OCR Task开发

[lpj0822]

• [x] 1.理解https://github.com/JaidedAI/EasyOCR代码
• [x] 2.定义OCR功能的标注数据格式
• [x] 3.在easyai中实现一种OCR算法
• [x] 4.测试OCR功能正常运行

[MiniBullLab]

中文OCR地址：https://github.com/DayBreak-u/chineseocr_lite/tree/master

[lpj0822]

https://github.com/PaddlePaddle/PaddleOCR

[vitahlin]

OCR数据格式：json

[lpj0822]

https://github.com/open-mmlab/mmocr https://github.com/JaidedAI/EasyOCR

[lpj0822]

https://github.com/DayBreak-u/chineseocr_lite

[MiniBullLab]

带有训练的dbnet+crnn ocr代码: https://github.com/WenmuZhou/PytorchOCR

[MiniBullLab]

ocr在json文件中的格式：

{
    "annotation": "Annotations",
    "database": "lpj_dataset",
    "filename": "000008.png",
    "folder": "JPEGImages",
    "objectCount": 2,
    "objects": {
        "ocrObject": [
            {
                "class": "others",  /* ‘machine printed’ or ‘handwritten’ or ‘others’ */
                "polygon": [
                    1221,
                    644,
                    1234,
                    636,
                    1248,
                    633,
                    1270,
                    634,
                    1274,
                    645,
                    1284,
                    657,
                    1267,
                    664,
                    1240,
                    663,
                    1221,
                    664,
                    1217,
                    657
                ],
                "pointCount": 10,
                "transcription": "my name",
                "language": "english", 
                "illegibility": 0
            }
        ]
    },
    "owner": "lpj",
    "path": "/home/lpj/Desktop/test_img/JPEGImages/000008.png",
    "size": {
        "depth": 3,
        "height": 1080,
        "width": 1920
    }
}

[foww-0001]

ocr数据已上传，路径在数据集/公开数据/文字识别数据

[vitahlin]

数据格式已经确定

[lpj0822]

dbnet与CRNN inference编写完成

[lpj0822]

dbnet权重模型转换

resnet18不同： resnet 比对感觉head_type = 2，初始通道是32，

id | pytorchocr层名 | pytorchocr层大小  | 我们的层名  | 我们的层大小
0 backbone.conv1.0.conv.weight torch.Size([32, 3, 3, 3]) baseNet_0.convBNActivationBlock_0.block.convolutional.weight torch.Size([32, 3, 3, 3])
1 backbone.conv1.0.bn.weight torch.Size([32]) baseNet_0.convBNActivationBlock_0.block.bn2d.weight torch.Size([32])
2 backbone.conv1.0.bn.bias torch.Size([32]) baseNet_0.convBNActivationBlock_0.block.bn2d.bias torch.Size([32])
3 backbone.conv1.0.bn.running_mean torch.Size([32]) baseNet_0.convBNActivationBlock_0.block.bn2d.running_mean torch.Size([32])
4 backbone.conv1.0.bn.running_var torch.Size([32]) baseNet_0.convBNActivationBlock_0.block.bn2d.running_var torch.Size([32])
5 backbone.conv1.1.conv.weight torch.Size([32, 32, 3, 3]) baseNet_0.convBNActivationBlock_1.block.convolutional.weight torch.Size([32, 32, 3, 3])
6 backbone.conv1.1.bn.weight torch.Size([32]) baseNet_0.convBNActivationBlock_1.block.bn2d.weight torch.Size([32])
7 backbone.conv1.1.bn.bias torch.Size([32]) baseNet_0.convBNActivationBlock_1.block.bn2d.bias torch.Size([32])
8 backbone.conv1.1.bn.running_mean torch.Size([32]) baseNet_0.convBNActivationBlock_1.block.bn2d.running_mean torch.Size([32])
9 backbone.conv1.1.bn.running_var torch.Size([32]) baseNet_0.convBNActivationBlock_1.block.bn2d.running_var torch.Size([32])
10 backbone.conv1.2.conv.weight torch.Size([64, 32, 3, 3]) baseNet_0.convBNActivationBlock_2.block.convolutional.weight torch.Size([32, 32, 3, 3])
11 backbone.conv1.2.bn.weight torch.Size([64]) baseNet_0.convBNActivationBlock_2.block.bn2d.weight torch.Size([32])
12 backbone.conv1.2.bn.bias torch.Size([64]) baseNet_0.convBNActivationBlock_2.block.bn2d.bias torch.Size([32])
13 backbone.conv1.2.bn.running_mean torch.Size([64]) baseNet_0.convBNActivationBlock_2.block.bn2d.running_mean torch.Size([32])
14 backbone.conv1.2.bn.running_var torch.Size([64]) baseNet_0.convBNActivationBlock_2.block.bn2d.running_var torch.Size([32])
15 backbone.stages.0.0.conv0.conv.weight torch.Size([64, 64, 3, 3]) baseNet_0.down_residualBlock_3.residual.0.block.convolutional.weight torch.Size([64, 32, 3, 3])
16 backbone.stages.0.0.conv0.bn.weight torch.Size([64]) baseNet_0.down_residualBlock_3.residual.0.block.bn2d.weight torch.Size([64])
17 backbone.stages.0.0.conv0.bn.bias torch.Size([64]) baseNet_0.down_residualBlock_3.residual.0.block.bn2d.bias torch.Size([64])
18 backbone.stages.0.0.conv0.bn.running_mean torch.Size([64]) baseNet_0.down_residualBlock_3.residual.0.block.bn2d.running_mean torch.Size([64])
19 backbone.stages.0.0.conv0.bn.running_var torch.Size([64]) baseNet_0.down_residualBlock_3.residual.0.block.bn2d.running_var torch.Size([64])
20 backbone.stages.0.0.conv1.conv.weight torch.Size([64, 64, 3, 3]) baseNet_0.down_residualBlock_3.residual.1.block.convolutional.weight torch.Size([64, 64, 3, 3])
21 backbone.stages.0.0.conv1.bn.weight torch.Size([64]) baseNet_0.down_residualBlock_3.residual.1.block.bn2d.weight torch.Size([64])
22 backbone.stages.0.0.conv1.bn.bias torch.Size([64]) baseNet_0.down_residualBlock_3.residual.1.block.bn2d.bias torch.Size([64])
23 backbone.stages.0.0.conv1.bn.running_mean torch.Size([64]) baseNet_0.down_residualBlock_3.residual.1.block.bn2d.running_mean torch.Size([64])
24 backbone.stages.0.0.conv1.bn.running_var torch.Size([64]) baseNet_0.down_residualBlock_3.residual.1.block.bn2d.running_var torch.Size([64])
25 backbone.stages.0.0.shortcut.conv.conv.weight torch.Size([64, 64, 1, 1]) baseNet_0.down_residualBlock_3.shortcut.block.convolutional.weight torch.Size([64, 32, 1, 1])
26 backbone.stages.0.0.shortcut.conv.bn.weight torch.Size([64]) baseNet_0.down_residualBlock_3.shortcut.block.bn2d.weight torch.Size([64])
27 backbone.stages.0.0.shortcut.conv.bn.bias torch.Size([64]) baseNet_0.down_residualBlock_3.shortcut.block.bn2d.bias torch.Size([64])
28 backbone.stages.0.0.shortcut.conv.bn.running_mean torch.Size([64]) baseNet_0.down_residualBlock_3.shortcut.block.bn2d.running_mean torch.Size([64])
29 backbone.stages.0.0.shortcut.conv.bn.running_var torch.Size([64]) baseNet_0.down_residualBlock_3.shortcut.block.bn2d.running_var torch.Size([64])
30 backbone.stages.0.1.conv0.conv.weight torch.Size([64, 64, 3, 3]) baseNet_0.residualBlock_4.residual.0.block.convolutional.weight torch.Size([64, 64, 3, 3])
31 backbone.stages.0.1.conv0.bn.weight torch.Size([64]) baseNet_0.residualBlock_4.residual.0.block.bn2d.weight torch.Size([64])
32 backbone.stages.0.1.conv0.bn.bias torch.Size([64]) baseNet_0.residualBlock_4.residual.0.block.bn2d.bias torch.Size([64])
33 backbone.stages.0.1.conv0.bn.running_mean torch.Size([64]) baseNet_0.residualBlock_4.residual.0.block.bn2d.running_mean torch.Size([64])
34 backbone.stages.0.1.conv0.bn.running_var torch.Size([64]) baseNet_0.residualBlock_4.residual.0.block.bn2d.running_var torch.Size([64])
35 backbone.stages.0.1.conv1.conv.weight torch.Size([64, 64, 3, 3]) baseNet_0.residualBlock_4.residual.1.block.convolutional.weight torch.Size([64, 64, 3, 3])
36 backbone.stages.0.1.conv1.bn.weight torch.Size([64]) baseNet_0.residualBlock_4.residual.1.block.bn2d.weight torch.Size([64])
37 backbone.stages.0.1.conv1.bn.bias torch.Size([64]) baseNet_0.residualBlock_4.residual.1.block.bn2d.bias torch.Size([64])
38 backbone.stages.0.1.conv1.bn.running_mean torch.Size([64]) baseNet_0.residualBlock_4.residual.1.block.bn2d.running_mean torch.Size([64])
39 backbone.stages.0.1.conv1.bn.running_var torch.Size([64]) baseNet_0.residualBlock_4.residual.1.block.bn2d.running_var torch.Size([64])
40 backbone.stages.1.0.conv0.conv.weight torch.Size([128, 64, 3, 3]) baseNet_0.down_residualBlock_5.residual.0.block.convolutional.weight torch.Size([128, 64, 3, 3])
41 backbone.stages.1.0.conv0.bn.weight torch.Size([128]) baseNet_0.down_residualBlock_5.residual.0.block.bn2d.weight torch.Size([128])
42 backbone.stages.1.0.conv0.bn.bias torch.Size([128]) baseNet_0.down_residualBlock_5.residual.0.block.bn2d.bias torch.Size([128])
43 backbone.stages.1.0.conv0.bn.running_mean torch.Size([128]) baseNet_0.down_residualBlock_5.residual.0.block.bn2d.running_mean torch.Size([128])
44 backbone.stages.1.0.conv0.bn.running_var torch.Size([128]) baseNet_0.down_residualBlock_5.residual.0.block.bn2d.running_var torch.Size([128])
45 backbone.stages.1.0.conv1.conv.weight torch.Size([128, 128, 3, 3]) baseNet_0.down_residualBlock_5.residual.1.block.convolutional.weight torch.Size([128, 128, 3, 3])
46 backbone.stages.1.0.conv1.bn.weight torch.Size([128]) baseNet_0.down_residualBlock_5.residual.1.block.bn2d.weight torch.Size([128])
47 backbone.stages.1.0.conv1.bn.bias torch.Size([128]) baseNet_0.down_residualBlock_5.residual.1.block.bn2d.bias torch.Size([128])
48 backbone.stages.1.0.conv1.bn.running_mean torch.Size([128]) baseNet_0.down_residualBlock_5.residual.1.block.bn2d.running_mean torch.Size([128])
49 backbone.stages.1.0.conv1.bn.running_var torch.Size([128]) baseNet_0.down_residualBlock_5.residual.1.block.bn2d.running_var torch.Size([128])
50 backbone.stages.1.0.shortcut.conv.conv.weight torch.Size([128, 64, 1, 1]) baseNet_0.down_residualBlock_5.shortcut.block.convolutional.weight torch.Size([128, 64, 1, 1])
51 backbone.stages.1.0.shortcut.conv.bn.weight torch.Size([128]) baseNet_0.down_residualBlock_5.shortcut.block.bn2d.weight torch.Size([128])
52 backbone.stages.1.0.shortcut.conv.bn.bias torch.Size([128]) baseNet_0.down_residualBlock_5.shortcut.block.bn2d.bias torch.Size([128])
53 backbone.stages.1.0.shortcut.conv.bn.running_mean torch.Size([128]) baseNet_0.down_residualBlock_5.shortcut.block.bn2d.running_mean torch.Size([128])
54 backbone.stages.1.0.shortcut.conv.bn.running_var torch.Size([128]) baseNet_0.down_residualBlock_5.shortcut.block.bn2d.running_var torch.Size([128])
55 backbone.stages.1.1.conv0.conv.weight torch.Size([128, 128, 3, 3]) baseNet_0.residualBlock_6.residual.0.block.convolutional.weight torch.Size([128, 128, 3, 3])
56 backbone.stages.1.1.conv0.bn.weight torch.Size([128]) baseNet_0.residualBlock_6.residual.0.block.bn2d.weight torch.Size([128])
57 backbone.stages.1.1.conv0.bn.bias torch.Size([128]) baseNet_0.residualBlock_6.residual.0.block.bn2d.bias torch.Size([128])
58 backbone.stages.1.1.conv0.bn.running_mean torch.Size([128]) baseNet_0.residualBlock_6.residual.0.block.bn2d.running_mean torch.Size([128])
59 backbone.stages.1.1.conv0.bn.running_var torch.Size([128]) baseNet_0.residualBlock_6.residual.0.block.bn2d.running_var torch.Size([128])
60 backbone.stages.1.1.conv1.conv.weight torch.Size([128, 128, 3, 3]) baseNet_0.residualBlock_6.residual.1.block.convolutional.weight torch.Size([128, 128, 3, 3])
61 backbone.stages.1.1.conv1.bn.weight torch.Size([128]) baseNet_0.residualBlock_6.residual.1.block.bn2d.weight torch.Size([128])
62 backbone.stages.1.1.conv1.bn.bias torch.Size([128]) baseNet_0.residualBlock_6.residual.1.block.bn2d.bias torch.Size([128])
63 backbone.stages.1.1.conv1.bn.running_mean torch.Size([128]) baseNet_0.residualBlock_6.residual.1.block.bn2d.running_mean torch.Size([128])
64 backbone.stages.1.1.conv1.bn.running_var torch.Size([128]) baseNet_0.residualBlock_6.residual.1.block.bn2d.running_var torch.Size([128])
65 backbone.stages.2.0.conv0.conv.weight torch.Size([256, 128, 3, 3]) baseNet_0.down_residualBlock_7.residual.0.block.convolutional.weight torch.Size([256, 128, 3, 3])
66 backbone.stages.2.0.conv0.bn.weight torch.Size([256]) baseNet_0.down_residualBlock_7.residual.0.block.bn2d.weight torch.Size([256])
67 backbone.stages.2.0.conv0.bn.bias torch.Size([256]) baseNet_0.down_residualBlock_7.residual.0.block.bn2d.bias torch.Size([256])
68 backbone.stages.2.0.conv0.bn.running_mean torch.Size([256]) baseNet_0.down_residualBlock_7.residual.0.block.bn2d.running_mean torch.Size([256])
69 backbone.stages.2.0.conv0.bn.running_var torch.Size([256]) baseNet_0.down_residualBlock_7.residual.0.block.bn2d.running_var torch.Size([256])
70 backbone.stages.2.0.conv1.conv.weight torch.Size([256, 256, 3, 3]) baseNet_0.down_residualBlock_7.residual.1.block.convolutional.weight torch.Size([256, 256, 3, 3])
71 backbone.stages.2.0.conv1.bn.weight torch.Size([256]) baseNet_0.down_residualBlock_7.residual.1.block.bn2d.weight torch.Size([256])
72 backbone.stages.2.0.conv1.bn.bias torch.Size([256]) baseNet_0.down_residualBlock_7.residual.1.block.bn2d.bias torch.Size([256])
73 backbone.stages.2.0.conv1.bn.running_mean torch.Size([256]) baseNet_0.down_residualBlock_7.residual.1.block.bn2d.running_mean torch.Size([256])
74 backbone.stages.2.0.conv1.bn.running_var torch.Size([256]) baseNet_0.down_residualBlock_7.residual.1.block.bn2d.running_var torch.Size([256])
75 backbone.stages.2.0.shortcut.conv.conv.weight torch.Size([256, 128, 1, 1]) baseNet_0.down_residualBlock_7.shortcut.block.convolutional.weight torch.Size([256, 128, 1, 1])
76 backbone.stages.2.0.shortcut.conv.bn.weight torch.Size([256]) baseNet_0.down_residualBlock_7.shortcut.block.bn2d.weight torch.Size([256])
77 backbone.stages.2.0.shortcut.conv.bn.bias torch.Size([256]) baseNet_0.down_residualBlock_7.shortcut.block.bn2d.bias torch.Size([256])
78 backbone.stages.2.0.shortcut.conv.bn.running_mean torch.Size([256]) baseNet_0.down_residualBlock_7.shortcut.block.bn2d.running_mean torch.Size([256])
79 backbone.stages.2.0.shortcut.conv.bn.running_var torch.Size([256]) baseNet_0.down_residualBlock_7.shortcut.block.bn2d.running_var torch.Size([256])
80 backbone.stages.2.1.conv0.conv.weight torch.Size([256, 256, 3, 3]) baseNet_0.residualBlock_8.residual.0.block.convolutional.weight torch.Size([256, 256, 3, 3])
81 backbone.stages.2.1.conv0.bn.weight torch.Size([256]) baseNet_0.residualBlock_8.residual.0.block.bn2d.weight torch.Size([256])
82 backbone.stages.2.1.conv0.bn.bias torch.Size([256]) baseNet_0.residualBlock_8.residual.0.block.bn2d.bias torch.Size([256])
83 backbone.stages.2.1.conv0.bn.running_mean torch.Size([256]) baseNet_0.residualBlock_8.residual.0.block.bn2d.running_mean torch.Size([256])
84 backbone.stages.2.1.conv0.bn.running_var torch.Size([256]) baseNet_0.residualBlock_8.residual.0.block.bn2d.running_var torch.Size([256])
85 backbone.stages.2.1.conv1.conv.weight torch.Size([256, 256, 3, 3]) baseNet_0.residualBlock_8.residual.1.block.convolutional.weight torch.Size([256, 256, 3, 3])
86 backbone.stages.2.1.conv1.bn.weight torch.Size([256]) baseNet_0.residualBlock_8.residual.1.block.bn2d.weight torch.Size([256])
87 backbone.stages.2.1.conv1.bn.bias torch.Size([256]) baseNet_0.residualBlock_8.residual.1.block.bn2d.bias torch.Size([256])
88 backbone.stages.2.1.conv1.bn.running_mean torch.Size([256]) baseNet_0.residualBlock_8.residual.1.block.bn2d.running_mean torch.Size([256])
89 backbone.stages.2.1.conv1.bn.running_var torch.Size([256]) baseNet_0.residualBlock_8.residual.1.block.bn2d.running_var torch.Size([256])
90 backbone.stages.3.0.conv0.conv.weight torch.Size([512, 256, 3, 3]) baseNet_0.down_residualBlock_9.residual.0.block.convolutional.weight torch.Size([512, 256, 3, 3])
91 backbone.stages.3.0.conv0.bn.weight torch.Size([512]) baseNet_0.down_residualBlock_9.residual.0.block.bn2d.weight torch.Size([512])
92 backbone.stages.3.0.conv0.bn.bias torch.Size([512]) baseNet_0.down_residualBlock_9.residual.0.block.bn2d.bias torch.Size([512])
93 backbone.stages.3.0.conv0.bn.running_mean torch.Size([512]) baseNet_0.down_residualBlock_9.residual.0.block.bn2d.running_mean torch.Size([512])
94 backbone.stages.3.0.conv0.bn.running_var torch.Size([512]) baseNet_0.down_residualBlock_9.residual.0.block.bn2d.running_var torch.Size([512])
95 backbone.stages.3.0.conv1.conv.weight torch.Size([512, 512, 3, 3]) baseNet_0.down_residualBlock_9.residual.1.block.convolutional.weight torch.Size([512, 512, 3, 3])
96 backbone.stages.3.0.conv1.bn.weight torch.Size([512]) baseNet_0.down_residualBlock_9.residual.1.block.bn2d.weight torch.Size([512])
97 backbone.stages.3.0.conv1.bn.bias torch.Size([512]) baseNet_0.down_residualBlock_9.residual.1.block.bn2d.bias torch.Size([512])
98 backbone.stages.3.0.conv1.bn.running_mean torch.Size([512]) baseNet_0.down_residualBlock_9.residual.1.block.bn2d.running_mean torch.Size([512])
99 backbone.stages.3.0.conv1.bn.running_var torch.Size([512]) baseNet_0.down_residualBlock_9.residual.1.block.bn2d.running_var torch.Size([512])
100 backbone.stages.3.0.shortcut.conv.conv.weight torch.Size([512, 256, 1, 1]) baseNet_0.down_residualBlock_9.shortcut.block.convolutional.weight torch.Size([512, 256, 1, 1])
101 backbone.stages.3.0.shortcut.conv.bn.weight torch.Size([512]) baseNet_0.down_residualBlock_9.shortcut.block.bn2d.weight torch.Size([512])
102 backbone.stages.3.0.shortcut.conv.bn.bias torch.Size([512]) baseNet_0.down_residualBlock_9.shortcut.block.bn2d.bias torch.Size([512])
103 backbone.stages.3.0.shortcut.conv.bn.running_mean torch.Size([512]) baseNet_0.down_residualBlock_9.shortcut.block.bn2d.running_mean torch.Size([512])
104 backbone.stages.3.0.shortcut.conv.bn.running_var torch.Size([512]) baseNet_0.down_residualBlock_9.shortcut.block.bn2d.running_var torch.Size([512])
105 backbone.stages.3.1.conv0.conv.weight torch.Size([512, 512, 3, 3]) baseNet_0.residualBlock_10.residual.0.block.convolutional.weight torch.Size([512, 512, 3, 3])
106 backbone.stages.3.1.conv0.bn.weight torch.Size([512]) baseNet_0.residualBlock_10.residual.0.block.bn2d.weight torch.Size([512])
107 backbone.stages.3.1.conv0.bn.bias torch.Size([512]) baseNet_0.residualBlock_10.residual.0.block.bn2d.bias torch.Size([512])
108 backbone.stages.3.1.conv0.bn.running_mean torch.Size([512]) baseNet_0.residualBlock_10.residual.0.block.bn2d.running_mean torch.Size([512])
109 backbone.stages.3.1.conv0.bn.running_var torch.Size([512]) baseNet_0.residualBlock_10.residual.0.block.bn2d.running_var torch.Size([512])
110 backbone.stages.3.1.conv1.conv.weight torch.Size([512, 512, 3, 3]) baseNet_0.residualBlock_10.residual.1.block.convolutional.weight torch.Size([512, 512, 3, 3])
111 backbone.stages.3.1.conv1.bn.weight torch.Size([512]) baseNet_0.residualBlock_10.residual.1.block.bn2d.weight torch.Size([512])
112 backbone.stages.3.1.conv1.bn.bias torch.Size([512]) baseNet_0.residualBlock_10.residual.1.block.bn2d.bias torch.Size([512])
113 backbone.stages.3.1.conv1.bn.running_mean torch.Size([512]) baseNet_0.residualBlock_10.residual.1.block.bn2d.running_mean torch.Size([512])
114 backbone.stages.3.1.conv1.bn.running_var torch.Size([512]) baseNet_0.residualBlock_10.residual.1.block.bn2d.running_var torch.Size([512])

反卷积没有bias： head.binarize.conv2.weight torch.Size([64, 64, 2, 2]) dbHead_2.binarize.conv2.block.deconv.weight torch.Size([64, 64, 2, 2]) head.binarize.conv2.bias torch.Size([64]) 缺少bias

@lpj0822

[foww-0001]

crnn中的MobileNetv3也有不同，少了第二层卷积torch.Size([8, 8, 1, 1])：

id | pytorchocr层名 | pytorchocr层大小  | 我们的层名  | 我们的层大小
0 backbone.conv1.conv.weight torch.Size([8, 3, 3, 3]) baseNet_0.convBNActivationBlock_0.block.convolutional.weight torch.Size([8, 3, 3, 3])
1 backbone.conv1.bn.weight torch.Size([8]) baseNet_0.convBNActivationBlock_0.block.bn2d.weight torch.Size([8])
2 backbone.conv1.bn.bias torch.Size([8]) baseNet_0.convBNActivationBlock_0.block.bn2d.bias torch.Size([8])
3 backbone.conv1.bn.running_mean torch.Size([8]) baseNet_0.convBNActivationBlock_0.block.bn2d.running_mean torch.Size([8])
4 backbone.conv1.bn.running_var torch.Size([8]) baseNet_0.convBNActivationBlock_0.block.bn2d.running_var torch.Size([8])
5 backbone.blocks.0.expand_conv.conv.weight torch.Size([8, 8, 1, 1]) baseNet_0.invertedResidualV2_1.block.convBNActivationBlock_1.block.convolutional.weight torch.Size([8, 1, 3, 3])
6 backbone.blocks.0.expand_conv.bn.weight torch.Size([8]) baseNet_0.invertedResidualV2_1.block.convBNActivationBlock_1.block.bn2d.weight torch.Size([8])
7 backbone.blocks.0.expand_conv.bn.bias torch.Size([8]) baseNet_0.invertedResidualV2_1.block.convBNActivationBlock_1.block.bn2d.bias torch.Size([8])
8 backbone.blocks.0.expand_conv.bn.running_mean torch.Size([8]) baseNet_0.invertedResidualV2_1.block.convBNActivationBlock_1.block.bn2d.running_mean torch.Size([8])
9 backbone.blocks.0.expand_conv.bn.running_var torch.Size([8]) baseNet_0.invertedResidualV2_1.block.convBNActivationBlock_1.block.bn2d.running_var torch.Size([8])

@lpj0822

[foww-0001]

少了一层1*1的卷积：

0 backbone.conv1.0.conv.weight torch.Size([32, 3, 3, 3]) baseNet_0.convBNActivationBlock_0.block.convolutional.weight torch.Size([32, 3, 3, 3])
1 backbone.conv1.0.bn.weight torch.Size([32]) baseNet_0.convBNActivationBlock_0.block.bn2d.weight torch.Size([32])
2 backbone.conv1.0.bn.bias torch.Size([32]) baseNet_0.convBNActivationBlock_0.block.bn2d.bias torch.Size([32])
3 backbone.conv1.0.bn.running_mean torch.Size([32]) baseNet_0.convBNActivationBlock_0.block.bn2d.running_mean torch.Size([32])
4 backbone.conv1.0.bn.running_var torch.Size([32]) baseNet_0.convBNActivationBlock_0.block.bn2d.running_var torch.Size([32])
5 backbone.conv1.1.conv.weight torch.Size([32, 32, 3, 3]) baseNet_0.convBNActivationBlock_1.block.convolutional.weight torch.Size([32, 32, 3, 3])
6 backbone.conv1.1.bn.weight torch.Size([32]) baseNet_0.convBNActivationBlock_1.block.bn2d.weight torch.Size([32])
7 backbone.conv1.1.bn.bias torch.Size([32]) baseNet_0.convBNActivationBlock_1.block.bn2d.bias torch.Size([32])
8 backbone.conv1.1.bn.running_mean torch.Size([32]) baseNet_0.convBNActivationBlock_1.block.bn2d.running_mean torch.Size([32])
9 backbone.conv1.1.bn.running_var torch.Size([32]) baseNet_0.convBNActivationBlock_1.block.bn2d.running_var torch.Size([32])
10 backbone.conv1.2.conv.weight torch.Size([64, 32, 3, 3]) baseNet_0.convBNActivationBlock_2.block.convolutional.weight torch.Size([64, 32, 3, 3])
11 backbone.conv1.2.bn.weight torch.Size([64]) baseNet_0.convBNActivationBlock_2.block.bn2d.weight torch.Size([64])
12 backbone.conv1.2.bn.bias torch.Size([64]) baseNet_0.convBNActivationBlock_2.block.bn2d.bias torch.Size([64])
13 backbone.conv1.2.bn.running_mean torch.Size([64]) baseNet_0.convBNActivationBlock_2.block.bn2d.running_mean torch.Size([64])
14 backbone.conv1.2.bn.running_var torch.Size([64]) baseNet_0.convBNActivationBlock_2.block.bn2d.running_var torch.Size([64])
15 backbone.stages.0.0.conv0.conv.weight torch.Size([64, 64, 3, 3]) baseNet_0.down_residualBlock_4.residual.0.block.convolutional.weight torch.Size([64, 64, 3, 3])
16 backbone.stages.0.0.conv0.bn.weight torch.Size([64]) baseNet_0.down_residualBlock_4.residual.0.block.bn2d.weight torch.Size([64])
17 backbone.stages.0.0.conv0.bn.bias torch.Size([64]) baseNet_0.down_residualBlock_4.residual.0.block.bn2d.bias torch.Size([64])
18 backbone.stages.0.0.conv0.bn.running_mean torch.Size([64]) baseNet_0.down_residualBlock_4.residual.0.block.bn2d.running_mean torch.Size([64])
19 backbone.stages.0.0.conv0.bn.running_var torch.Size([64]) baseNet_0.down_residualBlock_4.residual.0.block.bn2d.running_var torch.Size([64])
20 backbone.stages.0.0.conv1.conv.weight torch.Size([64, 64, 3, 3]) baseNet_0.down_residualBlock_4.residual.1.block.convolutional.weight torch.Size([64, 64, 3, 3])
21 backbone.stages.0.0.conv1.bn.weight torch.Size([64]) baseNet_0.down_residualBlock_4.residual.1.block.bn2d.weight torch.Size([64])
22 backbone.stages.0.0.conv1.bn.bias torch.Size([64]) baseNet_0.down_residualBlock_4.residual.1.block.bn2d.bias torch.Size([64])
23 backbone.stages.0.0.conv1.bn.running_mean torch.Size([64]) baseNet_0.down_residualBlock_4.residual.1.block.bn2d.running_mean torch.Size([64])
24 backbone.stages.0.0.conv1.bn.running_var torch.Size([64]) baseNet_0.down_residualBlock_4.residual.1.block.bn2d.running_var torch.Size([64])
25 backbone.stages.0.0.shortcut.conv.conv.weight torch.Size([64, 64, 1, 1]) baseNet_0.residualBlock_5.residual.0.block.convolutional.weight torch.Size([64, 64, 3, 3])
26 backbone.stages.0.0.shortcut.conv.bn.weight torch.Size([64]) baseNet_0.residualBlock_5.residual.0.block.bn2d.weight torch.Size([64])
27 backbone.stages.0.0.shortcut.conv.bn.bias torch.Size([64]) baseNet_0.residualBlock_5.residual.0.block.bn2d.bias torch.Size([64])
28 backbone.stages.0.0.shortcut.conv.bn.running_mean torch.Size([64]) baseNet_0.residualBlock_5.residual.0.block.bn2d.running_mean torch.Size([64])
29 backbone.stages.0.0.shortcut.conv.bn.running_var torch.Size([64]) baseNet_0.residualBlock_5.residual.0.block.bn2d.running_var torch.Size([64])

@lpj0822

[lpj0822]

已经修改

[foww-0001]

dbnet模型已经上传，在百度网盘下：深度学习模型文件/pytorch/pytorch_ocr下面

[foww-0001]

crnn中的最后fc参数不匹配：

227 fcLinear_3.weight torch.Size([6625, 96]) torch.Size([93, 96])
228 fcLinear_3.bias torch.Size([6625]) torch.Size([93])

[foww-0001]

dbHead_2.binarize.conv1.block.convolutional.weight dbHead_2.thresh.conv1.block.convolutional.weight 缺少bn参数。

[lpj0822]

已经修改

[foww-0001]

dbnet已重新上传。

[lpj0822]

dbnet运行：

 python3 easyai/inference_task.py -i /home/lpj/dataset/ocr_test -t polygon2d -m dbnet -w /home/lpj/dataset/dbnet.pt -s

[foww-0001]

新的CRNN已经上传。

[lpj0822]

dbnet infernce 已经跑通，可以多测试

[foww-0001]

LSTM中使用batch_first=False的需要在做一次transpose。

x_1 = torch.randn(100,200,512)
x_2 = x_1.transpose(0,1)

model_1 = torch.nn.LSTM(batch_first=True,hidden_size=1024,input_size=512)
model_2 = torch.nn.LSTM(batch_first=False,hidden_size=1024,input_size=512)

start_time_1 = time.time()

result_1 = model_1(x_1)
end_time_1 = time.time()

result_2 = model_2(x_2)
end_time_2 = time.time()

print(end_time_1 - start_time_1,end_time_2 - end_time_1)

[lpj0822]

rec text 运行：

python3 easyai/inference_task.py -t recognize_text -i /home/lpj/dataset/text_test -m CRNN -w /home/lpj/dataset/CRNN.pt

已测试，可以正常运行。

[lpj0822]

ocr 运行：

python3 ocr_infer.py --det_path /home/lpj/Downloads/ch_det_server_db_res18.pth --rec_path /home/lpj/Downloads/ch_rec_moblie_crnn_mbv3.pth --img_path /home/lpj/dataset/ocr_test/11.jpg

写错了，这是PytorchOCR的运行方式。

[MiniBullLab]

python3 easyai/inference_task.py -t ocr -i /home/lpj/Desktop/yolov3_person/MOT16-11-raw.mp4 -m dbnet -m CRNN -w dbnet权重 -w CRNN权重 -s

[foww-0001]

集装箱的识别数据上传到百度云：路径在数据集/公开数据/文字识别数据/ocr_recognize_data.zip

[lpj0822]

你可以跑ocr inference @foww-0001

[kingwangxiang]

inference已调通，训练还没有调试。

[MiniBullLab]

新ocr数据上传，路径在数据集/公开数据/文字识别数据/ICDAR2015.zip

[lpj0822]

train:

python3 easyai/train_task.py -t recognize_text -i /home/lpj/dataset/ocr/ICDAR2015/ImageSets/train.txt -v /home/lpj/dataset/ocr/ICDAR2015/ImageSets/val.txt -m CRNN

[MiniBullLab]

python3 easy_tools/easy_ai.py -t OCR -i /home/lpj/dataset/ocr/ICDAR2015/ImageSets/train.txt -v /home/lpj/dataset/ocr/ICDAR2015/ImageSets/val.txt

[lpj0822]

OCR的训练脚本，下位机转换 @foww-0001

[foww-0001]

ocr合成数据上传，在百度网盘上。文件名为图片字符。 @lpj0822

[lpj0822]

TextNet.sh运行

./easy_tools/train_scripts/TextNet.sh /home/lpj/dataset/ocr/ICDAR2015/ImageSets/train.txt /home/lpj/dataset/ocr/ICDAR2015/ImageSets/val.txt

[lpj0822]

文本识别

[kingwangxiang]

结构正在修改，加入几个loss(ACEloss)，结果还在测试中。