DGP Multi-Cam + Velocity Loss + FP16 Inference + PackNetSlim (#30)

* Support for multi-camera loading on the DGP dataset
* Support for fp16 at inference time
* Velocity loss (see VelSupModel)
* PackNetSlim01 (faster version of PackNet)

configs/default_config.py

@@ -80,11 +80,11 @@
 ########################################################################################################################
 cfg.model.loss = CN()
 #
-cfg.model.loss.num_scales = 4               # Number of inverse depth scales to use
-cfg.model.loss.progressive_scaling = 0.0    # Training percentage to decay number of scales
-cfg.model.loss.flip_lr_prob = 0.5           # Probablity of horizontal flippping
-cfg.model.loss.rotation_mode = 'euler'      # Rotation mode
-cfg.model.loss.upsample_depth_maps = True   # Resize depth maps to highest resolution
+cfg.model.loss.num_scales = 4                   # Number of inverse depth scales to use
+cfg.model.loss.progressive_scaling = 0.0        # Training percentage to decay number of scales
+cfg.model.loss.flip_lr_prob = 0.5               # Probablity of horizontal flippping
+cfg.model.loss.rotation_mode = 'euler'          # Rotation mode
+cfg.model.loss.upsample_depth_maps = True       # Resize depth maps to highest resolution
 #
 cfg.model.loss.ssim_loss_weight = 0.85          # SSIM loss weight
 cfg.model.loss.occ_reg_weight = 0.1             # Occlusion regularizer loss weight
@@ -97,6 +97,8 @@
 cfg.model.loss.padding_mode = 'zeros'           # Photometric loss padding mode
 cfg.model.loss.automask_loss = True             # Automasking to remove static pixels
 #
+cfg.model.loss.velocity_loss_weight = 0.1       # Velocity supervision loss weight
+#
 cfg.model.loss.supervised_method = 'sparse-l1'  # Method for depth supervision
 cfg.model.loss.supervised_num_scales = 4        # Number of scales for supervised learning
 cfg.model.loss.supervised_loss_weight = 0.9     # Supervised loss weight
@@ -138,7 +140,7 @@
 cfg.datasets.train.path = []                        # Training data path
 cfg.datasets.train.split = []                       # Training split
 cfg.datasets.train.depth_type = ['']                # Training depth type
-cfg.datasets.train.cameras = []                     # Training cameras
+cfg.datasets.train.cameras = [[]]                   # Training cameras (double list, one for each dataset)
 cfg.datasets.train.repeat = [1]                     # Number of times training dataset is repeated per epoch
 cfg.datasets.train.num_logs = 5                     # Number of training images to log
 ########################################################################################################################
@@ -153,7 +155,7 @@
 cfg.datasets.validation.path = []                   # Validation data path
 cfg.datasets.validation.split = []                  # Validation split
 cfg.datasets.validation.depth_type = ['']           # Validation depth type
-cfg.datasets.validation.cameras = []                # Validation cameras
+cfg.datasets.validation.cameras = [[]]              # Validation cameras (double list, one for each dataset)
 cfg.datasets.validation.num_logs = 5                # Number of validation images to log
 ########################################################################################################################
 ### DATASETS.TEST
@@ -167,7 +169,7 @@
 cfg.datasets.test.path = []                         # Test data path
 cfg.datasets.test.split = []                        # Test split
 cfg.datasets.test.depth_type = ['']                 # Test depth type
-cfg.datasets.test.cameras = []                      # Test cameras
+cfg.datasets.test.cameras = [[]]                    # Test cameras (double list, one for each dataset)
 cfg.datasets.test.num_logs = 5                      # Number of test images to log
 ########################################################################################################################
 ### THESE SHOULD NOT BE CHANGED

configs/eval_ddad.yaml

@@ -18,7 +18,7 @@ datasets:
         path: ['/data/datasets/DDAD/ddad.json']
         split: ['val']
         depth_type: ['lidar']
-        cameras: ['camera_01']
+        cameras: [['camera_01']]
 save:
     folder: '/data/save'
     viz: True

configs/overfit_ddad.yaml

@@ -31,17 +31,17 @@ datasets:
         path: ['/data/datasets/DDAD_tiny/ddad_tiny.json']
         split: ['train']
         depth_type: ['lidar']
-        cameras: ['camera_01']
+        cameras: [['camera_01']]
         repeat: [500]
     validation:
         dataset: ['DGP']
         path: ['/data/datasets/DDAD_tiny/ddad_tiny.json']
         split: ['train']
         depth_type: ['lidar']
-        cameras: ['camera_01']
+        cameras: [['camera_01']]
     test:
         dataset: ['DGP']
         path: ['/data/datasets/DDAD_tiny/ddad_tiny.json']
         split: ['train']
         depth_type: ['lidar']
-        cameras: ['camera_01']
+        cameras: [['camera_01']]

configs/train_ddad.yaml

@@ -30,19 +30,19 @@ datasets:
         path: ['/data/datasets/DDAD/ddad.json']
         split: ['train']
         depth_type: ['lidar']
-        cameras: ['camera_01']
+        cameras: [['camera_01']]
         repeat: [5]
     validation:
         num_workers: 8
         dataset: ['DGP']
         path: ['/data/datasets/DDAD/ddad.json']
         split: ['val']
         depth_type: ['lidar']
-        cameras: ['camera_01']
+        cameras: [['camera_01']]
     test:
         num_workers: 8
         dataset: ['DGP']
         path: ['/data/datasets/DDAD/ddad.json']
         split: ['val']
         depth_type: ['lidar']
-        cameras: ['camera_01']
+        cameras: [['camera_01']]