-
Notifications
You must be signed in to change notification settings - Fork 11
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
The pretrain model on Gen1 dataset #13
Comments
Excuse me, Did you encounter the following issue when training gen1 data? |
I don't encounter this issue. And I think it seems like an issue about channel setting, I suggest tocheck the config on *.yaml. |
I changed the yolo.py and common.py from yolov3 source code, did you change these too? |
Hello, may I ask how you downloaded the dataset? Can you please let me know |
You can download dataset at https://www.prophesee.ai/2020/01/24/prophesee-gen1-automotive-detection-dataset/ |
@Orekishiro I can train now!, but when I did val, my P、R、map all are zero. Did you changed the val or something else? Or you have already tested on your test_data? |
I did not directly run val.py, and the image shown in this issue is automatically generated after the training is completed. To run train_g1.py, I delete some unused code in val.py, such as DetectMultiBackend and plots code, they don't influence the results of the inference stage. You say that the P、R、mAP are all zero, I guess the reason is that the format of the target label. |
感謝你的回覆! 我再去試試看有關val的部分以及我的label格式,你方便加個discord嗎名字是diopang,我是碩士生現在正在研究關於event camera用SNN做object detection |
May I ask how the event data was placed in the folder? I have been confused by this question for some time |
EMS-YOLO他这个框架的逻辑,应该是先用give_g1_data.py缓存下来了事件表示和label标签,之后再用datasets_g1T.py进行加载。 |
非常感谢您的回复! |
@Orekishiro 所以你會先用give_g1_data.py 生成出.npy檔案後 再用datasets_g1T來create_dataloader是嗎 |
这个没有,我没用他原来代码读取。我是先找label的时间戳,然后截取这一段的事件转为numpy存储,同时生成事件表示,再重写了一个Dataset读的numpy文件,其实逻辑和原EMS是相同的。 |
@Orekishiro 你有看過他對應的img跟label的anchor嗎 我顯示後發現anchor都歪掉 |
但是我如果將label的框往左上角調整,就會換成我training時的框也跟著往左上角偏移導致沒有抓到 |
@Orekishiro 请问您有没有遇到过这个tensor的问题, File "E:\EMS-YOLO-main\models\yolo.py", line 137, in forward
|
@Orekishiro 感謝你的回覆! 想問你有對val.py做修改嗎,因為我發現蠻多部分有缺少的 |
你可以看一下yolo.py和common.py中time_window这个参数的设置是否一样;在yolo.py里经过forward函数时,根据时间步长time_window将输入复制,输入的shape为(time_window,batch_size,C,H,W),与commom.py中的mem_update函数就可以对上了。 |
这里我记得我好像是直接将那个import DetectMultiBackend给注释掉了,其他部分好像没有太修改,这个具体的记不太清了。 |
非常感谢您的回复,我再多尝试下 |
@Orekishiro 请问您选的什么初始权重文件呢? |
我之前拿Res10跑的,没加权重;后来的Res34也没加,可能加载coco的权重会提高一些性能。 |
好滴好滴,谢谢您的回复! |
好的了解! 但我試了一下我的label格式跟train格式都是由give_g1_data.py生的create_dataloader,所以應該會一樣才對,但不知為啥map P R皆為0,網路上說有可能是cuda pytroch版本問題,想問一下你的這兩個版本是啥 謝謝 |
@Orekishiro 有關def non_max_suppression你有發現他回傳的output會跟Label一樣嗎 |
In your paper, you use EMS-Res10 model and achieve 0.267 mAP on Gen1 Dataset, but I used the framework you provided to train on the Gen1 dataset, I couldn't get good results.
I don't know if there were some problems in my training stage, so could you provide the trained model on Gen1 Dataset?
The text was updated successfully, but these errors were encountered: