'pretrain_net': args.pretrain_net,
'freeze_pretrain_cnn': args.freeze_pretrain_cnn,
'squash_ctrl_params': args.squash_ctrl_params,
'clip_gradient': args.clip_gradient,
'fixed_order': args.fixed_order,
'ctrl_rnn_inp_struct': "attn",
'num_ctrl_rnn_iter': args.num_ctrl_rnn_iter,
'num_glimpse_mlp_layers': args.num_glimpse_mlp_layers,
'fixed_var': args.fixed_var,
'use_iou_box': args.use_iou_box,
'dynamic_var': args.dynamic_var,
'add_d_out': args.add_d_out,
'add_y_out': args.add_y_out,
'rnd_hflip': rnd_hflip,
'rnd_vflip': rnd_vflip,
'rnd_transpose': rnd_transpose,
'rnd_colour': rnd_colour,
'num_semantic_classes': args.num_semantic_classes
}
return model_opt
if __name__ == '__main__':
parsers = {
'default': TrainArgsParser(),
'data': DataArgsParser(),
'model': BoxModelArgsParser()
}
BoxExperiment.create_from_main('box_model',
parsers=parsers,
description='training').run()
for ii in range(y_out.shape[0]):
idx = inp['idx_map'][ii]
group = h5f[self.dataset.get_str_id(idx)]
if 'instance_pred' in group:
del group['instance_pred']
for ins in range(y_out.shape[1]):
y_out_arr = y_out[ii, ins]
y_out_arr = (y_out_arr * 255).astype('uint8')
y_out_str = cv2.imencode('.png', y_out_arr)[1]
group['instance_pred/{:02d}'.format(ins)] = y_out_str
if 'score_pred' in group:
del group['score_pred']
group['score_pred'] = s_out[ii]
class PackExperiment(EvalExperimentBase):
def get_runner(self, split):
return PackRunner(self.sess, self.model, self.dataset[split], self.opt,
self.model_opt)
def get_model(self):
self.model_opt['use_knob'] = False
return get_model(self.model_opt)
if __name__ == '__main__':
parsers = {'default': EvalArgsParser(), 'data': DataArgsParser()}
PackExperiment.create_from_main(
'ris_pack', parsers=parsers, description='Pack ris output').run()
def main():
parsers = {'default': EvalArgsParser(), 'data': DataArgsParser()}
FGPackExperiment.create_from_main('fg_pack',
parsers=parsers,
description='Pack fg output').run()
def main():
parsers = {'default': MyEvalArgsParser(), 'data': DataArgsParser()}
EvalExperiment.create_from_main('eval',
parsers=parsers,
description='Evaluate output').run()
def main():
parsers = {'default': FGEvalArgsParser(), 'data': DataArgsParser()}
FGEvalExperiment.create_from_main('fg_eval',
parsers=parsers,
description='Eval fg output').run()
def main():
parsers = {'default': CityscapesEvalArgsParser(), 'data': DataArgsParser()}
CityscapesEvalExperiment.create_from_main(
'ris_pp_eval', parsers=parsers,
description='Eval ris pp output').run()