import zipfile import os def extract_and_process(zip_path): # 1. Extract the zip extract_dir = "extracted_vids" with zipfile.ZipFile(zip_path, 'r') as zip_ref: zip_ref.extractall(extract_dir) # 2. Iterate through videos and generate features # This part depends on your specific 'feature generation' tool print(f"Processing videos in {extract_dir} for SfM features...") # Placeholder for your specific SFM command: # os.system(f"python extract_features.py --input {extract_dir} --output features.h5") # Usage # extract_and_process('26RegionSFM_31_short_vids.zip') Use code with caution. Copied to clipboard Next Steps
are you using? (e.g., COLMAP, OpenSfM, or a custom deep learning repo). 26RegionSFM_31_short_vids.zip
: Match those features across regions or frames to build the SfM model. Example: Feature Extraction Script (Python) Copied to clipboard Next Steps are you using
: Use a model (like SIFT, SuperPoint, or a Region-based CLIP model) to generate descriptors. Example: Feature Extraction Script (Python) : Use a
If this is part of a standard vision pipeline, you generally need to: : Extract the frames from the short videos.
If you are using a tool like SlowFast Feature Extractor or a RegionCLIP based approach, you can use a script similar to this to process your zip:
To provide the exact "generate feature" command or code, could you clarify: