Merge pull request #958 from FlyingQianMM/develop_qh

fix cannot import pdx.utils.logging when using python==3.6

dygraph/paddlex/cv/transforms/__init__.py

@@ -14,7 +14,7 @@
 
 from .operators import *
 from .batch_operators import BatchRandomResize, BatchRandomResizeByShort, _BatchPadding
-import paddlex.cv.transforms as T
+from paddlex.cv import transforms as T
 
 
 def arrange_transforms(model_type, transforms, mode='train'):

dygraph/paddlex/paddleseg/datasets/ade.py

@@ -22,7 +22,7 @@ from paddlex.paddleseg.utils.download import download_file_and_uncompress
 from paddlex.paddleseg.utils import seg_env
 from paddlex.paddleseg.cvlibs import manager
 from paddlex.paddleseg.transforms import Compose
-import paddlex.paddleseg.transforms.functional as F
+from paddlex.paddleseg.transforms import functional as F
 
 URL = "http://data.csail.mit.edu/places/ADEchallenge/ADEChallengeData2016.zip"
 
@@ -40,7 +40,8 @@ class ADE20K(Dataset):
     """
     NUM_CLASSES = 150
 
-    def __init__(self, transforms, dataset_root=None, mode='train', edge=False):
+    def __init__(self, transforms, dataset_root=None, mode='train',
+                 edge=False):
         self.dataset_root = dataset_root
         self.transforms = Compose(transforms)
         mode = mode.lower()

dygraph/paddlex/paddleseg/datasets/dataset.py

@@ -20,7 +20,7 @@ from PIL import Image
 
 from paddlex.paddleseg.cvlibs import manager
 from paddlex.paddleseg.transforms import Compose
-import paddlex.paddleseg.transforms.functional as F
+from paddlex.paddleseg.transforms import functional as F
 
 
 @manager.DATASETS.add_component
@@ -100,8 +100,8 @@ class Dataset(paddle.io.Dataset):
                     'When `mode` is "train", `train_path` is necessary, but it is None.'
                 )
             elif not os.path.exists(train_path):
-                raise FileNotFoundError(
-                    '`train_path` is not found: {}'.format(train_path))
+                raise FileNotFoundError('`train_path` is not found: {}'.format(
+                    train_path))
             else:
                 file_path = train_path
         elif mode == 'val':
@@ -110,8 +110,8 @@ class Dataset(paddle.io.Dataset):
                     'When `mode` is "val", `val_path` is necessary, but it is None.'
                 )
             elif not os.path.exists(val_path):
-                raise FileNotFoundError(
-                    '`val_path` is not found: {}'.format(val_path))
+                raise FileNotFoundError('`val_path` is not found: {}'.format(
+                    val_path))
             else:
                 file_path = val_path
         else:
@@ -120,8 +120,8 @@ class Dataset(paddle.io.Dataset):
                     'When `mode` is "test", `test_path` is necessary, but it is None.'
                 )
             elif not os.path.exists(test_path):
-                raise FileNotFoundError(
-                    '`test_path` is not found: {}'.format(test_path))
+                raise FileNotFoundError('`test_path` is not found: {}'.format(
+                    test_path))
             else:
                 file_path = test_path
 

dygraph/paddlex/ppdet/engine/tracker.py

@@ -29,7 +29,7 @@ from paddlex.ppdet.modeling.mot.utils import Timer, load_det_results
 from paddlex.ppdet.modeling.mot import visualization as mot_vis
 
 from paddlex.ppdet.metrics import Metric, MOTMetric
-import paddlex.ppdet.utils.stats as stats
+from paddlex.ppdet.utils import stats
 
 from .callbacks import Callback, ComposeCallback
 from .export_utils import _dump_infer_config
@@ -242,8 +242,9 @@ class Tracker(object):
         n_frame = 0
         timer_avgs, timer_calls = [], []
         for seq in seqs:
-            save_dir = os.path.join(output_dir, 'mot_outputs',
-                                    seq) if save_images or save_videos else None
+            save_dir = os.path.join(
+                output_dir, 'mot_outputs',
+                seq) if save_images or save_videos else None
             logger.info('start seq: {}'.format(seq))
 
             infer_dir = os.path.join(data_root, seq, 'img1')
@@ -253,7 +254,8 @@ class Tracker(object):
             dataloader = create('EvalMOTReader')(self.dataset, 0)
 
             result_filename = os.path.join(result_root, '{}.txt'.format(seq))
-            meta_info = open(os.path.join(data_root, seq, 'seqinfo.ini')).read()
+            meta_info = open(os.path.join(data_root, seq, 'seqinfo.ini')).read(
+            )
             frame_rate = int(meta_info[meta_info.find('frameRate') + 10:
                                        meta_info.find('\nseqLength')])
 

dygraph/paddlex/ppdet/engine/trainer.py

@@ -36,7 +36,7 @@ from paddlex.ppdet.utils.visualizer import visualize_results, save_result
 from paddlex.ppdet.metrics import JDEDetMetric, JDEReIDMetric
 from paddlex.ppdet.metrics import Metric, COCOMetric, VOCMetric, WiderFaceMetric, get_infer_results, KeyPointTopDownCOCOEval
 from paddlex.ppdet.data.source.category import get_categories
-import paddlex.ppdet.utils.stats as stats
+from paddlex.ppdet.utils import stats
 
 from .callbacks import Callback, ComposeCallback, LogPrinter, Checkpointer, WiferFaceEval, VisualDLWriter
 from .export_utils import _dump_infer_config
@@ -95,8 +95,8 @@ class Trainer(object):
         if self.mode == 'train':
             steps_per_epoch = len(self.loader)
             self.lr = create('LearningRate')(steps_per_epoch)
-            self.optimizer = create('OptimizerBuilder')(self.lr,
-                                                        self.model.parameters())
+            self.optimizer = create('OptimizerBuilder')(
+                self.lr, self.model.parameters())
 
         self._nranks = dist.get_world_size()
         self._local_rank = dist.get_rank()
@@ -401,7 +401,7 @@ class Trainer(object):
         clsid2catid, catid2name = get_categories(
             self.cfg.metric, anno_file=anno_file)
 
-        # Run Infer 
+        # Run Infer
         self.status['mode'] = 'test'
         self.model.eval()
         for step_id, data in enumerate(loader):
@@ -485,8 +485,8 @@ class Trainer(object):
 
         # Save infer cfg
         _dump_infer_config(self.cfg,
-                           os.path.join(save_dir, 'infer_cfg.yml'), image_shape,
-                           self.model)
+                           os.path.join(save_dir, 'infer_cfg.yml'),
+                           image_shape, self.model)
 
         input_spec = [{
             "image": InputSpec(

dygraph/paddlex/utils/checkpoint.py

@@ -17,7 +17,7 @@ import os.path as osp
 import glob
 import paddle
 import paddlex
-import paddlex.utils.logging as logging
+from paddlex.utils import logging
 from .download import download_and_decompress
 
 seg_pretrain_weights_dict = {

dygraph/requirements.txt

@@ -1,5 +1,5 @@
 tqdm
-scipy
+scipy==1.5.4
 colorama
 cython
 pycocotools
@@ -7,8 +7,8 @@ visualdl >= 2.1.1
 paddleslim == 2.1.0
 shapely
 paddlepaddle-gpu==2.1.1
-numpy >= 1.20
 opencv-python
 scikit-learn==0.23.2
 lap
 motmetrics
+matplotlib==3.3.4

dygraph/setup.py

@@ -31,7 +31,8 @@ setuptools.setup(
     install_requires=[
         "pycocotools;platform_system!='Windows'", 'pyyaml', 'colorama', 'tqdm',
         'paddleslim==2.1.0', 'visualdl>=2.1.1', 'shapely>=1.7.0',
-        'opencv-python', 'scipy', 'lap', 'motmetrics', 'scikit-learn==0.23.2'
+        'opencv-python', 'scipy==1.5.4', 'lap', 'motmetrics',
+        'scikit-learn==0.23.2', 'matplotlib==3.3.4'
     ],
     classifiers=[
         "Programming Language :: Python :: 3",