Open kpis-msa opened 3 years ago
Hello, did you solve this problem? I got the same problem, I hope you can share the method to me, thank you so much!
In fact, in opts.py file of the original poject, too many parameters were set to None, and I don't even know how to complement it.
Any leads on this?
I used the following command to perform predictions using the pre-trained models
"python main.py --root_path "+%directory path where the data is stored%+" --video_path %path to extracted jpg% --annotation_path test.json "+"--result_path results --dataset %does not really matter but put ucf101 or kinetics% --resume_path "+%model_path%+" --model_depth 50 --n_classes 700 --no_train --no_val --inference --output_topk 1 --inference_batch_size 1"
Here I create the test.json myself. An entry in the json would look something like this:
{
"labels": [%labels list%],
"database":
{
"%video_id%":
{
"subset": "%subsetname eg. validation, train%",
"annotations":
{
"segment": [ %start frame num%, %end frame num%]
}
"video_path" : "%absolute path to video%"
}
%next video id%:
{
%same as above %
}
}
}
Could you please elaborate what "annotations" should be in the case of test videos?
you need to add a dictionary that contains the "segment" key and the value for this key would be a list of 2 numbers. And those 2 numbers would be the starting and ending frame number
Can you share the code that generated this. json file? Thank you! @Purav-Zumkhawala
I'd like to use this model using the Japanese dataset as follows: https://actions.stair.center/
But I don't have an annotation JSON file for the below option. --annotation_path kinetics.json
Please tell me how to predict using a trained model (~/data/results/save_200.pth.)