compatibility with pifpaf v0.12.1 (#7)

* update with new pifpaf version

* pylint

* pylint

monstereo/__init__.py

@@ -1,4 +1,4 @@
 
 """Open implementation of MonoLoco++ / MonStereo."""
 
-__version__ = '0.2.2'
+__version__ = '0.2.3'

monstereo/network/process.py

@@ -7,11 +7,11 @@ import numpy as np
 import torch
 import torchvision
 
+from ..utils import get_keypoints, pixel_to_camera, to_cartesian, back_correct_angles
+
 logging.basicConfig(level=logging.INFO)
 logger = logging.getLogger(__name__)
 
-from ..utils import get_keypoints, pixel_to_camera, to_cartesian, back_correct_angles
-
 BF = 0.54 * 721
 z_min = 4
 z_max = 60

monstereo/predict.py

@@ -16,7 +16,7 @@ import PIL
 import openpifpaf
 import openpifpaf.datasets as datasets
 from openpifpaf.predict import processor_factory, preprocess_factory
-from openpifpaf import decoder, network, visualizer, show
+from openpifpaf import decoder, network, visualizer, show, logger
 
 from .visuals.printer import Printer
 from .network import Loco
@@ -45,14 +45,15 @@ def factory_from_args(args):
                   "Using a ShuffleNet backbone")
             args.checkpoint = 'shufflenetv2k30'
 
+    logger.configure(args, LOG)  # logger first
+
     # Devices
     args.device = torch.device('cpu')
-    args.disable_cuda = False
     args.pin_memory = False
     if torch.cuda.is_available():
         args.device = torch.device('cuda')
         args.pin_memory = True
-    args.loader_workers = 8
+    LOG.debug('neural network device: %s', args.device)
 
     # Add visualization defaults
     args.figure_width = 10
@@ -69,7 +70,7 @@ def factory_from_args(args):
 
     # Configure
     decoder.configure(args)
-    network.configure(args)
+    network.Factory.configure(args)
     show.configure(args)
     visualizer.configure(args)
 
@@ -105,7 +106,7 @@ def predict(args):
         # unbatch (only for MonStereo)
         for idx, (pred, meta) in enumerate(zip(pred_batch, meta_batch)):
             print('batch %d: %s', batch_i, meta['file_name'])
-            pred = preprocess.annotations_inverse(pred, meta)
+            pred = [ann.inverse_transform(meta) for ann in pred]
 
             if args.output_directory is None:
                 splits = os.path.split(meta['file_name'])

monstereo/run.py

@@ -2,7 +2,7 @@
 
 import argparse
 
-from openpifpaf import decoder, network, visualizer, show
+from openpifpaf import decoder, network, visualizer, show, logger
 
 
 def cli():
@@ -39,15 +39,17 @@ def cli():
     predict_parser.add_argument('--dpi', help='image resolution',  type=int, default=150)
     predict_parser.add_argument('--long-edge', default=None, type=int,
                                 help='rescale the long side of the image (aspect ratio maintained)')
+    predict_parser.add_argument('--disable-cuda', action='store_true', help='disable CUDA')
     predict_parser.add_argument('--focal',
                                 help='focal length in mm for a sensor size of 7.2x5.4 mm. Default nuScenes sensor',
                                 type=float, default=5.7)
 
     # Pifpaf parsers
-    decoder.cli(predict_parser)
+    decoder.cli(parser)
-    network.cli(predict_parser)
+    logger.cli(parser)
-    show.cli(predict_parser)
+    network.Factory.cli(parser)
-    visualizer.cli(predict_parser)
+    show.cli(parser)
+    visualizer.cli(parser)
 
     # Monoloco
     predict_parser.add_argument('--net', help='Choose network: monoloco, monoloco_p, monoloco_pp, monstereo')

monstereo/visuals/printer.py

@@ -111,7 +111,7 @@ class Printer:
 
         #  Initialize multi figure, resizing it for aesthetic proportion
         if 'multi' in self.output_types:
-            assert 'bird' and 'front' not in self.output_types, \
+            assert 'bird' not in self.output_types and 'front' not in self.output_types, \
                 "multi figure cannot be print together with front or bird ones"
 
             self.y_scale = self.width / (self.height * 2)  # Defined proportion

setup.py

@@ -28,7 +28,7 @@ setup(
     zip_safe=False,
 
     install_requires=[
-        'openpifpaf==v0.12b1',
+        'openpifpaf==v0.12.1',
         'matplotlib'
     ],
     extras_require={