danbochman / real-time-action-recognition Goto Github PK

Hey while running the following command
python spatial_cnn_cpu.py --resume model_best.pth.tar --demo

I got this pickle error
File "spatial_cnn_cpu.py", line 38, in main
train_loader, test_loader, test_video = data_loader.run()
File "C:\Users\LeNoVo T430\Desktop\Real-Time-Action-Recognition\dataloader\spatial_dataloader.py", line 96, in run
self.load_frame_count()
File "C:\Users\LeNoVo T430\Desktop\Real-Time-Action-Recognition\dataloader\spatial_dataloader.py", line 85, in load_frame_count
dic_frame = pickle.load(file)

_pickle.UnpicklingError: the STRING opcode argument must be quoted

plz guide me how can i solve this problem

Hi @danbochman

Can we train it on Custom Video Data set with 8 classes.

Please help me..

Hy sir! you suggest me that i should change my python version.
Then i shift to Linux Operating System because it already give me that version of python and i already have this OS on my laptop.
Sir the pickle error is solved...
But Sir I got another error which is this one

salmaucp@salmaucp-ThinkPad-T430s:~/Real-Time-Action-Recognition$ python spatial_cnn_cpu.py --resume model_best.pth.tar --demo
Namespace(batch_size=8, demo=True, epochs=500, evaluate=False, lr=0.0005, resume='model_best.pth.tar', start_epoch=0)
==> (Training video, Validation video):( 9537 3783 )
==> sampling testing frames
==> Training data : 9537 frames
Traceback (most recent call last):
File "spatial_cnn_cpu.py", line 333, in
main()
File "spatial_cnn_cpu.py", line 37, in main
train_loader, test_loader, test_video = data_loader.run()
File "/home/salmaucp/Real-Time-Action-Recognition/dataloader/spatial_dataloader.py", line 98, in run
train_loader = self.train()
File "/home/salmaucp/Real-Time-Action-Recognition/dataloader/spatial_dataloader.py", line 131, in train
print training_set[1][0]['img1'].size()
File "/home/salmaucp/Real-Time-Action-Recognition/dataloader/spatial_dataloader.py", line 59, in getitem
data[key] = self.load_ucf_image(video_name, index)
File "/home/salmaucp/Real-Time-Action-Recognition/dataloader/spatial_dataloader.py", line 29, in load_ucf_image
img = Image.open(path + 'frame{}.jpg'.format(str(index).zfill(6)))
File "/home/salmaucp/.local/lib/python2.7/site-packages/PIL/Image.py", line 2766, in open
fp = builtins.open(filename, "rb")
IOError: [Errno 2] No such file or directory: '/hdd/UCF-101/Data/jpegs_256/v_Swing_g09_c02/frame000031.jpg'

Sir I tried to solved it by downloading ucf jpeg 256 parts but i cant get required output
Sir please Guide me over this problem. kindly please guide me sir!!!
Thank You So mUch...

Hello Sir,
I am trying to use your code but I am getting this error
File "/home/mab73/anaconda2/lib/python2.7/site-packages/torchvision/transforms/transforms.py", line 60, in __call__ img = t(img) File "/home/mab73/anaconda2/lib/python2.7/site-packages/torchvision/transforms/transforms.py", line 163, in __call__ return F.normalize(tensor, self.mean, self.std, self.inplace) File "/home/mab73/anaconda2/lib/python2.7/site-packages/torchvision/transforms/functional.py", line 206, in normalize mean = torch.tensor(mean, dtype=torch.float32) AttributeError: 'module' object has no attribute 'float32'
I am using torch 0.3.1 with cuda 8.0. Any idea what is going on, are you using different torch version?

File "spatial_cnn_cpu.py", line 5, in
from dataloader import UCF101_splitter
ImportError: cannot import name 'UCF101_splitter'

Hi
Thank you for your great work first!
However I got a question on the accuracy of the real time recognition
I just cloned your repo, modified some code to adapt to py 3.5 and deleted all code about training and evaling.
After downloading your pretrained model, by running spatial_cnn_cpu.py, I can get the recognition result but the accuracy is low and the confidence score is only about 0.45 maximum, quite different from the demo video given in the repo.
Is that in the demo video you are running on a gpu, using both spatial cnn and motion cnn, and finally fused the result?
Or in spatial_cnn_cpu.py you just use rgb as input, but in spatial_cnn_gpu, optflow also?