郑启航

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official code use `selective_adacolor` superpixel method training 15999 steps results: ![15999_face_photo](https://user-images.githubusercontent.com/26156999/98946281-a7de0200-252e-11eb-81e8-0e2c9dd3995e.jpg) ![15999_face_result](https://user-images.githubusercontent.com/26156999/98946288-aa405c00-252e-11eb-804b-958e039df0c8.jpg) ![15999_scenery_photo](https://user-images.githubusercontent.com/26156999/98946313-b2000080-252e-11eb-8877-3187c727752b.jpg) ![15999_scenery_result](https://user-images.githubusercontent.com/26156999/98946321-b3c9c400-252e-11eb-9a40-79307874c6e0.jpg)

|test images|official code|pytorch version| |--|--|--| |![actress2](https://user-images.githubusercontent.com/26156999/99029488-8c660c00-25ad-11eb-8440-3245a44a9d76.jpg)|![actress2](https://user-images.githubusercontent.com/26156999/99029726-2928a980-25ae-11eb-8575-69985d89b1e5.jpg)|![actress2_out](https://user-images.githubusercontent.com/26156999/99029955-d3083600-25ae-11eb-9290-d67b7b386f7a.jpg)| |![china6](https://user-images.githubusercontent.com/26156999/99029533-abfd3480-25ad-11eb-98c4-f249b2addd7b.jpg)|![china6](https://user-images.githubusercontent.com/26156999/99029762-4f4e4980-25ae-11eb-9f45-6bee3c58f1c7.jpg)|![china6_out](https://user-images.githubusercontent.com/26156999/99029968-d996ad80-25ae-11eb-92b0-837080304aee.jpg)| |![food6](https://user-images.githubusercontent.com/26156999/99029545-b3244280-25ad-11eb-98e4-dd352debbeef.jpg)|![food6](https://user-images.githubusercontent.com/26156999/99029769-55dcc100-25ae-11eb-8061-e24ad3a40f60.jpg)|![food6_out](https://user-images.githubusercontent.com/26156999/99029976-def3f800-25ae-11eb-843b-b078534da1b3.jpg)| |![food16](https://user-images.githubusercontent.com/26156999/99029560-bdded780-25ad-11eb-9914-d2ad933c735d.jpg)|![food16](https://user-images.githubusercontent.com/26156999/99029790-5f662900-25ae-11eb-99dc-a1a216b17c5c.jpg)|![food16_out](https://user-images.githubusercontent.com/26156999/99029992-e7e4c980-25ae-11eb-86fb-8c2a1ff0fca5.jpg)| |![liuyifei4](https://user-images.githubusercontent.com/26156999/99029574-c505e580-25ad-11eb-8cf2-6d539775821d.jpg)|![liuyifei4](https://user-images.githubusercontent.com/26156999/99029807-69882780-25ae-11eb-8db2-6c5b8019053c.jpg)|![liuyifei4_out](https://user-images.githubusercontent.com/26156999/99029999-ed421400-25ae-11eb-97a9-c547ba80221a.jpg)| |![london1](https://user-images.githubusercontent.com/26156999/99029662-00081900-25ae-11eb-9a13-148293575cfc.jpg)|![london1](https://user-images.githubusercontent.com/26156999/99029816-70169f00-25ae-11eb-832e-e5cd40ffd260.jpg)|![london1_out](https://user-images.githubusercontent.com/26156999/99030014-f6cb7c00-25ae-11eb-9de6-61afd6a7c146.jpg)| |![mountain4](https://user-images.githubusercontent.com/26156999/99029665-01d1dc80-25ae-11eb-9d1a-50e642e1ffa2.jpg)|![mountain4](https://user-images.githubusercontent.com/26156999/99029821-760c8000-25ae-11eb-9306-35a71f729787.jpg)|![mountain4_out](https://user-images.githubusercontent.com/26156999/99030023-faf79980-25ae-11eb-86f8-1686b1066de0.jpg)| |![mountain5](https://user-images.githubusercontent.com/26156999/99029669-04343680-25ae-11eb-81ec-f43ef41d4b73.jpg)|![mountain5](https://user-images.githubusercontent.com/26156999/99029846-815fab80-25ae-11eb-9928-d7698d72d47b.jpg)|![mountain5_out](https://user-images.githubusercontent.com/26156999/99030034-02b73e00-25af-11eb-8e2c-6701207872cb.jpg)| |![national_park1](https://user-images.githubusercontent.com/26156999/99029672-05fdfa00-25ae-11eb-9826-c893204518e1.jpg)|![national_park1](https://user-images.githubusercontent.com/26156999/99029853-86245f80-25ae-11eb-9f22-ebbf667124b8.jpg)|![national_park1_out](https://user-images.githubusercontent.com/26156999/99030050-0a76e280-25af-11eb-962e-fcfa8f498fde.jpg)| |![party5](https://user-images.githubusercontent.com/26156999/99029675-072f2700-25ae-11eb-99f7-12a6e3eb37a0.jpg)|![party5](https://user-images.githubusercontent.com/26156999/99029864-94727b80-25ae-11eb-866d-1cc251a93ff7.jpg)|![party5_out](https://user-images.githubusercontent.com/26156999/99030058-0f3b9680-25af-11eb-9904-e3ad41986498.jpg)| |![party7](https://user-images.githubusercontent.com/26156999/99029680-08605400-25ae-11eb-8ed2-988a149ace78.jpg)|![party7](https://user-images.githubusercontent.com/26156999/99029881-9b998980-25ae-11eb-9287-298a595d36cb.jpg)|![party7_out](https://user-images.githubusercontent.com/26156999/99030070-15317780-25af-11eb-89cf-f04a92bb6960.jpg)|

Hi. I add new weights in google drive, you can find in the readme. I also upload tensorflow version weights named `whitebox-tf.zip`.

I found the strange color caused by `guided filter`, but now I didn't find a better method to solve it.

ok. I will try if time permits

@GustavoStahl thanks, I missing the test_code ε value is not equal to train_code ε. But I don't think the *color transfer algorithm* is needed. For this model, it needs to...

mobilenetv1 0.75-yolov3 with 2 detect layers, .h5 file about 13mb, 65 [email protected] on voc . But this repo cannot be achieved, because the optimization part is done for others. I've...

@EunseongBoo you need to use a callback to monitor accuracy. usually, I training 75 epoch got the best model.

应该是数据集类别数量和训练时指定的类别数量不同导致的。你可以将自定义数据集做成voc的格式,这样防止自定义数据集时写代码处理出错的可能性。

检查你生成的数据集label,看看有没有大于6的值。 发自我的iPhone ------------------ 原始邮件 ------------------ 发件人: Kearney ***@***.***> 发送时间: 2022年3月16日 23:40 收件人: zhen8838/K210_Yolo_framework ***@***.***> 抄送: 郑启航 ***@***.***>, Comment ***@***.***> 主题: 回复:[zhen8838/K210_Yolo_framework] 自定义数据集,成功导出anchor.npy和img_ann.npy,然后在训练时却发生如下错误 (#20) 蹲一下后续。我用公开的数据(http://faculty.neu.edu.cn/songkechen/zh_CN/zdylm/263270/list/index.htm),六类数据 修改了参数 CLSNUM=6 ,莫非是我其它参数没改? make anchors DATASET=voc...