Comments (4)
For the pytorch version, it should be 0.2 or 0.3 because this is a project developed 2 years ago. But if you want to work with the latest pytorch version, it should be fine or requiring very minimum of change because this repo doesn't have any customized layer or operation.
Since this is a standard classification problem, the speed is just the network's speed. I mean, if you know resnet50's speed, our model should have the same speed.
Other requirements may be just opencv.
from two-stream-pytorch.
can we use the python-opencv, not the make version from source code?
from two-stream-pytorch.
If you want to extract optical flow, you need build from source.
But if you only want to train the model, no matter spatial stream or temporal stream, python-opencv is enough.
from two-stream-pytorch.
ok, thank you!
from two-stream-pytorch.
Related Issues (20)
- About pre-trained Model HOT 2
- test video HOT 5
- Question about training the models together HOT 2
- Different running env? HOT 5
- Can you provide your results for loss and accuracy values of spatial and temporal training?
- The number of GPUs? HOT 1
- I use your restnet152 model parameters for testing, but in split_1 the accuracy is only 67.59%.
- Use the video input from the camera for action recognition HOT 7
- Problems about VideoSpatialPrediction.py HOT 2
- How is the two streams fused ? HOT 1
- What is the accuracy of UCF101?
- what's version of pytorch and cuda
- dense_flow 可不可以在windows安装 HOT 1
- 如果没有安装dense_flow,运行build_of.py文件,是不是不会运行出结果 HOT 1
- fusion two stream feature?
- a PROBLEM when using VGG as motion model
- 老师我想问下怎么late fusion呀 HOT 1
- 关于抽帧的图片存放路径 HOT 2
- video sampling rate in training two-stream network
- About parameter --new_length in training RGB videos
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