Comments (3)
Hello
I'm new to programming and I am unable to understand the execution steps to be followed to see the output . Please guide the sequence of execution in order to see the output
from anomaly-detection-in-surveillance-videos.
Hello, I apologise for such a late reply.
The outline depends on why you are doing this project.
Assuming you want a working model with not much intention to research and extend this, you can start with
- downloading the data set.
- Data processing.
- Using C3D pre trained model on sport1m to extract features for your data set (I will not get into fine tuning under the assumption).
- Convert those feature using the MATLAB script provided by C3D into real valued data as per you requirement(make a csv for simple implementation).
- Code the architecture mentioned in the paper using you favourite deep learning library (tensorflow vs pytorch vs caffe2).
- Run it and report the results.
The necessary details about the hyper parameters and regularisation is all mentioned in the paper I have cited. Please read the paper and understand the idea first. Hope this helps
from anomaly-detection-in-surveillance-videos.
Hello,
Love your work here thanks so much, As @Shiny128 said, please help out the detail of what to run and execute to get the final result from training the model to predicting the anomaly.
thank you
from anomaly-detection-in-surveillance-videos.
Related Issues (20)
- About download datasets HOT 2
- how did you convert video into vectors. I guess the code for that is missing. HOT 1
- Sequence of execution of the following steps HOT 3
- The display of `epoch_loss`
- The difference of model between model.ckpt.meta and the code
- The implementation of loss function HOT 1
- Not able to start a tensor flow session HOT 1
- What is the difference between this git and this git : https://github.com/WaqasSultani/AnomalyDetectionCVPR2018?
- Can you tell me some details about the environment of implementation
- How to run this on a live video to test accuracy ?
- How to implement this project? HOT 1
- Dataset
- Error in anomaly_NN.py HOT 1
- How to implement the project?? HOT 1
- About the result HOT 2
- Hello HOT 1
- Feature Extraction HOT 2
- Extracted Features HOT 1
- input_feature_vector_gen.py issue HOT 5
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from anomaly-detection-in-surveillance-videos.