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  1. rapidocr-ncnn/det/PP-OCRv6_small_det.bin +3 -0
  2. rapidocr-ncnn/det/PP-OCRv6_small_det.param +219 -0
  3. rapidocr-ncnn/metadata.json +15 -15
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+ Convolution convrelu_0 1 1 in0 1 0=24 1=3 11=3 12=1 13=2 14=1 2=1 3=2 4=1 5=1 6=648 9=1
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+ Split splitncnn_0 1 2 1 2 3
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+ Convolution convrelu_1 1 1 3 4 0=12 1=2 11=2 12=1 13=1 2=1 3=1 4=-233 5=1 6=1152 9=1
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+ Convolution convrelu_2 1 1 4 5 0=24 1=2 11=2 12=1 13=1 2=1 3=1 4=-233 5=1 6=1152 9=1
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+ Padding pad_41 1 1 2 6 0=0 1=1 2=0 3=1 4=0 5=-3.402823e+38 6=0
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+ Pooling maxpool2d_40 1 1 6 7 0=0 1=2 11=2 12=1 13=0 2=1 3=0 5=1
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+ Concat cat_0 2 1 7 5 8 0=0
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+ Convolution convrelu_3 1 1 8 9 0=24 1=3 11=3 12=1 13=2 14=1 2=1 3=2 4=1 5=1 6=10368 9=1
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+ Convolution convrelu_4 1 1 9 10 0=48 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=1152 9=1
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+ ConvolutionDepthWise convdw_144 1 1 10 11 0=48 1=3 11=3 12=1 13=1 14=1 2=1 3=1 4=1 5=1 6=432 7=48
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+ Split splitncnn_1 1 2 11 12 13
15
+ Reduction mean_139 1 1 13 14 0=3 1=0 -23303=2,1,2 4=1 5=1
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+ Convolution convrelu_5 1 1 14 15 0=12 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=576 9=1
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+ Convolution conv_69 1 1 15 16 0=48 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=576
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+ HardSigmoid hsigmoid_21 1 1 16 17 0=0.166667 1=0.5
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+ BinaryOp mul_0 2 1 12 17 18 0=2
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+ Split splitncnn_2 1 2 18 19 20
21
+ Convolution conv_70 1 1 20 21 0=96 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=4608
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+ GELU gelu_8 1 1 21 22
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+ Convolution conv_71 1 1 22 23 0=48 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=4608
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+ BinaryOp add_1 2 1 19 23 24 0=0
25
+ ConvolutionDepthWise convdw_145 1 1 24 25 0=48 1=3 11=3 12=1 13=1 14=1 2=1 3=1 4=1 5=1 6=432 7=48
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+ Split splitncnn_3 1 2 25 26 27
27
+ Convolution conv_72 1 1 27 28 0=96 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=4608
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+ GELU gelu_9 1 1 28 29
29
+ Convolution conv_73 1 1 29 30 0=48 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=4608
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+ BinaryOp add_2 2 1 26 30 31 0=0
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+ Split splitncnn_4 1 2 31 32 33
32
+ ConvolutionDepthWise convdw_146 1 1 33 34 0=48 1=3 11=3 12=1 13=2 14=1 2=1 3=2 4=1 5=1 6=432 7=48
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+ Convolution conv_74 1 1 34 35 0=96 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=4608
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+ GELU gelu_10 1 1 35 36
35
+ Convolution conv_75 1 1 36 37 0=96 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=9216
36
+ ConvolutionDepthWise convdw_147 1 1 37 38 0=96 1=3 11=3 12=1 13=1 14=1 2=1 3=1 4=1 5=1 6=864 7=96
37
+ Split splitncnn_5 1 2 38 39 40
38
+ Reduction mean_140 1 1 40 41 0=3 1=0 -23303=2,1,2 4=1 5=1
39
+ Convolution convrelu_6 1 1 41 42 0=24 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=2304 9=1
40
+ Convolution conv_77 1 1 42 43 0=96 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=2304
41
+ HardSigmoid hsigmoid_22 1 1 43 44 0=0.166667 1=0.5
42
+ BinaryOp mul_3 2 1 39 44 45 0=2
43
+ Split splitncnn_6 1 2 45 46 47
44
+ Convolution conv_78 1 1 47 48 0=192 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=18432
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+ GELU gelu_11 1 1 48 49
46
+ Convolution conv_79 1 1 49 50 0=96 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=18432
47
+ BinaryOp add_4 2 1 46 50 51 0=0
48
+ ConvolutionDepthWise convdw_148 1 1 51 52 0=96 1=3 11=3 12=1 13=1 14=1 2=1 3=1 4=1 5=1 6=864 7=96
49
+ Split splitncnn_7 1 2 52 53 54
50
+ Convolution conv_80 1 1 54 55 0=192 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=18432
51
+ GELU gelu_12 1 1 55 56
52
+ Convolution conv_81 1 1 56 57 0=96 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=18432
53
+ BinaryOp add_5 2 1 53 57 58 0=0
54
+ Split splitncnn_8 1 2 58 59 60
55
+ ConvolutionDepthWise convdw_149 1 1 60 61 0=96 1=3 11=3 12=1 13=2 14=1 2=1 3=2 4=1 5=1 6=864 7=96
56
+ Convolution conv_82 1 1 61 62 0=192 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=18432
57
+ GELU gelu_13 1 1 62 63
58
+ Convolution conv_83 1 1 63 64 0=192 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=36864
59
+ ConvolutionDepthWise convdw_150 1 1 64 65 0=192 1=3 11=3 12=1 13=1 14=1 2=1 3=1 4=1 5=1 6=1728 7=192
60
+ Split splitncnn_9 1 2 65 66 67
61
+ Reduction mean_141 1 1 67 68 0=3 1=0 -23303=2,1,2 4=1 5=1
62
+ Convolution convrelu_7 1 1 68 69 0=48 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=9216 9=1
63
+ Convolution conv_85 1 1 69 70 0=192 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=9216
64
+ HardSigmoid hsigmoid_23 1 1 70 71 0=0.166667 1=0.5
65
+ BinaryOp mul_6 2 1 66 71 72 0=2
66
+ Split splitncnn_10 1 2 72 73 74
67
+ Convolution conv_86 1 1 74 75 0=384 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=73728
68
+ GELU gelu_14 1 1 75 76
69
+ Convolution conv_87 1 1 76 77 0=192 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=73728
70
+ BinaryOp add_7 2 1 73 77 78 0=0
71
+ ConvolutionDepthWise convdw_151 1 1 78 79 0=192 1=3 11=3 12=1 13=1 14=1 2=1 3=1 4=1 5=1 6=1728 7=192
72
+ Split splitncnn_11 1 2 79 80 81
73
+ Convolution conv_88 1 1 81 82 0=384 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=73728
74
+ GELU gelu_15 1 1 82 83
75
+ Convolution conv_89 1 1 83 84 0=192 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=73728
76
+ BinaryOp add_8 2 1 80 84 85 0=0
77
+ ConvolutionDepthWise convdw_152 1 1 85 86 0=192 1=3 11=3 12=1 13=1 14=1 2=1 3=1 4=1 5=1 6=1728 7=192
78
+ Split splitncnn_12 1 2 86 87 88
79
+ Reduction mean_142 1 1 88 89 0=3 1=0 -23303=2,1,2 4=1 5=1
80
+ Convolution convrelu_8 1 1 89 90 0=48 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=9216 9=1
81
+ Convolution conv_91 1 1 90 91 0=192 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=9216
82
+ HardSigmoid hsigmoid_24 1 1 91 92 0=0.166667 1=0.5
83
+ BinaryOp mul_9 2 1 87 92 93 0=2
84
+ Split splitncnn_13 1 2 93 94 95
85
+ Convolution conv_92 1 1 95 96 0=384 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=73728
86
+ GELU gelu_16 1 1 96 97
87
+ Convolution conv_93 1 1 97 98 0=192 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=73728
88
+ BinaryOp add_10 2 1 94 98 99 0=0
89
+ ConvolutionDepthWise convdw_153 1 1 99 100 0=192 1=3 11=3 12=1 13=1 14=1 2=1 3=1 4=1 5=1 6=1728 7=192
90
+ Split splitncnn_14 1 2 100 101 102
91
+ Convolution conv_94 1 1 102 103 0=384 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=73728
92
+ GELU gelu_17 1 1 103 104
93
+ Convolution conv_95 1 1 104 105 0=192 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=73728
94
+ BinaryOp add_11 2 1 101 105 106 0=0
95
+ Split splitncnn_15 1 2 106 107 108
96
+ ConvolutionDepthWise convdw_154 1 1 108 109 0=192 1=3 11=3 12=1 13=2 14=1 2=1 3=2 4=1 5=1 6=1728 7=192
97
+ Convolution conv_96 1 1 109 110 0=384 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=73728
98
+ GELU gelu_18 1 1 110 111
99
+ Convolution conv_97 1 1 111 112 0=384 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=147456
100
+ ConvolutionDepthWise convdw_155 1 1 112 113 0=384 1=3 11=3 12=1 13=1 14=1 2=1 3=1 4=1 5=1 6=3456 7=384
101
+ Split splitncnn_16 1 2 113 114 115
102
+ Reduction mean_143 1 1 115 116 0=3 1=0 -23303=2,1,2 4=1 5=1
103
+ Convolution convrelu_9 1 1 116 117 0=96 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=36864 9=1
104
+ Convolution conv_99 1 1 117 118 0=384 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=36864
105
+ HardSigmoid hsigmoid_25 1 1 118 119 0=0.166667 1=0.5
106
+ BinaryOp mul_12 2 1 114 119 120 0=2
107
+ Split splitncnn_17 1 2 120 121 122
108
+ Convolution conv_100 1 1 122 123 0=768 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=294912
109
+ GELU gelu_19 1 1 123 124
110
+ Convolution conv_101 1 1 124 125 0=384 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=294912
111
+ BinaryOp add_13 2 1 121 125 126 0=0
112
+ ConvolutionDepthWise convdw_156 1 1 126 127 0=384 1=3 11=3 12=1 13=1 14=1 2=1 3=1 4=1 5=1 6=3456 7=384
113
+ Split splitncnn_18 1 2 127 128 129
114
+ Convolution conv_102 1 1 129 130 0=768 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=294912
115
+ GELU gelu_20 1 1 130 131
116
+ Convolution conv_103 1 1 131 132 0=384 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=294912
117
+ BinaryOp add_14 2 1 128 132 133 0=0
118
+ Convolution conv_104 1 1 133 134 0=96 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=0 6=36864
119
+ Split splitncnn_19 1 3 134 135 136 137
120
+ Pooling gap_0 1 1 137 138 0=1 4=1
121
+ Convolution convrelu_10 1 1 138 139 0=24 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=2304 9=1
122
+ Convolution conv_106 1 1 139 140 0=96 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=2304
123
+ Reshape reshape_131 1 1 140 141 0=1 1=1 2=-1
124
+ BinaryOp mul_15 1 1 141 142 0=2 1=1 2=1.2
125
+ HardSigmoid hsigmoid_26 1 1 142 143 0=0.166667 1=0.5
126
+ BinaryOp mul_16 2 1 135 143 144 0=2
127
+ BinaryOp add_17 2 1 136 144 145 0=0
128
+ Split splitncnn_20 1 2 145 146 147
129
+ Convolution conv_107 1 1 107 148 0=96 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=0 6=18432
130
+ Split splitncnn_21 1 3 148 149 150 151
131
+ Pooling gap_1 1 1 151 152 0=1 4=1
132
+ Convolution convrelu_11 1 1 152 153 0=24 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=2304 9=1
133
+ Convolution conv_109 1 1 153 154 0=96 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=2304
134
+ Reshape reshape_132 1 1 154 155 0=1 1=1 2=-1
135
+ BinaryOp mul_18 1 1 155 156 0=2 1=1 2=1.2
136
+ HardSigmoid hsigmoid_27 1 1 156 157 0=0.166667 1=0.5
137
+ Convolution conv_110 1 1 59 158 0=96 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=0 6=9216
138
+ Split splitncnn_22 1 3 158 159 160 161
139
+ Pooling gap_2 1 1 161 162 0=1 4=1
140
+ Convolution convrelu_12 1 1 162 163 0=24 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=2304 9=1
141
+ Convolution conv_112 1 1 163 164 0=96 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=2304
142
+ Reshape reshape_133 1 1 164 165 0=1 1=1 2=-1
143
+ BinaryOp mul_19 1 1 165 166 0=2 1=1 2=1.2
144
+ HardSigmoid hsigmoid_28 1 1 166 167 0=0.166667 1=0.5
145
+ Convolution conv_113 1 1 32 168 0=96 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=0 6=4608
146
+ Split splitncnn_23 1 3 168 169 170 171
147
+ Pooling gap_3 1 1 171 172 0=1 4=1
148
+ Convolution convrelu_13 1 1 172 173 0=24 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=2304 9=1
149
+ Convolution conv_115 1 1 173 174 0=96 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=2304
150
+ Reshape reshape_134 1 1 174 175 0=1 1=1 2=-1
151
+ BinaryOp mul_20 1 1 175 176 0=2 1=1 2=1.2
152
+ HardSigmoid hsigmoid_29 1 1 176 177 0=0.166667 1=0.5
153
+ Interp interpolate_34 1 1 146 178 0=1 1=2.0 2=2.0 6=0
154
+ BinaryOp mul_21 2 1 149 157 179 0=2
155
+ BinaryOp add_22 2 1 150 179 180 0=0
156
+ BinaryOp add_23 2 1 180 178 181 0=0
157
+ Split splitncnn_24 1 2 181 182 183
158
+ Interp interpolate_35 1 1 182 184 0=1 1=2.0 2=2.0 6=0
159
+ BinaryOp mul_24 2 1 159 167 185 0=2
160
+ BinaryOp add_25 2 1 160 185 186 0=0
161
+ BinaryOp add_26 2 1 186 184 187 0=0
162
+ Split splitncnn_25 1 2 187 188 189
163
+ Interp interpolate_36 1 1 188 190 0=1 1=2.0 2=2.0 6=0
164
+ BinaryOp mul_27 2 1 169 177 191 0=2
165
+ BinaryOp add_28 2 1 170 191 192 0=0
166
+ BinaryOp add_29 2 1 192 190 193 0=0
167
+ ConvolutionDepthWise convdw_157 1 1 147 194 0=96 1=7 11=7 12=1 13=1 14=3 2=1 3=1 4=3 5=1 6=4704 7=96
168
+ Convolution conv_116 1 1 194 195 0=24 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=0 6=2304
169
+ Split splitncnn_26 1 3 195 196 197 198
170
+ Pooling gap_4 1 1 198 199 0=1 4=1
171
+ Convolution convrelu_14 1 1 199 200 0=6 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=144 9=1
172
+ Convolution conv_118 1 1 200 201 0=24 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=144
173
+ Reshape reshape_135 1 1 201 202 0=1 1=1 2=-1
174
+ BinaryOp mul_30 1 1 202 203 0=2 1=1 2=1.2
175
+ HardSigmoid hsigmoid_30 1 1 203 204 0=0.166667 1=0.5
176
+ BinaryOp mul_31 2 1 196 204 205 0=2
177
+ BinaryOp add_32 2 1 197 205 206 0=0
178
+ ConvolutionDepthWise convdw_158 1 1 183 207 0=96 1=7 11=7 12=1 13=1 14=3 2=1 3=1 4=3 5=1 6=4704 7=96
179
+ Convolution conv_119 1 1 207 208 0=24 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=0 6=2304
180
+ Split splitncnn_27 1 3 208 209 210 211
181
+ Pooling gap_5 1 1 211 212 0=1 4=1
182
+ Convolution convrelu_15 1 1 212 213 0=6 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=144 9=1
183
+ Convolution conv_121 1 1 213 214 0=24 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=144
184
+ Reshape reshape_136 1 1 214 215 0=1 1=1 2=-1
185
+ BinaryOp mul_33 1 1 215 216 0=2 1=1 2=1.2
186
+ HardSigmoid hsigmoid_31 1 1 216 217 0=0.166667 1=0.5
187
+ BinaryOp mul_34 2 1 209 217 218 0=2
188
+ BinaryOp add_35 2 1 210 218 219 0=0
189
+ ConvolutionDepthWise convdw_159 1 1 189 220 0=96 1=7 11=7 12=1 13=1 14=3 2=1 3=1 4=3 5=1 6=4704 7=96
190
+ Convolution conv_122 1 1 220 221 0=24 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=0 6=2304
191
+ Split splitncnn_28 1 3 221 222 223 224
192
+ Pooling gap_6 1 1 224 225 0=1 4=1
193
+ Convolution convrelu_16 1 1 225 226 0=6 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=144 9=1
194
+ Convolution conv_124 1 1 226 227 0=24 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=144
195
+ Reshape reshape_137 1 1 227 228 0=1 1=1 2=-1
196
+ BinaryOp mul_36 1 1 228 229 0=2 1=1 2=1.2
197
+ HardSigmoid hsigmoid_32 1 1 229 230 0=0.166667 1=0.5
198
+ BinaryOp mul_37 2 1 222 230 231 0=2
199
+ BinaryOp add_38 2 1 223 231 232 0=0
200
+ ConvolutionDepthWise convdw_160 1 1 193 233 0=96 1=7 11=7 12=1 13=1 14=3 2=1 3=1 4=3 5=1 6=4704 7=96
201
+ Convolution conv_125 1 1 233 234 0=24 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=0 6=2304
202
+ Split splitncnn_29 1 3 234 235 236 237
203
+ Pooling gap_7 1 1 237 238 0=1 4=1
204
+ Convolution convrelu_17 1 1 238 239 0=6 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=144 9=1
205
+ Convolution conv_127 1 1 239 240 0=24 1=1 11=1 12=1 13=1 14=0 2=1 3=1 4=0 5=1 6=144
206
+ Reshape reshape_138 1 1 240 241 0=1 1=1 2=-1
207
+ BinaryOp mul_39 1 1 241 242 0=2 1=1 2=1.2
208
+ HardSigmoid hsigmoid_33 1 1 242 243 0=0.166667 1=0.5
209
+ BinaryOp mul_40 2 1 235 243 244 0=2
210
+ BinaryOp add_41 2 1 236 244 245 0=0
211
+ Interp interpolate_37 1 1 206 246 0=1 1=8.0 2=8.0 6=0
212
+ Interp interpolate_38 1 1 219 247 0=1 1=4.0 2=4.0 6=0
213
+ Interp interpolate_39 1 1 232 248 0=1 1=2.0 2=2.0 6=0
214
+ Concat cat_1 4 1 246 247 248 245 249 0=0
215
+ Convolution convrelu_18 1 1 249 250 0=24 1=3 11=3 12=1 13=1 14=1 2=1 3=1 4=1 5=1 6=20736 9=1
216
+ Deconvolution deconvrelu_0 1 1 250 251 0=24 1=2 11=2 12=1 13=2 14=0 18=0 19=0 2=1 3=2 4=0 5=1 6=2304 9=1
217
+ Deconvolution deconv_130 1 1 251 252 0=1 1=2 11=2 12=1 13=2 14=0 18=0 19=0 2=1 3=2 4=0 5=0 6=96
218
+ BinaryOp add_42 1 1 252 253 0=0 1=1 2=0.201487
219
+ Sigmoid sigmoid_62 1 1 253 out0
rapidocr-ncnn/metadata.json CHANGED
@@ -2,7 +2,7 @@
2
  "bundle_id": "rapidocr-ncnn",
3
  "model_class": "ocr",
4
  "provider": "RapidAI",
5
- "upstream_id": "RapidAI/RapidOcrNcnn@1.2.0",
6
  "upstream_commit": "d3602107871929529db9dceb26445e642111a13b",
7
  "task": "ocr",
8
  "format": "ncnn",
@@ -11,9 +11,9 @@
11
  "vulkan_version": "1.3.236.0",
12
  "pipeline": {
13
  "det": {
14
- "model": "ch_PP-OCRv3_det_infer",
15
- "param": "det/ch_PP-OCRv3_det_infer.param",
16
- "bin": "det/ch_PP-OCRv3_det_infer.bin"
17
  },
18
  "cls": {
19
  "model": "ch_ppocr_mobile_v2.0_cls_infer",
@@ -64,14 +64,6 @@
64
  "sha256": "207a50228e6ecba8d6bd4df4259770547f43099a04978315fb4baa8d547c63b5",
65
  "size": 17072
66
  },
67
- "det/ch_PP-OCRv3_det_infer.bin": {
68
- "sha256": "9c233d604bbb4a6e6fc1db34d3890cf5eb4de8d71167072d1ec0fc3691c665f7",
69
- "size": 2296300
70
- },
71
- "det/ch_PP-OCRv3_det_infer.param": {
72
- "sha256": "2e4701d9c9fa6aa1864067683e8357991496459234c7ea73b253d8e5fcc121c6",
73
- "size": 24254
74
- },
75
  "keys/ppocr_keys_v1.txt": {
76
  "sha256": "28b2362ad4ab2dc38769aa72feb535e3a9ddb3fd2a7585a05920e6393b1dc7f7",
77
  "size": 26249
@@ -83,11 +75,19 @@
83
  "rec/ch_PP-OCRv3_rec_infer.param": {
84
  "sha256": "4158faa4fa1a5c60d1c8ff510765a52c77abf77aeda6c1608f2ba08d3542704e",
85
  "size": 13793
 
 
 
 
 
 
 
 
86
  }
87
  },
88
  "notes": [
89
- "Official RapidOcrNcnn 1.2.0 NCNN release bundle includes PP-OCRv3 Chinese-English OCR models only.",
90
- "RapidOCR v3 documents additional multilingual PP-OCRv4/PP-OCRv5 models, but those are currently published by RapidAI as ONNX/MNN/Paddle/Torch rather than RapidOcrNcnn NCNN artifacts.",
91
- "ZimaOS Photos default OCR backend uses RapidOCR NCNN directly; Tesseract is not part of the default OCR path."
92
  ]
93
  }
 
2
  "bundle_id": "rapidocr-ncnn",
3
  "model_class": "ocr",
4
  "provider": "RapidAI",
5
+ "upstream_id": "RapidAI/RapidOcrNcnn@1.2.0+PP-OCRv6-small-det",
6
  "upstream_commit": "d3602107871929529db9dceb26445e642111a13b",
7
  "task": "ocr",
8
  "format": "ncnn",
 
11
  "vulkan_version": "1.3.236.0",
12
  "pipeline": {
13
  "det": {
14
+ "model": "PP-OCRv6_small_det",
15
+ "param": "det/PP-OCRv6_small_det.param",
16
+ "bin": "det/PP-OCRv6_small_det.bin"
17
  },
18
  "cls": {
19
  "model": "ch_ppocr_mobile_v2.0_cls_infer",
 
64
  "sha256": "207a50228e6ecba8d6bd4df4259770547f43099a04978315fb4baa8d547c63b5",
65
  "size": 17072
66
  },
 
 
 
 
 
 
 
 
67
  "keys/ppocr_keys_v1.txt": {
68
  "sha256": "28b2362ad4ab2dc38769aa72feb535e3a9ddb3fd2a7585a05920e6393b1dc7f7",
69
  "size": 26249
 
75
  "rec/ch_PP-OCRv3_rec_infer.param": {
76
  "sha256": "4158faa4fa1a5c60d1c8ff510765a52c77abf77aeda6c1608f2ba08d3542704e",
77
  "size": 13793
78
+ },
79
+ "det/PP-OCRv6_small_det.param": {
80
+ "sha256": "9016c47f7a26df0a8d1e3a01aa3ccb5a0bbebcf965bd2229006e413d7245ef95",
81
+ "size": 18831
82
+ },
83
+ "det/PP-OCRv6_small_det.bin": {
84
+ "sha256": "5b4317b0fcebd70a4ab957a36115498447a8f6fe57b45594c523234a8edb4c4c",
85
+ "size": 4852431
86
  }
87
  },
88
  "notes": [
89
+ "Runtime remains RapidOcrNcnn 1.2.0, but the detection stage is upgraded to a locally converted PP-OCRv6 small det NCNN model.",
90
+ "Classification and recognition remain on the existing PP-OCRv3 Chinese-English NCNN artifacts for compatibility with the current Photos OCR pipeline.",
91
+ "The PP-OCRv6 small det NCNN artifacts were converted locally from the official PaddlePaddle PP-OCRv6_small_det_onnx release."
92
  ]
93
  }