What is inside your brm.7z file (e.g., images, CSVs, or R model files)?
Load a model (e.g., VGG16, ResNet) and use it as a "feature_extractor" by targeting the flatten or global pooling layer. brm.7z
If the file contains video for biological research, tools like DeepEthogram use a spatial feature extractor to produce separate estimates of behavior probability. Summary Workflow Extract: Unzip brm.7z to a local directory. What is inside your brm
Use 7-Zip or the py7zr library in Python to extract the contents. Summary Workflow Extract: Unzip brm
Once the data is extracted, you can use a pre-trained neural network to "produce deep features" (also called embeddings). This involves passing the data through the network and capturing the output of an intermediate hidden layer rather than the final classification layer.
If the file relates to "Deep-FS" or Deep Boltzmann Machines, you can use Restricted Boltzmann Machines (RBMs) to learn and extract hierarchical features directly from the raw representation.