Multi-gpu training

[qinjian623]

Add a new file train_culane_mp.py which is single-node , multi-gpu training script.

The original train_culane.py was deleted while developing the new one, maybe we should restore it back.

Default batch_size is still 2, but it should be too small for multi-gpu training. 64 is acceptable on a 4-V100 node.

A new var metric_skips=10 is introduced. This could low the frequency of f1 metric which using CPU only.

Start training with:

CUDA_VISIBLE_DEVICES=4,5,6,7 python train_culane_mp.py ...

to control how many GPUs involved in training.

[qinjian623]

Sorry for forgetting mention this,
In the file ./datasets/culane.py line 115 to line 124,
those l[1:] or l[:] differences came from an unofficial version CULane dataset, we fix part of links in the list file.

So may need some minor changes to use official CULane.

                if self.image_set == 'test':
                    self.img_list.append(os.path.join(self.data_dir_path,
                                                      l[1:]))  # l[1:]  get rid of the first '/' so as for os.path.join
                else:
                    self.img_list.append(os.path.join(self.data_dir_path, l))

                if self.image_set == 'test':
                    self.seg_list.append(os.path.join(self.data_dir_path, 'laneseg_label_w16_test', l[1:-3] + 'png'))
                else:
                    self.seg_list.append(os.path.join(self.data_dir_path, 'laneseg_label_w16', l[:-3] + 'png'))