'pedestrian', 'footway', 'path', 'cycleway', 'construction'
]:
for vertex in [edge.src, edge.dst]:
skip_vertices.add(vertex)
for vertex in g.vertices:
vertex.edge_pos = None
if vertex not in skip_vertices: