create：初始化

owndata/README.dataset.txt

+# Mask Wearing > 416x416-black-padding
+https://public.roboflow.ai/object-detection/mask-wearing
+
+Provided by [Joseph Nelson](https://twitter.com/josephofiowa)
+License: Public Domain
+
+# Overview
+
+The `Mask Wearing` dataset is an object detection dataset of individuals wearing various types of masks and those without masks. The images were originally collected by Cheng Hsun Teng from Eden Social Welfare Foundation, Taiwan and relabled by the Roboflow team.
+
+Example image (some with masks, some without):
+![Example Image](https://i.imgur.com/Z2yQ4YC.png)
+
+# Use Cases
+
+One could use this dataset to build a system for detecting if an individual is wearing a mask in a given photo.
+
+# Using this Dataset
+
+Use the `fork` button to copy this dataset to your own Roboflow account and export it with new preprocessing settings (perhaps resized for your model's desired format or converted to grayscale), or additional augmentations to make your model generalize better. 
+
+# About Roboflow
+
+[Roboflow](https://roboflow.ai) makes managing, preprocessing, augmenting, and versioning datasets for computer vision seamless.
+
+Developers reduce 50% of their code when using Roboflow's workflow, automate annotation quality assurance, save training time, and increase model reproducibility.
+
+#### [![Roboflow Workmark](https://i.imgur.com/WHFqYSJ.png =350x)](https://roboflow.ai)
\ No newline at end of file

owndata/README.roboflow.txt

+
+Mask Wearing - v1 416x416-black-padding
+==============================
+
+This dataset was exported via roboflow.ai on June 11, 2020 at 1:32 AM GMT
+
+It includes 149 images.
+People are annotated in YOLO v5 PyTorch format.
+
+The following pre-processing was applied to each image:
+* Auto-orientation of pixel data (with EXIF-orientation stripping)
+* Resize to 416x416 (Fit (black edges))
+
+No image augmentation techniques were applied.
+
+

owndata/data.yaml

+train: owndata/train/images
+val: owndata/valid/images
+
+nc: 2
+names: ['mask', 'no-mask']
\ No newline at end of file

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owndata/train/labels/rawImage_jpg.rf.8bdbe22463c3162f05180ff91e67f039.txt

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owndata/train/labels/remote (1)_jpeg.rf.df7fe4fb8181ab460fc57d04a9991de5.txt

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owndata/train/labels/sars-gettyimages-157005245_jpg.rf.5f33a6bd1f780b98e348507f3835d4d6.txt

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owndata/train/labels/sdfsdfsfff_jpg.rf.c4aca6cc392df43f61e14ac002741ab6.txt

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owndata/train/labels/sdsdsff_jpg.rf.09e108ae66cf64a3e852ba71cd079040.txt

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owndata/train/labels/sgssgg_jpeg.rf.f8a8d53430471346c8e823f41dd44afc.txt

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owndata/train/labels/shutterstock_289132226_jpg.rf.2fb2653c829b5d8f4442db65341441c0.txt

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owndata/train/labels/shutterstock_584407723_jpg.rf.bb5ad9ec2eb1ae4510ee88524e453043.txt

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owndata/train/labels/skynews-coronavirus-london-fashion-week_4920359_jpg.rf.cf79aa98be9f8687d550dc35caf9edb6.txt

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owndata/train/labels/skypost16012020a01s_jpg.rf.f52aa2d35c2002c3003e1771ea8e650d.txt

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owndata/train/labels/smartmi-3pcs-filter-mask-pm25-haze-dustproof-mask-with-vent_jpg.rf.c5b0c5b7666032c5b4634740eafde234.txt

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owndata/train/labels/so(19)_jpg.rf.0f2cb945829d1efef8e7fdf7757bd27e.txt

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owndata/train/labels/so(24) (1)_jpg.rf.1f4af0bfb01c55eb2ebf890b72a6f58c.txt

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owndata/train/labels/soo(1)_jpg.rf.d722163e3c3e0b9f1e4b7a73ea6893cb.txt

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owndata/train/labels/soooo_jpg.rf.accf5a6d0b0fe444b354a2d293821715.txt

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owndata/train/labels/stsciRq_png.rf.32af3f507296909b52bed7d5649e6d45.txt

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owndata/train/labels/thai_cov-transmission030220_jpg.rf.bdec1f9f73cff2be8d795fcc7665525b.txt

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owndata/train/labels/thumbnail-ba5c72edb320b49a69e86b05775c49b2-scaled-1_jpeg.rf.035d587add7bc2a6c7616d72e56bfad4.txt

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owndata/train/labels/unnamed_jpg.rf.638850185c6f05a027f34188518f6a9e.txt

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owndata/train/labels/upload-productImg-1527496119162_320_234_jpeg.rf.d7affc7d5fe3df8bc9a7c5b9678a3c3c.txt

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owndata/train/labels/virus_jpg.rf.dc9789ac36ce03125dccaad2f106ed90.txt

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owndata/train/labels/virus_protection123_jpg.rf.d401b0dc63d28e5afed1324e32b5e985.txt

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owndata/train/labels/w1240-p16x9-5f8aa310737f8e0e6c43d95a68a82b03b6f60106_jpg.rf.104bedd5b3bad4a0d0a453203e0617a3.txt

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owndata/train/labels/w1240-p16x9-6f1db5e0460631cfa98d2d6d8032942f81700bb0_jpg.rf.8c642180c2f1fc98109dad7ff09fe24c.txt

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owndata/valid/labels/0009S6815V3PEU1N-C123-F4_jpg.rf.6b0befd018e6308b6029a17a2ee08c48.txt

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owndata/valid/labels/000_1OC3DT_jpg.rf.0570a1f4ab79e324496c311456b6b1f8.txt

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owndata/valid/labels/002_1024_jpeg.rf.b8c41940cb8dd4fa61e92892345859ad.txt

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\ No newline at end of file

owndata/valid/labels/0109-00176-096b1_jpg.rf.c55de2d88f34d1217acdc245fd8292fa.txt

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\ No newline at end of file

owndata/valid/labels/022814asiatodaymasks_960x540_jpg.rf.20ad64bc5ec9eed694d9f559b9aba31d.txt

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\ No newline at end of file

owndata/valid/labels/025418_springwest005_jpg.rf.9d634581749567c27d459b574b431f74.txt

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\ No newline at end of file

owndata/valid/labels/08165739_jpg.rf.68cc16cde41ba8799e983506931416b8.txt

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\ No newline at end of file

owndata/valid/labels/08_11_2019-airpollution_234_19737819_192539446_jpg.rf.113e45f57dba09fde40d8490ae957fe6.txt

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\ No newline at end of file

owndata/valid/labels/0ad90195-cd77-489e-bf85-08c83b80d3e0_jpg.rf.20ed8f759c47a565b60684cfd4524a21.txt

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\ No newline at end of file

owndata/valid/labels/10fea_8011463765e2aa28b386cf_jpg.rf.0b90546b568e369f33ca67b3208b1655.txt

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\ No newline at end of file

owndata/valid/labels/1125506397_15801322206581n_jpg.rf.e5618d107f187fa409de96fcc56148ff.txt

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\ No newline at end of file

owndata/valid/labels/1196686205_jpg_14_jpg.rf.ff88135a0f165ca412244980acfbe591.txt

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\ No newline at end of file

owndata/valid/labels/1197315184_jpg_0_jpg.rf.39eb63061e0efb89a8f12a31d676daea.txt

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\ No newline at end of file

owndata/valid/labels/1197620896_jpg.rf.161417d4b3eafad7376c0ed2f2d66f51.txt

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\ No newline at end of file

owndata/valid/labels/1483800496-3386248642_jpg.rf.1aff1d3aed5aa07389738834833e8b9b.txt

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\ No newline at end of file

owndata/valid/labels/15150794626913_jpg.rf.fd41a2c638de913958a46ee288deb908.txt

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\ No newline at end of file

owndata/valid/labels/15391513321824spp815on8_jpg.rf.0fb7d846ae187777d61da0d24f67114c.txt

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\ No newline at end of file

owndata/valid/labels/REVZGCBIJNQPMIIXOKDCQA3GJI_jpg.rf.ca8353dc437234ee009df613c8b34137.txt

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\ No newline at end of file

owndata/valid/labels/S1-EV360_FACEMA_M_20200130144349_jpg.rf.a641b3a9b315b4de3b3214da280cafab.txt

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\ No newline at end of file

owndata/valid/labels/phpM5suKS_jpg.rf.556d78a695ded9fb5f5d1848c85ed2e0.txt

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\ No newline at end of file

owndata/valid/labels/r1000019q669394n9qp_jpg.rf.827235a6fff02f26ce1320d926f9c5bd.txt

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\ No newline at end of file

owndata/valid/labels/r1400018548960op29s_jpg.rf.d052eff94795b87ea6ad365aef959779.txt

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\ No newline at end of file

owndata/valid/labels/sdgdsgsg_jpg.rf.f6f5f4d4bc541a470631516b804fa642.txt

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\ No newline at end of file

owndata/valid/labels/shutterstock_1145933543-e1579497052960_jpg.rf.f3807b96202c59d946e24047e52e92d0.txt

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\ No newline at end of file

owndata/valid/labels/shutterstock_editorial_10536831j_2e16d0ba_fill-1200x650_jpg.rf.c77c476c19e1ef443057d7ff1a1c9396.txt

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\ No newline at end of file

owndata/valid/labels/stock-photo-mother-and-her-daughter-walking-go-to-school-with-wearing-a-protection-mask-against-pm-air-1346870465_jpg.rf.a6b929aae5f5f3dc8beac91039f8c85a.txt

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\ No newline at end of file

owndata/valid/labels/us-state-department-warns-against-visiting-china-citing-coronavirus_jpg.rf.e3a632121d73efda9ad7c4c5d5000bad.txt

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\ No newline at end of file

owndata/valid/labels/w1240-p16x9-CORONAVIRUS-CHINA-HEALTH-APPLE STORE_jpg.rf.8f83c6922f9fa841301e6722c35ec9e4.txt

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\ No newline at end of file

owndata/valid/labels/w1240-p16x9-coronavirus_CHINA-HEALTH_jpg.rf.73f3f135732ac6139a592ab1139f604a.txt

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\ No newline at end of file

owndata/yolov5s.yaml

+# YOLOv5 🚀 by Ultralytics, GPL-3.0 license
+
+# Parameters
+nc: 2  # number of classes
+depth_multiple: 0.33  # model depth multiple
+width_multiple: 0.50  # layer channel multiple
+anchors:
+  - [10,13, 16,30, 33,23]  # P3/8
+  - [30,61, 62,45, 59,119]  # P4/16
+  - [116,90, 156,198, 373,326]  # P5/32
+
+# YOLOv5 v6.0 backbone
+backbone:
+  # [from, number, module, args]
+  [[-1, 1, Conv, [64, 6, 2, 2]],  # 0-P1/2
+   [-1, 1, Conv, [128, 3, 2]],  # 1-P2/4
+   [-1, 3, C3, [128]],
+   [-1, 1, Conv, [256, 3, 2]],  # 3-P3/8
+   [-1, 6, C3, [256]],
+   [-1, 1, Conv, [512, 3, 2]],  # 5-P4/16
+   [-1, 9, C3, [512]],
+   [-1, 1, Conv, [1024, 3, 2]],  # 7-P5/32
+   [-1, 3, C3, [1024]],
+   [-1, 1, SPPF, [1024, 5]],  # 9
+  ]
+
+# YOLOv5 v6.0 head
+head:
+  [[-1, 1, Conv, [512, 1, 1]],
+   [-1, 1, nn.Upsample, [None, 2, 'nearest']],
+   [[-1, 6], 1, Concat, [1]],  # cat backbone P4
+   [-1, 3, C3, [512, False]],  # 13
+
+   [-1, 1, Conv, [256, 1, 1]],
+   [-1, 1, nn.Upsample, [None, 2, 'nearest']],
+   [[-1, 4], 1, Concat, [1]],  # cat backbone P3
+   [-1, 3, C3, [256, False]],  # 17 (P3/8-small)
+
+   [-1, 1, Conv, [256, 3, 2]],
+   [[-1, 14], 1, Concat, [1]],  # cat head P4
+   [-1, 3, C3, [512, False]],  # 20 (P4/16-medium)
+
+   [-1, 1, Conv, [512, 3, 2]],
+   [[-1, 10], 1, Concat, [1]],  # cat head P5
+   [-1, 3, C3, [1024, False]],  # 23 (P5/32-large)
+
+   [[17, 20, 23], 1, Detect, [nc, anchors]],  # Detect(P3, P4, P5)
+  ]

train.py

@@ -70,7 +70,7 @@ GIT_INFO = check_git_info()
 def train(hyp, opt, device, callbacks):  # hyp is path/to/hyp.yaml or hyp dictionary
     save_dir, epochs, batch_size, weights, single_cls, evolve, data, cfg, resume, noval, nosave, workers, freeze = \
         Path(opt.save_dir), opt.epochs, opt.batch_size, opt.weights, opt.single_cls, opt.evolve, opt.data, opt.cfg, \
-        opt.resume, opt.noval, opt.nosave, opt.workers, opt.freeze
+            opt.resume, opt.noval, opt.nosave, opt.workers, opt.freeze
     callbacks.run('on_pretrain_routine_start')
 
     # Directories
@@ -435,11 +435,11 @@ def train(hyp, opt, device, callbacks):  # hyp is path/to/hyp.yaml or hyp dictio
 def parse_opt(known=False):
     parser = argparse.ArgumentParser()
     parser.add_argument('--weights', type=str, default=ROOT / 'yolov5s.pt', help='initial weights path')
-    parser.add_argument('--cfg', type=str, default='', help='model.yaml path')
-    parser.add_argument('--data', type=str, default=ROOT / 'data/coco128.yaml', help='dataset.yaml path')
+    parser.add_argument('--cfg', type=str, default='owndata/yolov5s.yaml', help='model.yaml path')
+    parser.add_argument('--data', type=str, default='owndata/data.yaml', help='dataset.yaml path')
     parser.add_argument('--hyp', type=str, default=ROOT / 'data/hyps/hyp.scratch-low.yaml', help='hyperparameters path')
     parser.add_argument('--epochs', type=int, default=100, help='total training epochs')
-    parser.add_argument('--batch-size', type=int, default=16, help='total batch size for all GPUs, -1 for autobatch')
+    parser.add_argument('--batch-size', type=int, default=32, help='total batch size for all GPUs, -1 for autobatch')
     parser.add_argument('--imgsz', '--img', '--img-size', type=int, default=640, help='train, val image size (pixels)')
     parser.add_argument('--rect', action='store_true', help='rectangular training')
     parser.add_argument('--resume', nargs='?', const=True, default=False, help='resume most recent training')
@@ -577,7 +577,7 @@ def main(opt, callbacks=Callbacks()):
                 'gsutil',
                 'cp',
                 f'gs://{opt.bucket}/evolve.csv',
-                str(evolve_csv),])
+                str(evolve_csv), ])
 
         for _ in range(opt.evolve):  # generations to evolve
             if evolve_csv.exists():  # if evolve.csv exists: select best hyps and mutate