Merge pull request #156 from mjq2020/dev

add：swift yolo and delete other yolo

configs/yolov5/yolov5_s_1xb16_300e_coco.py → configs/swift_yolo/swift_yolo_1xb16_300e_coco.py

@@ -4,7 +4,7 @@
 # MODEL
 num_classes = 71
 deepen_factor = 0.33
-widen_factor = 0.5
+widen_factor = 0.15
 
 # DATA
 dataset_type = 'sscma.CustomYOLOv5CocoDataset'
@@ -17,12 +17,11 @@
 data_root = 'https://universe.roboflow.com/ds/z5UOcgxZzD?key=bwx9LQUT0t'
 height = 640
 width = 640
-imgsz = (width, height)
 batch = 16
 workers = 2
 val_batch = batch
 val_workers = workers
-
+imgsz = (width, height)
 
 # TRAIN
 persistent_workers = True
@@ -86,8 +85,22 @@
     dict(type='LoadAnnotations', with_bbox=True),
 ]
 
+# from mmyolo.datasets.transforms import YOLOv5RandomAffine
+
+color_space = [
+    [dict(type='mmdet.ColorTransform')],
+    [dict(type='mmdet.AutoContrast')],
+    [dict(type='mmdet.Equalize')],
+    [dict(type='mmdet.Sharpness')],
+    [dict(type='mmdet.Posterize')],
+    [dict(type='mmdet.Solarize')],
+    [dict(type='mmdet.Color')],
+    [dict(type='mmdet.Contrast')],
+    [dict(type='mmdet.Brightness')],
+]
 train_pipeline = [
-    *pre_transform,
+    dict(type='LoadImageFromFile', file_client_args=dict(backend='disk')),
+    dict(type='LoadAnnotations', with_bbox=True),
     dict(type='Mosaic', img_scale=imgsz, pad_val=114.0, pre_transform=pre_transform),
     dict(
         type='YOLOv5RandomAffine',
@@ -104,6 +117,13 @@
         bbox_params=dict(type='BboxParams', format='pascal_voc', label_fields=['gt_bboxes_labels', 'gt_ignore_flags']),
         keymap={'img': 'image', 'gt_bboxes': 'bboxes'},
     ),
+    dict(
+        type='mmdet.RandomOrder',
+        transforms=[
+            dict(type='mmdet.RandAugment', aug_space=color_space, aug_num=1),
+            # dict(type='mmdet.RandAugment', aug_space=geometric, aug_num=1),
+        ],
+    ),
     dict(type='YOLOv5HSVRandomAug'),
     dict(type='mmdet.RandomFlip', prob=0.5),
     dict(