├── .gitignore
├── LICENSE
├── README.md
├── doc
    ├── .ipynb_checkpoints
    │   ├── jiyan_gt_challenge_demo-checkpoint.ipynb
    │   └── 在Python中使用模型-checkpoint.ipynb
    ├── Ubuntu18.04 install darknet yolo-v3|cuda|cudnn|opencv|anaconda.md
    ├── classifier_train_handbook.md
    ├── detector_train_handbook.md
    ├── jiyan_gt_challenge.md
    ├── jiyan_gt_challenge_demo.ipynb
    ├── 九宫格图片验证码训练集.md
    └── 在Python中使用模型.ipynb
├── hanzi_detection
    ├── .gitignore
    ├── LICENSE
    ├── LICENSE.fuck
    ├── LICENSE.gen
    ├── LICENSE.gpl
    ├── LICENSE.meta
    ├── LICENSE.mit
    ├── LICENSE.v1
    ├── Makefile
    ├── README.md
    ├── examples
    │   ├── art.c
    │   ├── attention.c
    │   ├── captcha.c
    │   ├── cifar.c
    │   ├── classifier.c
    │   ├── coco.c
    │   ├── darknet.c
    │   ├── detector-scipy-opencv.py
    │   ├── detector.c
    │   ├── detector.py
    │   ├── dice.c
    │   ├── go.c
    │   ├── instance-segmenter.c
    │   ├── lsd.c
    │   ├── nightmare.c
    │   ├── regressor.c
    │   ├── rnn.c
    │   ├── rnn_vid.c
    │   ├── segmenter.c
    │   ├── super.c
    │   ├── swag.c
    │   ├── tag.c
    │   ├── voxel.c
    │   ├── writing.c
    │   └── yolo.c
    ├── files
    │   ├── train
    │   │   └── jiyan_train_imgs_txt_1K
    │   │   │   ├── 0015673f726b2a1ddd43c1758553093b.txt
    │   │   │   ├── 0030fbc156e567a2c34afe4495318e16.txt
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    │   │   │   ├── fdd51b44cf3ddf8dc6a77b9bfc19ca1c.txt
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    │   │   │   └── ffeb17610b24a45fbb9c9b687caa4d56.txt
    │   └── valid
    │   │   └── jiyan_valid_imgs_txt_500
    │   │       ├── 009a7e97021d97dae6673b80f5562419.txt
    │   │       ├── 00d85d76fffde2afbb5662ec32d4e6e3.txt
    │   │       ├── 0109defc816d4d3f9ebec520758101ed.txt
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    │   │       ├── 0140db605724c01ba5142cbc218cfe25.txt
    │   │       ├── 01c7ed9c137d1361d3cbc3425457119d.txt
    │   │       ├── 01e020b4086fd8ecb300e61150e66444.txt
    │   │       ├── 02f204657e32d9898613c0cb56cb5f19.txt
    │   │       ├── 0304f393f7eb69101ddab817824ce675.txt
    │   │       ├── 03256b23586b52f75fd89c48169c2580.txt
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    │   │       ├── 080ba59085ef88048ec8415d3eaf742a.txt
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    │   │       ├── 27edc29c28067e0c199215b30c046517.txt
    │   │       ├── 29a82a5f398c44c717e5963b8aa18ce0.txt
    │   │       ├── 2a27d33108c135b78005316e25b7344b.txt
    │   │       ├── 2a37dff08e425c14579ca4ecb232122b.txt
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    │   │       ├── 2cd54245fbc81730d1697b2224ba4795.txt
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    │   │       ├── 2f63ed89bae4f75af1bf58e85899a462.txt
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    │   │       ├── 31b28e3fd6a231d6382367606843f088.txt
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    │   │       ├── 326dc5fc5b0a058a96c3690141849192.txt
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    │   │       └── ff9f936e5f3dd45ab09465d39d379763.txt
    ├── include
    │   └── darknet.h
    ├── libdarknet.so
    ├── model
    │   ├── jiyan_classify.cfg
    │   └── jiyan_yolov3.cfg
    ├── python
    │   ├── darknet.py
    │   └── proverbot.py
    ├── readme_classify.md
    ├── scripts
    │   ├── dice_label.sh
    │   ├── gen_tactic.sh
    │   ├── get_coco_dataset.sh
    │   ├── imagenet_label.sh
    │   └── voc_label.py
    └── src
    │   ├── activation_kernels.cu
    │   ├── activation_layer.c
    │   ├── activation_layer.h
    │   ├── activations.c
    │   ├── activations.h
    │   ├── avgpool_layer.c
    │   ├── avgpool_layer.h
    │   ├── avgpool_layer_kernels.cu
    │   ├── batchnorm_layer.c
    │   ├── batchnorm_layer.h
    │   ├── blas.c
    │   ├── blas.h
    │   ├── blas_kernels.cu
    │   ├── box.c
    │   ├── box.h
    │   ├── classifier.h
    │   ├── col2im.c
    │   ├── col2im.h
    │   ├── col2im_kernels.cu
    │   ├── compare.c
    │   ├── connected_layer.c
    │   ├── connected_layer.h
    │   ├── convolutional_kernels.cu
    │   ├── convolutional_layer.c
    │   ├── convolutional_layer.h
    │   ├── cost_layer.c
    │   ├── cost_layer.h
    │   ├── crnn_layer.c
    │   ├── crnn_layer.h
    │   ├── crop_layer.c
    │   ├── crop_layer.h
    │   ├── crop_layer_kernels.cu
    │   ├── cuda.c
    │   ├── cuda.h
    │   ├── data.c
    │   ├── data.h
    │   ├── deconvolutional_kernels.cu
    │   ├── deconvolutional_layer.c
    │   ├── deconvolutional_layer.h
    │   ├── demo.c
    │   ├── demo.h
    │   ├── detection_layer.c
    │   ├── detection_layer.h
    │   ├── dropout_layer.c
    │   ├── dropout_layer.h
    │   ├── dropout_layer_kernels.cu
    │   ├── gemm.c
    │   ├── gemm.h
    │   ├── gru_layer.c
    │   ├── gru_layer.h
    │   ├── im2col.c
    │   ├── im2col.h
    │   ├── im2col_kernels.cu
    │   ├── image.c
    │   ├── image.h
    │   ├── image_opencv.cpp
    │   ├── iseg_layer.c
    │   ├── iseg_layer.h
    │   ├── l2norm_layer.c
    │   ├── l2norm_layer.h
    │   ├── layer.c
    │   ├── layer.h
    │   ├── list.c
    │   ├── list.h
    │   ├── local_layer.c
    │   ├── local_layer.h
    │   ├── logistic_layer.c
    │   ├── logistic_layer.h
    │   ├── lstm_layer.c
    │   ├── lstm_layer.h
    │   ├── matrix.c
    │   ├── matrix.h
    │   ├── maxpool_layer.c
    │   ├── maxpool_layer.h
    │   ├── maxpool_layer_kernels.cu
    │   ├── network.c
    │   ├── network.h
    │   ├── normalization_layer.c
    │   ├── normalization_layer.h
    │   ├── option_list.c
    │   ├── option_list.h
    │   ├── parser.c
    │   ├── parser.h
    │   ├── region_layer.c
    │   ├── region_layer.h
    │   ├── reorg_layer.c
    │   ├── reorg_layer.h
    │   ├── rnn_layer.c
    │   ├── rnn_layer.h
    │   ├── route_layer.c
    │   ├── route_layer.h
    │   ├── shortcut_layer.c
    │   ├── shortcut_layer.h
    │   ├── softmax_layer.c
    │   ├── softmax_layer.h
    │   ├── stb_image.h
    │   ├── stb_image_write.h
    │   ├── tree.c
    │   ├── tree.h
    │   ├── upsample_layer.c
    │   ├── upsample_layer.h
    │   ├── utils.c
    │   ├── utils.h
    │   ├── yolo_layer.c
    │   └── yolo_layer.h
└── media
    ├── 0b7bbb3595309f7f9123704ef354a52d旅_u65c5.jpg
    ├── 1590951689.png
    ├── ab9a8dcdda85f1d8789909803374fbea.jpg
    ├── e697bc6aa912eeb2610998833f209242.jpg
    ├── geet_demo.jpg
    ├── yidun_demo.jpg
    └── 阿_1cde28c6abce11eab97c0242ac110002.jpg


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1 | 0 0.7906976744186046 0.2786458333333333 0.20348837209302326 0.15625
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1 | 0 0.7848837209302325 0.5234375 0.20348837209302326 0.15625
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1 | 0 0.8517441860465116 0.36197916666666663 0.20348837209302326 0.15625
2 | 0 0.2965116279069767 0.5052083333333333 0.20348837209302326 0.15625
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1 | 0 0.5901162790697674 0.6119791666666666 0.20348837209302326 0.15625
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1 | 0 0.747093023255814 0.17708333333333331 0.20348837209302326 0.15625
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/hanzi_detection/files/valid/jiyan_valid_imgs_txt_500/f7da67a66d65dbe721d9359a064ab5cc.txt:
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1 | 0 0.7994186046511628 0.1171875 0.20348837209302326 0.15625
2 | 0 0.3488372093023256 0.6901041666666666 0.20348837209302326 0.15625
3 | 0 0.15406976744186046 0.1875 0.20348837209302326 0.15625
4 | 0 0.8023255813953488 0.359375 0.20348837209302326 0.15625
5 | 


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/hanzi_detection/files/valid/jiyan_valid_imgs_txt_500/ff9f936e5f3dd45ab09465d39d379763.txt:
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1 | 0 0.6075581395348837 0.765625 0.20348837209302326 0.15625
2 | 0 0.6686046511627907 0.40625 0.20348837209302326 0.15625
3 | 0 0.15406976744186046 0.4114583333333333 0.20348837209302326 0.15625
4 | 0 0.21511627906976744 0.65625 0.20348837209302326 0.15625
5 | 


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/hanzi_detection/libdarknet.so:
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https://raw.githubusercontent.com/WebSpiderUtils/verification_code/3aa35c8a1868e0c2898a2b000cadb77476ece0dc/hanzi_detection/libdarknet.so


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/hanzi_detection/scripts/gen_tactic.sh:
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1 | #!/bin/bash
2 | # Usage:
3 | # wget http://pjreddie.com/media/files/peek.weights
4 | # scripts/gen_tactic.sh < data/goal.txt
5 | ./darknet rnn generatetactic cfg/gru.cfg peek.weights 2>/dev/null
6 | 


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/hanzi_detection/src/box.h:
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 1 | #ifndef BOX_H
 2 | #define BOX_H
 3 | #include "darknet.h"
 4 | 
 5 | typedef struct{
 6 |     float dx, dy, dw, dh;
 7 | } dbox;
 8 | 
 9 | float box_rmse(box a, box b);
10 | dbox diou(box a, box b);
11 | box decode_box(box b, box anchor);
12 | box encode_box(box b, box anchor);
13 | 
14 | #endif
15 | 


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/hanzi_detection/src/classifier.h:
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1 | 
2 | 


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/hanzi_detection/src/demo.h:
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1 | #ifndef DEMO_H
2 | #define DEMO_H
3 | 
4 | #include "image.h"
5 | 
6 | #endif
7 | 


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/hanzi_detection/src/layer.h:
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1 | #include "darknet.h"
2 | 


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/hanzi_detection/src/list.h:
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 1 | #ifndef LIST_H
 2 | #define LIST_H
 3 | #include "darknet.h"
 4 | 
 5 | list *make_list();
 6 | int list_find(list *l, void *val);
 7 | 
 8 | void list_insert(list *, void *);
 9 | 
10 | 
11 | void free_list_contents(list *l);
12 | 
13 | #endif
14 | 


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/hanzi_detection/src/matrix.h:
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 1 | #ifndef MATRIX_H
 2 | #define MATRIX_H
 3 | #include "darknet.h"
 4 | 
 5 | matrix copy_matrix(matrix m);
 6 | void print_matrix(matrix m);
 7 | 
 8 | matrix hold_out_matrix(matrix *m, int n);
 9 | matrix resize_matrix(matrix m, int size);
10 | 
11 | float *pop_column(matrix *m, int c);
12 | 
13 | #endif
14 | 


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/hanzi_detection/src/parser.h:
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 1 | #ifndef PARSER_H
 2 | #define PARSER_H
 3 | #include "darknet.h"
 4 | #include "network.h"
 5 | 
 6 | void save_network(network net, char *filename);
 7 | void save_weights_double(network net, char *filename);
 8 | 
 9 | #endif
10 | 


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/hanzi_detection/src/tree.h:
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1 | #ifndef TREE_H
2 | #define TREE_H
3 | #include "darknet.h"
4 | 
5 | int hierarchy_top_prediction(float *predictions, tree *hier, float thresh, int stride);
6 | float get_hierarchy_probability(float *x, tree *hier, int c, int stride);
7 | 
8 | #endif
9 | 


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/media/0b7bbb3595309f7f9123704ef354a52d旅_u65c5.jpg:
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/media/1590951689.png:
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/media/e697bc6aa912eeb2610998833f209242.jpg:
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/media/geet_demo.jpg:
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https://raw.githubusercontent.com/WebSpiderUtils/verification_code/3aa35c8a1868e0c2898a2b000cadb77476ece0dc/media/geet_demo.jpg


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/media/yidun_demo.jpg:
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https://raw.githubusercontent.com/WebSpiderUtils/verification_code/3aa35c8a1868e0c2898a2b000cadb77476ece0dc/media/yidun_demo.jpg


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