Lint and format

xvjiarui · Jun 29, 2020 · 4f24fa1 · 4f24fa1
1 parent 3e59739
commit 4f24fa1
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Showing 3 changed files with 233 additions and 165 deletions.
diff --git a/configs/yolo/yolov3_ms_aug_273e.py b/configs/yolo/yolov3_ms_aug_273e.py
@@ -8,17 +8,12 @@
         type='Darknet',
         depth=53,
         out_indices=(3, 4, 5),
-        ),
-    neck=dict(
-        type='YoloNeck',),
-    bbox_head=dict(
-        type='YoloHead',))
+    ),
+    neck=dict(type='YoloNeck', ),
+    bbox_head=dict(type='YoloHead', ))
 # training and testing settings
 train_cfg = dict(
-    one_hot_smoother=0.,
-    ignore_config=0.5,
-    xy_use_logit=False,
-    debug=False)
+    one_hot_smoother=0., ignore_config=0.5, xy_use_logit=False, debug=False)
 test_cfg = dict(
     nms_pre=1000,
     min_bbox_size=0,
@@ -29,22 +24,21 @@
 # dataset settings
 dataset_type = 'CocoDataset'
 data_root = 'data/coco/'
-img_norm_cfg = dict(
-    mean=[0, 0, 0], std=[255., 255., 255.], to_rgb=True)
+img_norm_cfg = dict(mean=[0, 0, 0], std=[255., 255., 255.], to_rgb=True)
 # TODO: Add PhotoMetricDistortion
 train_pipeline = [
     dict(type='LoadImageFromFile', to_float32=True),
     dict(type='LoadAnnotations', with_bbox=True),
     dict(type='PhotoMetricDistortion'),
-    dict(type='Expand',
-         mean=img_norm_cfg['mean'],
-         to_rgb=img_norm_cfg['to_rgb'],
-         ratio_range=(1, 2)
-         ),
-    dict(type='MinIoURandomCrop',
-         min_ious=(0.4, 0.5, 0.6, 0.7, 0.8, 0.9),
-         min_crop_size=0.3
-         ),
+    dict(
+        type='Expand',
+        mean=img_norm_cfg['mean'],
+        to_rgb=img_norm_cfg['to_rgb'],
+        ratio_range=(1, 2)),
+    dict(
+        type='MinIoURandomCrop',
+        min_ious=(0.4, 0.5, 0.6, 0.7, 0.8, 0.9),
+        min_crop_size=0.3),
     dict(type='Resize', img_scale=[(320, 320), (608, 608)], keep_ratio=True),
     dict(type='RandomFlip', flip_ratio=0.5),
     dict(type='Normalize', **img_norm_cfg),
@@ -87,10 +81,9 @@
         ann_file=data_root + 'annotations/instances_val2017.json',
         img_prefix=data_root + 'val2017/',
         pipeline=test_pipeline,
-    )
-)
+    ))
 # optimizer
-optimizer = dict(type='SGD', lr=2e-3, momentum=0.9, weight_decay=0.0005)
+optimizer = dict(type='SGD', lr=5e-4, momentum=0.9, weight_decay=0.0005)
 optimizer_config = dict(grad_clip=dict(max_norm=35, norm_type=2))
 # learning policy
 lr_config = dict(
@@ -117,4 +110,4 @@
 workflow = [('train', 1)]
 evaluation = dict(interval=1, metric=['bbox'])
 # TODO: Remove hot fix
-find_unused_parameters=True
+find_unused_parameters = True