logging.info('- found pose_id: %d' % self.pose_id)
else:
self.pose_id = 0
logging.info('- take default pose_id = 0')
def __getitem__(self, key):
return self.info[key]
def __contains__(self, key):
return True if key in self.info else False
def build_camera(self):
return Camera(camera_dir=self.camera_dir, pose_id=self.pose_id)
if __name__ == "__main__":
setupLogging('log/augmentation/Video.log', logging.DEBUG, 'w')
video = Video(video_dir='augmentation/scenes/cam578/Mar15-10h')
camera = video.build_camera()
#video_file = 'augmentation/scenes/cam578/Mar15-10h/Mar15-10h.json'
#video_info = json.load(open(atcity(video_file)))
#video_info['video_dir'] = 'augmentation/scenes/cam578/Mar15-10h'
#video.load(video_info=video_info)
#assert video.example_background is not None
#cv2.imshow('test', video.example_background)
#cv2.waitKey(-1)
bpy.data.objects[car_name].hide_render = True
bpy.data.objects[car_name0].hide_render = False
# render scene
bpy.ops.render.render(write_still=True, layer='Depth')
_rename(render_dir, 'depth0001', 'depth-%03d.png' % car_i0)
if params['save_blender_files']:
bpy.ops.wm.save_as_mainfile(
filepath=atcity(op.join(render_dir, 'render.blend')))
# logging.info ('objects in the end of frame: %d' % len(bpy.data.objects))
logging.info('make_snapshot: successfully finished a frame')
setupLogging('log/augmentation/renderScene.log', logging.INFO, 'a')
traffic_path = op.join(WORK_DIR, TRAFFIC_FILENAME)
logging.info('traffic_path: %s' % traffic_path)
frame_info = json.load(open(traffic_path))
setParamUnlessThere(frame_info, 'render_cars_as_cubes', False)
# place all cars
car_names = []
for i, vehicle in enumerate(frame_info['vehicles']):
if frame_info['render_cars_as_cubes']:
location = (vehicle['x'], vehicle['y'], 0.1)
bpy.ops.mesh.primitive_cube_add(location=location, radius=0.3)
else:
collection_id = vehicle['collection_id']
model_id = vehicle['model_id']
job['no_annotations'] = args.no_annotations
job['traffic_file'] = args.traffic_file
job['video_dir'] = args.video_info_dir
setParamUnlessThere(job, 'out_video_dir', op.dirname(args.traffic_file))
return job
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument('--save_blender_files', action='store_true')
parser.add_argument('--logging_level', default=20, type=int)
parser.add_argument('--timeout',
type=int,
help='maximum running time, in munutes')
parser.add_argument(
'--no_annotations',
action='store_true',
help='will speed up rendering since individual cars wont be rendered')
parser.add_argument('--frame_range',
default='[::]',
help='python style ranges, e.g. "[5::2]"')
parser.add_argument('--video_info_dir', required=True)
parser.add_argument('--traffic_file', required=True)
args = parser.parse_args()
setupLogging('log/augmentation/ProcessVideo.log', args.logging_level, 'w')
job = make_job(args)
process_video(job)
parser.add_argument('--logging_level', default=20, type=int)
parser.add_argument('--frame_range',
default='[::]',
help='python style ranges, e.g. "[5::2]"')
parser.add_argument('--in_db_file', required=True)
parser.add_argument('--video_dir', required=True)
parser.add_argument('--traffic_file',
required=True,
help='output .json file where to write traffic info. '
'Can be "traffic.json" in video output dir.')
group = parser.add_mutually_exclusive_group(required=True)
group.add_argument('--speed_kph', type=int)
group.add_argument('--num_cars', type=int)
args = parser.parse_args()
setupLogging('log/augmentation/GenerateTraffic.log', args.logging_level,
'w')
if not op.exists(atcity(op.dirname(args.traffic_file))):
os.makedirs(atcity(op.dirname(args.traffic_file)))
job = {
'frame_range': args.frame_range,
'in_db_file': args.in_db_file,
'video_dir': args.video_dir,
'out_video_dir': op.dirname(args.in_db_file)
}
if args.speed_kph is not None:
setParamUnlessThere(job, 'speed_kph', args.speed_kph)
elif args.num_cars is not None:
setParamUnlessThere(job, 'num_cars', args.num_cars)
else:
''' generate lanes map with cars as icons for visualization '''
# make azimuth_map a 2D array
img = self.azimuth_map.copy()
#alpha, azimuth_map = azimuth_map[:,:,-1], azimuth_map[:,:,0]
# put cars on top
for v in self.vehicles:
cv2.circle(img, (v['x'], v['y']), 5, (128, 128, 128), -1)
return img
if __name__ == "__main__":
setupLogging('log/augmentation/traffic.log', logging.DEBUG, 'w')
video_dir = 'augmentation/scenes/cam166/Feb23-09h'
collection_names = [
'7c7c2b02ad5108fe5f9082491d52810',
'uecadcbca-a400-428d-9240-a331ac5014f6'
]
timestamp = datetime.now()
video = Video(video_dir)
camera = video.build_camera()
cad = Cad(collection_names)
#model = TrafficModel (camera, video, cad=cad, speed_kph=10, burn_in=True)
model = TrafficModelRandom(camera, video, cad, num_cars_mean=10)
import os, sys
sys.path.insert(0, os.path.join(os.getenv('CITY_PATH'), 'src'))
import logging
from learning.video2images import video2images
from learning.helperSetup import setupLogging, atcity
setupLogging('log/learning/Video2Images.log', logging.INFO, 'a')
video2images('data/camdata/cam166/Feb14-08h/src.avi', 'data/labelme/try')